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Title: Lyapunov-Based Control Design for Uncertain MIMO Systems.
Creator: Wang, Zhao, Behal, Aman, Boloni, Ladislau, Haralambous, Michael, University of Central Florida
Abstract / Description: In this dissertation. we document the progress in the control design for a class of MIMO nonlinear uncertain system from five papers. In the first part, we address the problem of adaptive control design for a class of multi-input multi-output (MIMO)nonlinear systems. A Lypaunov based singularity free control law, which compensates for parametric uncertainty in both the drift vector and the input gain matrix, is proposed under the mild assumption that the signs of the leading minors of...
Show moreIn this dissertation. we document the progress in the control design for a class of MIMO nonlinear uncertain system from five papers. In the first part, we address the problem of adaptive control design for a class of multi-input multi-output (MIMO)nonlinear systems. A Lypaunov based singularity free control law, which compensates for parametric uncertainty in both the drift vector and the input gain matrix, is proposed under the mild assumption that the signs of the leading minors of thecontrol input gain matrix are known. Lyapunov analysis shows global uniform ultimate boundedness (GUUB) result for the tracking error under full state feedback (FSFB). Under the restriction that only the output vector is available for measurement, an output feedback (OFB) controller is designed based on a standard high gain observer (HGO) (-) stability under OFB is fostered by the uniformity of the FSFB solution. Simulation results for both FSFB and OFB controllers demonstrate the ef?cacy of the MIMO control design in the classical 2-DOF robot manipulator model.In the second part, an adaptive feedback control is designed for a class of MIMO nonlinear systems containing parametric uncertainty in both the drift vector and the input gain matrix, which is assumed to be full-rank and non-symmetric in general. Based on an SDU decomposition of the gain matrix, a singularity-free adaptive tracking control law is proposed that is shown to be globally asymptotically stable (GAS) under full-state feedback. Output feedback results are facilitated via the use of a high-gain observer (HGO). Under output feedback control, ultimate boundedness of the error signals is obtained (&)#241; the size of the bound is related to the size of the uncertainty in the parameters. An explicit upper bound is also provided on the size of the HGO gain constant.In third part, a class of aeroelastic systems with an unmodeled nonlinearity and external disturbance is considered. By using leading- and trailing-edge control surface actuations, a full-state feedforward/feedback controller is designed to suppress the aeroelastic vibrations of a nonlinear wing section subject to external disturbance. The full-state feedback control yields a uniformly ultimately bounded result for two-axis vibration suppression. With the restriction that only pitching and plunging displacements are measurable while their rates are not, a high-gain observer is used to modify the full-state feedback control design to an output feedback design. Simulation results demonstrate the ef ? cacy of the multi-input multi-output control toward suppressing aeroelastic vibration and limit cycle oscillations occurring in pre and post? utter velocity regimes when the system is subjected to a variety of external disturbance signals. Comparisons are drawn with a previously designed adaptive multi-input multi-output controller.In the fourth part, a continuous robust feedback control is designed for a class of high-order multi-input multi-output (MIMO) nonlinear systems with two degrees of freedom containing unstructured nonlinear uncertainties in the drift vector and parametric uncertainties in the high frequency gain matrix, which is allowed to be non-symmetric in general. Given some mild assumptions on the system model, a singularity-free continuous robust tracking control law is designed that is shown to be semi-globally asymptotically stable under full-state feedback through a Lyapunov stability analysis. The performance of the proposed algorithm have been verified on a two-link robot manipulator model and 2-DOF aeroelastic model.
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Date Issued: 2012
Identifier: CFE0004345, ucf:49420
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0004345

Title: Optimization Approaches for Electricity Generation Expansion Planning Under Uncertainty.
Creator: Zhan, Yiduo, Zheng, Qipeng, Vela, Adan, Garibay, Ivan, Sun, Wei, University of Central Florida
Abstract / Description: In this dissertation, we study the long-term electricity infrastructure investment planning problems in the electrical power system. These long-term capacity expansion planning problems aim at making the most effective and efficient investment decisions on both thermal and wind power generation units. One of our research focuses are uncertainty modeling in these long-term decision-making problems in power systems, because power systems' infrastructures require a large amount of investments,...
Show moreIn this dissertation, we study the long-term electricity infrastructure investment planning problems in the electrical power system. These long-term capacity expansion planning problems aim at making the most effective and efficient investment decisions on both thermal and wind power generation units. One of our research focuses are uncertainty modeling in these long-term decision-making problems in power systems, because power systems' infrastructures require a large amount of investments, and need to stay in operation for a long time and accommodate many different scenarios in the future. The uncertainties we are addressing in this dissertation mainly include demands, electricity prices, investment and maintenance costs of power generation units. To address these future uncertainties in the decision-making process, this dissertation adopts two different optimization approaches: decision-dependent stochastic programming and adaptive robust optimization. In the decision-dependent stochastic programming approach, we consider the electricity prices and generation units' investment and maintenance costs being endogenous uncertainties, and then design probability distribution functions of decision variables and input parameters based on well-established econometric theories, such as the discrete-choice theory and the economy-of-scale mechanism. In the adaptive robust optimization approach, we focus on finding the multistage adaptive robust solutions using affine policies while considering uncertain intervals of future demands.This dissertation mainly includes three research projects. The study of each project consists of two main parts, the formulation of its mathematical model and the development of solution algorithms for the model. This first problem concerns a large-scale investment problem on both thermal and wind power generation from an integrated angle without modeling all operational details. In this problem, we take a multistage decision-dependent stochastic programming approach while assuming uncertain electricity prices. We use a quasi-exact solution approach to solve this multistage stochastic nonlinear program. Numerical results show both computational efficient of the solutions approach and benefits of using our decision-dependent model over traditional stochastic programming models. The second problem concerns the long-term investment planning with detailed models of real-time operations. We also take a multistage decision-dependent stochastic programming approach to address endogenous uncertainties such as generation units' investment and maintenance costs. However, the detailed modeling of operations makes the problem a bilevel optimization problem. We then transform it to a Mathematic Program with Equilibrium Constraints (MPEC) problem. We design an efficient algorithm based on Dantzig-Wolfe decomposition to solve this multistage stochastic MPEC problem. The last problem concerns a multistage adaptive investment planning problem while considering uncertain future demand at various locations. To solve this multi-level optimization problem, we take advantage of affine policies to transform it to a single-level optimization problem. Our numerical examples show the benefits of using this multistage adaptive robust planning model over both traditional stochastic programming and single-level robust optimization approaches. Based on numerical studies in the three projects, we conclude that our approaches provide effective and efficient modeling and computational tools for advanced power systems' expansion planning.
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Date Issued: 2016
Identifier: CFE0006676, ucf:51248
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0006676

Title: ROBUSTNESS ANALYSIS FOR TURBOMACHINERY STALL FLUTTER.
Creator: Forhad, Md, Xu, Yunjun, University of Central Florida
Abstract / Description: Flutter is an aeroelastic instability phenomenon that can result either in serious damage or complete destruction of a gas turbine blade structure due to high cycle fatigue. Although 90% of potential high cycle fatigue occurrences are uncovered during engine development, the remaining 10% stand for one third of the total engine development costs. Field experience has shown that during the last decades as much as 46% of fighter aircrafts were not mission-capable in certain periods due to high...
Show moreFlutter is an aeroelastic instability phenomenon that can result either in serious damage or complete destruction of a gas turbine blade structure due to high cycle fatigue. Although 90% of potential high cycle fatigue occurrences are uncovered during engine development, the remaining 10% stand for one third of the total engine development costs. Field experience has shown that during the last decades as much as 46% of fighter aircrafts were not mission-capable in certain periods due to high cycle fatigue related mishaps. To assure a reliable and safe operation, potential for blade flutter must be eliminated from the turbomachinery stages. However, even the most computationally intensive higher order models of today are not able to predict flutter accurately. Moreover, there are uncertainties in the operational environment, and gas turbine parts degrade over time due to fouling, erosion and corrosion resulting in parametric uncertainties. Therefore, it is essential to design engines that are robust with respect to the possible uncertainties. In this thesis, the robustness of an axial compressor blade design is studied with respect to parametric uncertainties through the Mu analysis. The nominal flutter model is adopted from . This model was derived by matching a two dimensional incompressible flow field across the flexible rotor and the rigid stator. The aerodynamic load on the blade is derived via the control volume analysis. For use in the Mu analysis, first the model originally described by a set of partial differential equations is reduced to ordinary differential equations by the Fourier series based collocation method. After that, the nominal model is obtained by linearizing the achieved non-linear ordinary differential equations. The uncertainties coming from the modeling assumptions and imperfectly known parameters and coefficients are all modeled as parametric uncertainties through the Monte Carlo simulation. As compared with other robustness analysis tools, such as Hinf, the Mu analysis is less conservative and can handle both structured and unstructured perturbations. Finally, Genetic Algorithm is used as an optimization tool to find ideal parameters that will ensure best performance in terms of damping out flutter. Simulation results show that the procedure described in this thesis can be effective in studying the flutter stability margin and can be used to guide the gas turbine blade design.
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Date Issued: 2011
Identifier: CFE0003999, ucf:48666
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0003999

Title: Multi-level Optimization and Applications with Non-Traditional Game Theory.
Creator: Yun, Guanxiang, Zheng, Qipeng, Boginski, Vladimir, Karwowski, Waldemar, Yong, Jiongmin, University of Central Florida
Abstract / Description: We study multi-level optimization problem on energy system, transportation system and information network. We use the concept of boundedly rational user equilibrium (BRUE) to predict the behaviour of users in systems. By using multi-level optimization method with BRUE, we can help to operate the system work in a more efficient way. Based on the introducing of model with BRUE constraints, it will lead to the uncertainty to the optimization model. We generate the robust optimization as the...
Show moreWe study multi-level optimization problem on energy system, transportation system and information network. We use the concept of boundedly rational user equilibrium (BRUE) to predict the behaviour of users in systems. By using multi-level optimization method with BRUE, we can help to operate the system work in a more efficient way. Based on the introducing of model with BRUE constraints, it will lead to the uncertainty to the optimization model. We generate the robust optimization as the multi-level optimization model to consider for the pessimistic condition with uncertainty. This dissertation mainly includes four projects. Three of them use the pricing strategy as the first level optimization decision variable. In general, our models' first level's decision variables are the measures that we can control, but the second level's decision variables are users behaviours that can only be restricted within BRUE with uncertainty.
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Date Issued: 2019
Identifier: CFE0007881, ucf:52758
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0007881

Title: VISION BASED TRAJECTORY TRACKING OF SPACE DEBRIS IN CLOSE PROXIMITY VIA INTEGRATED ESTIMATION AND CONTROL.
Creator: Li, Ni, Xu, Yunjun, University of Central Florida
Abstract / Description: The increasingly cluttered environment in space is placing a premium on techniques capable of tracking and estimating the trajectory of space debris. Unlike the debris smaller than 1 cm or larger than 10 cm, it is always a challenge for spacecraft or satellite mission designers to consider explicitly the ones ranged from 1 cm to 10 cm a priori. To tackle this challenge, a vision based debris' trajectory tracking method in close proximity using two cameras onboard satellites in a formation is...
Show moreThe increasingly cluttered environment in space is placing a premium on techniques capable of tracking and estimating the trajectory of space debris. Unlike the debris smaller than 1 cm or larger than 10 cm, it is always a challenge for spacecraft or satellite mission designers to consider explicitly the ones ranged from 1 cm to 10 cm a priori. To tackle this challenge, a vision based debris' trajectory tracking method in close proximity using two cameras onboard satellites in a formation is presented in the thesis. Also to differentiate the target debris from other clutters, data association is investigated. A two-stage nonlinear robust controller is developed to adjust the attitude of the satellites such that the desired field of view can be achieved for the target debris. Capabilities of the proposed integrated estimation and control methods are validated in the simulations.
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Date Issued: 2011
Identifier: CFE0003731, ucf:48775
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0003731

Title: Study of Novel Power Semiconductor Devices for Performance and Reliability.
Creator: Padmanabhan, Karthik, Yuan, Jiann-Shiun, Sundaram, Kalpathy, Atia, George, DeMara, Ronald, Chow, Lee, University of Central Florida
Abstract / Description: Power Semiconductor Devices are crucial components in present day power electronic systems. The performance and efficiency of the devices have a direct correlation with the power system efficiency. This dissertation will examine some of the components that are commonly used in a power system, with emphasis on their performance characteristics and reliability. In recent times, there has a proliferation of charge balance devices in high voltage discrete power devices. We examine the same charge...
Show morePower Semiconductor Devices are crucial components in present day power electronic systems. The performance and efficiency of the devices have a direct correlation with the power system efficiency. This dissertation will examine some of the components that are commonly used in a power system, with emphasis on their performance characteristics and reliability. In recent times, there has a proliferation of charge balance devices in high voltage discrete power devices. We examine the same charge balance concept in a fast recovery diode and a MOSFET. This is crucial in the extending system performance at compact dimensions. At smaller device and system sizes, the performance trade-off between the ON and OFF states becomes all the more critical. The focus on reducing the switching losses while maintaining system reliability increases. In a conventional planar technology, the technology places a limit on the switching performance owing to the larger die sizes. Using a charge balance structure helps achieve the improved trade-off, while working towards ultimately improving system reliability, size and cost.Chapter 1 introduces the basic power system based on an inductive switching circuit, and the various components that determine its efficiency. Chapter 2 presents a novel Trench Fast Recovery Diode (FRD) structure with injection control is proposed in this dissertation. The proposed structure achieves improved carrier profile without the need for excess lifetime control. This substantially improves the device performance, especially at extreme temperatures (-40oC to 175oC). The device maintains low leakage at high temperatures, and it's Qrr and Irm do not degrade as is the usual case in heavily electron radiated devices. A 1600 diode using this structure has been developed, with a low forward turn-on voltage and good reverse recovery properties. The experimental results show that the structure maintains its performance at high temperatures.In chapter 3, we develop a termination scheme for the previously mentioned diode. A major limitation on the performance of high voltage power semiconductor is the edge termination of the device. It is critical to maintain the breakdown voltage of the device without compromising the reliability of the device by controlling the surface electric field. A good termination structure is critical to the reliability of the power semiconductor device. The proposed termination uses a novel trench MOS with buried guard ring structure to completely eliminate high surface electric field in the silicon region of the termination. The termination scheme was applied towards a 1350 V fast recovery diode, and showed excellent results. It achieved 98% of parallel plane breakdown voltage, with low leakage and no shifts after High Temperature Reverse Bias testing due to mobile ion contamination from packaging mold compound.In chapter 4, we also investigate the device physics behind a superjunction MOSFET structure for improved robustness. The biggest issue with a completely charge balanced MOSFET is decreased robustness in an Unclamped Inductive Switching (UIS) Circuit. The equally charged P and N pillars result in a flat electric field profile, with the peak carrier density closer to the P-N junction at the surface. This results in an almost negligible positive dynamic Rds-on effect in the MOSFET. By changing the charge profile of the P-column, either by increasing it completely or by implementing a graded profile with the heavier P on top, we can change the field profile and shift the carrier density deeper into silicon, increasing the positive dynamic Rds-on effect. Simulation and experimental results are presented to support the theory and understanding.Chapter 5 summarizes all the theories presented and the contributions made by them in the field. It also seeks to highlight future work to be done in these areas.
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Date Issued: 2016
Identifier: CFE0006158, ucf:51148
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0006158

Title: Modeling and Contour Control of Multi-Axis Linear Driven Machine Tools.
Creator: Zhao, Ran, Lin, Kuo-Chi, Xu, Chengying, Bai, Yuanli, Das, Tuhin, An, Linan, University of Central Florida
Abstract / Description: In modern manufacturing industries, many applications require precision motion control of multi-agent systems, like multi-joint robot arms and multi-axis machine tools. Cutter (end effector) should stay as close as possible to the reference trajectory to ensure the quality of the final products. In conventional computer numerical control (CNC), the control unit of each axis is independently designed to achieve the best individual tracking performance. However, this becomes less effective when...
Show moreIn modern manufacturing industries, many applications require precision motion control of multi-agent systems, like multi-joint robot arms and multi-axis machine tools. Cutter (end effector) should stay as close as possible to the reference trajectory to ensure the quality of the final products. In conventional computer numerical control (CNC), the control unit of each axis is independently designed to achieve the best individual tracking performance. However, this becomes less effective when dealing with multi-axis contour following tasks because of the lack of coordination among axes. This dissertation studies the control of multi-axis machine tools with focus on reducing the contour error. The proposed research explicitly addresses the minimization of contour error and treats the multi-axis machine tool as a multi-input-multi-output (MIMO) system instead of several decoupled single-input-single-output (SISO) systems. New control schemes are developed to achieve superior contour following performance even in the presence of disturbances. This study also extends the applications of the proposed control system from plane contours to regular contours in R3. The effectiveness of the developed control systems is experimentally verified on a micro milling machine.
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Date Issued: 2014
Identifier: CFE0005287, ucf:50552
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0005287

Title: Lyapunov-Based Robust and Adaptive Control Design for nonlinear Uncertain Systems.
Creator: Zhang, Kun, Behal, Aman, Haralambous, Michael, Xu, Yunjun, Boloni, Ladislau, Marzocca, Piergiovanni, University of Central Florida
Abstract / Description: The control of systems with uncertain nonlinear dynamics is an important field of control scienceattracting decades of focus. In this dissertation, four different control strategies are presentedusing sliding mode control, adaptive control, dynamic compensation, and neural network for a nonlinear aeroelastic system with bounded uncertainties and external disturbance. In Chapter 2, partial state feedback adaptive control designs are proposed for two different aeroelastic systems operating in...
Show moreThe control of systems with uncertain nonlinear dynamics is an important field of control scienceattracting decades of focus. In this dissertation, four different control strategies are presentedusing sliding mode control, adaptive control, dynamic compensation, and neural network for a nonlinear aeroelastic system with bounded uncertainties and external disturbance. In Chapter 2, partial state feedback adaptive control designs are proposed for two different aeroelastic systems operating in unsteady flow. In Chapter 3, a continuous robust control design is proposed for a class of single input and single output system with uncertainties. An aeroelastic system with a trailingedge flap as its control input will be considered as the plant for demonstration of effectiveness of the controller. The controller is proved to be robust by both athematical proof and simulation results. In Chapter 3, a robust output feedback control strategy is discussed for the vibration suppression of an aeroelastic system operating in an unsteady incompressible flowfield. The aeroelastic system is actuated using a combination of leading-edge (LE) and trailing-edge (TE) flaps in the presence of different kinds of gust disturbances. In Chapter 5, a neural-network based model-free controller is designed for an aeroelastic system operating at supersonic speed. The controller is shown to be able to effectively asymptotically stabilize the system via both a Lyapunov-based stability proof and numerical simulation results.
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Date Issued: 2015
Identifier: CFE0005748, ucf:50110
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0005748

Title: Pressure Image Based Attitude Controller for Small Unmanned Aerial Vehicles.
Creator: Thompson, Kenneth, Xu, Yunjun, Gou, Jihua, Lin, Kuo-Chi, University of Central Florida
Abstract / Description: As technology improves, small unmanned aerial vehicles (SUAV) have been identified for their utility in a variety of applications in which larger unmanned craft may be incapable of accomplishing mission objectives. These aircraft with their small size and long flight durations are ideal for hazardous inspection and long duration surveillance missions. One challenge preventing the widespread adoption of these systems is their instability to abrupt changes in the flow field around them due to...
Show moreAs technology improves, small unmanned aerial vehicles (SUAV) have been identified for their utility in a variety of applications in which larger unmanned craft may be incapable of accomplishing mission objectives. These aircraft with their small size and long flight durations are ideal for hazardous inspection and long duration surveillance missions. One challenge preventing the widespread adoption of these systems is their instability to abrupt changes in the flow field around them due to wind gusts or flow separation.Currently, traditional rigid body based sensors are implemented in their flight control systems, which are sufficient in higher inertia aircraft for accurate control.However, in low inertia SUAV applications during a flow event, often, the inertial sensors are incapable of detecting the event before catastrophic failure.A method of directly measuring the flow information around the SUAV in order to generate control commands will improve the stability of these systems by allowing these systems to directly react to flow events.In contrast, established inertial based control systems can only react to changes in vehicle dynamics caused by flow events.Such a method is developed utilizing a network of pressure and shear sensors embedded in the wing and used to create (")flow images(") which can be easily manipulated to generate control commands.A method of accurately calculating the aerodynamic moment acting on the aircraft based on the flow image is also developed for implementation of flow image-based control in real world systems.
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Date Issued: 2018
Identifier: CFE0007417, ucf:52722
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0007417

Title: Development of an Adaptive Restoration Tool For a Self-Healing Smart Grid.
Creator: Golshani, Amir, Sun, Wei, Qu, Zhihua, Vosoughi, Azadeh, Zhou, Qun, Zheng, Qipeng, University of Central Florida
Abstract / Description: Large power outages become more commonplace due to the increase in both frequency and strength of natural disasters and cyber-attacks. The outages and blackouts cost American industries and business billions of dollars and jeopardize the lives of hospital patients. The losses can be greatlyreduced with a fast, reliable and flexible restoration tool. Fast recovery and successfully adapting to extreme events are critical to build a resilient, and ultimately self-healing power grid. This...
Show moreLarge power outages become more commonplace due to the increase in both frequency and strength of natural disasters and cyber-attacks. The outages and blackouts cost American industries and business billions of dollars and jeopardize the lives of hospital patients. The losses can be greatlyreduced with a fast, reliable and flexible restoration tool. Fast recovery and successfully adapting to extreme events are critical to build a resilient, and ultimately self-healing power grid. This dissertation is aimed to tackle the challenging task of developing an adaptive restoration decisionsupport system (RDSS). The RDSS determines restoration actions both in planning and real-time phases and adapts to constantly changing system conditions. First, an efficient network partitioning approach is developed to provide initial conditions for RDSS by dividing large outage network into smaller islands. Then, the comprehensive formulation of RDSS integrates different recovery phases into one optimization problem, and encompasses practical constraints including AC powerflow, dynamic reserve, and dynamic behaviors of generators and load. Also, a frequency constrained load recovery module is proposed and integrated into the RDSS to determine the optimal location and amount of load pickup. Next, the proposed RDSS is applied to harness renewable energy sources and pumped-storage hydro (PSH) units by addressing the inherent variabilities and uncertainties of renewable and coordinating wind and PSH generators. A two-stage stochastic and robust optimization problem is formulated, and solved by the integer L-shaped and column-and-constraintsgeneration decomposition algorithms. The developed RDSS tool has been tested onthe modified IEEE 39-bus and IEEE 57-bus systems under different scenarios. Numerical results demonstrate the effectiveness and efficiency of the proposed RDSS. In case of contingencies or unexpected outages during the restoration process, RDSS can quickly update the restoration plan and adapt to changing system conditions. RDSS is an important step toward a self-healing power grid and its implementation will reduce the recovery time while maintaining system security.
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Date Issued: 2017
Identifier: CFE0007284, ucf:52169
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0007284

Title: DESIGN OF LOW-CAPACITANCE AND HIGH-SPEED ELECTROSTATIC DISCHARGE (ESD) DEVICES FOR LOW-VOLTAGE PROTECTION APPLICATIONS.
Creator: Li, You, Liou, Juin J., University of Central Florida
Abstract / Description: Electrostatic discharge (ESD) is defined as the transfer of charge between bodies at different potentials. The electrostatic discharge induced integrated circuit damages occur throughout the whole life of a product from the manufacturing, testing, shipping, handing, to end user operating stages. This is particularly true as microelectronics technology continues shrink to nano-metric dimensions. The ESD related failures is a major IC reliability concern and results in a loss of millions...
Show moreElectrostatic discharge (ESD) is defined as the transfer of charge between bodies at different potentials. The electrostatic discharge induced integrated circuit damages occur throughout the whole life of a product from the manufacturing, testing, shipping, handing, to end user operating stages. This is particularly true as microelectronics technology continues shrink to nano-metric dimensions. The ESD related failures is a major IC reliability concern and results in a loss of millions dollars to the semiconductor industry each year. Several ESD stress models and test methods have been developed to reproduce the real world ESD discharge events and quantify the sensitivity of ESD protection structures. The basic ESD models are: Human body model (HBM), Machine model (MM), and Charged device model (CDM). To avoid or reduce the IC failure due to ESD, the on-chip ESD protection structures and schemes have been implemented to discharge ESD current and clamp overstress voltage under different ESD stress events. Because of its simple structure and good performance, the junction diode is widely used in on-chip ESD protection applications. This is particularly true for ESD protection of low-voltage ICs where a relatively low trigger voltage for the ESD protection device is required. However, when the diode operates under the ESD stress, its current density and temperature are far beyond the normal conditions and the device is in danger of being damaged. For the design of effective ESD protection solution, the ESD robustness and low parasitic capacitance are two major concerns. The ESD robustness is usually defined after the failure current It2 and on-state resistance Ron. The transmission line pulsing (TLP) measurement is a very effective tool for evaluating the ESD robustness of a circuit or single element. This is particularly helpful in characterizing the effect of HBM stress where the ESD-induced damages are more likely due to thermal failures. Two types of diodes with different anode/cathode isolation technologies will be investigated for their ESD performance: one with a LOCOS (Local Oxidation of Silicon) oxide isolation called the LOCOS-bound diode, the other with a polysilicon gate isolation called the polysilicon-bound diode. We first examine the ESD performance of the LOCOS-bound diode. The effects of different diode geometries, metal connection patterns, dimensions and junction configurations on the ESD robustness and parasitic capacitance are investigated experimentally. The devices considered are N+/P-well junction LOCOS-bound diodes having different device widths, lengths and finger numbers, but the approach applies generally to the P+/N-well junction diode as well. The results provide useful insights into optimizing the diode for robust HBM ESD protection applications. Then, the current carrying and voltage clamping capabilities of LOCOS- and polysilicon-bound diodes are compared and investigated based on both TCAD simulation and experimental results. Comparison of these capabilities leads to the conclusion that the polysilicon-bound diode is more suited for ESD protection applications due to its higher performance. The effects of polysilicon-bound diodeÃ‚Â's design parameters, including the device width, anode/cathode length, finger number, poly-gate length, terminal connection and metal topology, on the ESD robustness are studied. Two figures of merits, FOM_It2 and FOM_Ron, are developed to better assess the effects of different parameters on polysilicon-bound diodeÃ‚Â's overall ESD performance. As latest generation package styles such as mBGAs, SOTs, SC70s, and CSPs are going to the millimeter-range dimensions, they are often effectively too small for people to handle with fingers. The recent industry data indicates the charged device model (CDM) ESD event becomes increasingly important in todayÃ‚Â's manufacturing environment and packaging technology. This event generates highly destructive pulses with a very short rise time and very small duration. TLP has been modified to probe CDM ESD protection effectiveness. The pulse width was reduced to the range of 1-10 ns to mimic the very fast transient of the CDM pulses. Such a very fast TLP (VFTLP) testing has been used frequently for CDM ESD characterization. The overshoot voltage and turn-on time are two key considerations for designing the CDM ESD protection devices. A relatively high overshoot voltage can cause failure of the protection devices as well as the protected devices, and a relatively long turn-on time may not switch on the protection device fast enough to effectively protect the core circuit against the CDM stress. The overshoot voltage and turn-on time of an ESD protection device can be observed and extracted from the voltage versus time waveforms measured from the VFTLP testing. Transient behaviors of polysilicon-bound diodes subject to pulses generated by the VFTLP tester are characterized for fast ESD events such as the charged device model. The effects of changing devicesÃ‚Â' dimension parameters on the transient behaviors and on the overshoot voltage and turn-on time are studied. The correlation between the diode failure and poly-gate configuration under the VFTLP stress is also investigated. Silicon-controlled rectifier (SCR) is another widely used ESD device for protecting the I/O pins and power supply rails of integrated circuits. Multiple fingers are often needed to achieve optimal ESD protection performance, but the uniformity of finger triggering and current flow is always a concern for multi-finger SCR devices operating under the post-snapback region. Without a proper understanding of the finger turn-on mechanism, design and realization of robust SCRs for ESD protection applications are not possible. Two two-finger SCRs with different combinations of anode/cathode regions are considered, and their finger turn-on uniformities are analyzed based on the I-V characteristics obtained from the transmission line pulsing (TLP) tester. The dV/dt effect of pulses with different rise times on the finger turn-on behavior of the SCRs are also investigated experimentally. In this work, unless noted otherwise, all the measurements are conducted using the Barth 4002 transmission line pulsing (TLP) and Barth 4012 very-fast transmission line pulsing (VFTLP) testers.
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Date Issued: 2010
Identifier: CFE0003440, ucf:48401
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0003440

Title: Design of Novel Devices and Circuits for Electrostatic Discharge Protection Applications in Advanced Semiconductor Technologies.
Creator: Wang, Zhixin, Liou, Juin, Gong, Xun, Yuan, Jiann-Shiun, Jin, Yier, Vinson, James, University of Central Florida
Abstract / Description: Electrostatic Discharge (ESD), as a subset of Electrical Overstress (EOS), was reported to be in charge of more than 35% of failure in integrated circuits (ICs). Especially in the manufacturing process, the silicon wafer turns out to be a functional ICs after numerous physical, chemical and mechanical processes, each of which expose the sensitive and fragile ICs to ESD environment. In normal end-user applications, ESD from human and machine handling, surge and spike signals in the power...
Show moreElectrostatic Discharge (ESD), as a subset of Electrical Overstress (EOS), was reported to be in charge of more than 35% of failure in integrated circuits (ICs). Especially in the manufacturing process, the silicon wafer turns out to be a functional ICs after numerous physical, chemical and mechanical processes, each of which expose the sensitive and fragile ICs to ESD environment. In normal end-user applications, ESD from human and machine handling, surge and spike signals in the power supply, and wrong supplying signals, will probably cause severe damage to the ICs and even the whole systems. Generally, ESD protections are evaluated after wafer and even system fabrication, increasing the development period and cost if the protections cannot meet customer's requirements. Therefore, it is important to design and customize robust and area-efficient ESD protections for the ICs at the early development stage. As the technologies generally scaling down, however, ESD protection clamps remain comparable area consumption in the recent years because they provide the discharging path for the ESD energy which rarely scales down. Diode is the most simple and effective device for ESD protection in ICs, but the usage is significantly limited by its low turn-on voltage. MOS devices can be triggered by a dynamic-triggered RC circuit for IOs operating at low voltage, while the one triggered by a static-triggered network, e.g., zener-resistor circuit or grounded-gate configuration, provides a high trigger voltage for high-voltage applications. However, the relatively low current discharging capability makes MOS devices as the secondary choice. Silicon-controlled rectifier (SCR) has become famous due to its high robustness and area efficiency, compared to diode and MOS. In this dissertation, a comprehensive design methodology for SCR based on simulation and measurement are presented for different advanced commercial technologies. Furthermore, an ESD clamp is designed and verified for the first time for the emerging GaN technology.For the SCR, no matter what modification is going to be made, the first concern when drawing the layout is to determine the layout geometrical style, finger width and finger number. This problem for diode and MOS device were studied in detail, so the same method was usually used in SCR. The research in this dissertation provides a closer look into the metal layout effect to the SCR, finding out the optimized robustness and minimized side-effect can be obtained by using specific layout geometry. Another concern about SCR is the relatively low turn-on speed when the IOs under protection is stressed by ESD pulses having very fast rising time, e.g., CDM and IEC 61000-4-2 pulses. On this occasion a large overshoot voltage is generated and cause damage to internal circuit component like gate oxides of MOS devices. The key determination of turn-on speed of SCR is physically investigated, followed by a novel design on SCR by directly connecting the Anode Gate and Cathode Gate to form internal trigger (DCSCR), with improved performance verified experimentally in this dissertation. The overshoot voltage and trigger voltage of the DCSCR will be significantly reduced, in return a better protection for internal circuit component is offered without scarifying neither area or robustness. Even though two SCR's with single direction of ESD current path can be constructed in reverse parallel to form bidirectional protection to pins, stand-alone bidirectional SCR (BSCR) is always desirable for sake of smaller area. The inherent high trigger voltage of BSCR that only fit in high-voltage technologies is overcome by embedding a PMOS transistor as trigger element, making it highly suitable for low-voltage ESD protection applications. More than that, this modification simultaneously introduces benefits including high robustness and low overshoot voltage.For high voltage pins, however, it presents another story for ESD designs. The high operation voltages require that a high trigger voltage and high holding voltage, so as to reduce the false trigger and latch-up risk. For several capacitive pins, the displacement current induced by a large snapback will cause severe damage to internal circuits. A novel design on SCR is proposed to minimize the snapback with adjustable trigger and holding voltage. Thanks to the additional a PIN diode, the similar high robustness and stable thermal leakage performance to SCR is maintained. For academic purpose of ESD design, it is always difficult to obtain the complete process deck in TCAD simulation because those information are highly confidential to the companies. Another challenge of using TCAD is the difficulty of maintaining the accuracy of physics models and predicting the performance of the other structures. In this dissertation a TCAD-aid ESD design methodology is used to evaluate ESD performance before the silicon shuttle.GaN is a promising material for high-voltage high-power RF application compared to the GaAs. However, distinct from GaAs, the leaky problem of the schottky junction and the lack of choice of passive/active components in GaN technology limit the ESD protection design, which will be discussed in this dissertation. However, a promising ESD protection clamp is finally developed based on depletion-mode pHEMT with adjustable trigger voltage, reasonable leakage current and high robustness.
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Date Issued: 2015
Identifier: CFE0006060, ucf:50989
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0006060

Title: Signal processing with Fourier analysis, novel algorithms and applications.
Creator: Syed, Alam, Foroosh, Hassan, Sun, Qiyu, Bagci, Ulas, Rahnavard, Nazanin, Atia, George, Katsevich, Alexander, University of Central Florida
Abstract / Description: Fourier analysis is the study of the way general functions may be represented or approximatedby sums of simpler trigonometric functions, also analogously known as sinusoidal modeling. Theoriginal idea of Fourier had a profound impact on mathematical analysis, physics, and engineeringbecause it diagonalizes time-invariant convolution operators. In the past signal processing was atopic that stayed almost exclusively in electrical engineering, where only the experts could cancelnoise, compress...
Show moreFourier analysis is the study of the way general functions may be represented or approximatedby sums of simpler trigonometric functions, also analogously known as sinusoidal modeling. Theoriginal idea of Fourier had a profound impact on mathematical analysis, physics, and engineeringbecause it diagonalizes time-invariant convolution operators. In the past signal processing was atopic that stayed almost exclusively in electrical engineering, where only the experts could cancelnoise, compress and reconstruct signals. Nowadays it is almost ubiquitous, as everyone now dealswith modern digital signals.Medical imaging, wireless communications and power systems of the future will experience moredata processing conditions and wider range of applications requirements than the systems of today.Such systems will require more powerful, efficient and flexible signal processing algorithms thatare well designed to handle such needs. No matter how advanced our hardware technology becomeswe will still need intelligent and efficient algorithms to address the growing demands in signalprocessing. In this thesis, we investigate novel techniques to solve a suite of four fundamentalproblems in signal processing that have a wide range of applications. The relevant equations, literatureof signal processing applications, analysis and final numerical algorithms/methods to solvethem using Fourier analysis are discussed for different applications in the electrical engineering /computer science. The first four chapters cover the following topics of central importance in thefield of signal processing: Fast Phasor Estimation using Adaptive Signal Processing (Chapter 2) Frequency Estimation from Nonuniform Samples (Chapter 3) 2D Polar and 3D Spherical Polar Nonuniform Discrete Fourier Transform (Chapter 4)iv Robust 3D registration using Spherical Polar Discrete Fourier Transform and Spherical Harmonics(Chapter 5)Even though each of these four methods discussed may seem completely disparate, the underlyingmotivation for more efficient processing by exploiting the Fourier domain signal structureremains the same. The main contribution of this thesis is the innovation in the analysis, synthesis, discretization of certain well-known problems like phasor estimation, frequency estimation, computations of a particular non-uniform Fourier transform and signal registration on the transformed domain. We conduct propositions and evaluations of certain applications relevant algorithms suchas, frequency estimation algorithm using non-uniform sampling, polar and spherical polar Fourier transform. The techniques proposed are also useful in the field of computer vision and medical imaging. From a practical perspective, the proposed algorithms are shown to improve the existing solutions in the respective fields where they are applied/evaluated. The formulation and final proposition is shown to have a variety of benefits. Future work with potentials in medical imaging, directional wavelets, volume rendering, video/3D object classifications, high dimensional registration are also discussed in the final chapter. Finally, in the spirit of reproducible research, we release the implementation of these algorithms to the public using Github.
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Date Issued: 2017
Identifier: CFE0006803, ucf:51775
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0006803

Title: Integrated Microwave Resonator/Antenna Structures for Sensor and Filter Applications.
Creator: Cheng, Haitao, Gong, Xun, Wahid, Parveen, Wu, Thomas, Kapoor, Vikram, An, Linan, University of Central Florida
Abstract / Description: This dissertation presents design challenges and promising solutions for temperature and pressure sensors which are highly desirable for harsh-environment applications, such as turbine engines. To survive the harsh environment consisting of high temperatures above 1000oC, high pressures around 300 psi, and corrosive gases, the sensors are required to be robust both electrically and mechanically. In addition, wire connection of the sensors is a challenging packaging problem, which remains...
Show moreThis dissertation presents design challenges and promising solutions for temperature and pressure sensors which are highly desirable for harsh-environment applications, such as turbine engines. To survive the harsh environment consisting of high temperatures above 1000oC, high pressures around 300 psi, and corrosive gases, the sensors are required to be robust both electrically and mechanically. In addition, wire connection of the sensors is a challenging packaging problem, which remains unresolved as of today. In this dissertation, robust ceramic sensors are demonstrated for both high temperature and pressure measurements. Also, the wireless sensors are achieved based on microwave resonators.Two types of temperature sensors are realized using integrated resonator/antennas and reflective patches, respectively. Both types of the sensors utilize alumina substrate which has a temperature-dependent dielectric constant. The temperature in the harsh environment is wirelessly detected by measuring the resonant frequency of the microwave resonator, which is dependent on the substrate permittivity. The integrated resonator/antenna structure minimizes the sensor dimension by adopting a seamless design between the resonator sensor and antenna. This integration technique can be also used to achieve an antenna array integrated with cavity filters. Alternatively, the aforementioned reflective patch sensor works simultaneously as a resonator sensor and a radiation element. Due to its planar structure, the reflective patch sensor is easy for design and fabrication. Both temperature sensors are measured above 1000oC.A pressure sensor is also demonstrated for high-temperature applications. Pressure is detected via the change in resonant frequency of an evanescent-mode resonator which corresponds to cavity deformation under gas pressure. A compact sensor size is achieved with a post loading the cavity resonator and a low-profile antenna connecting to the sensor. Polymer-Derived-Ceramic (PDC) is developed and used for the sensor fabrication. The pressure sensor is characterized under various pressures at high temperatures up to 800oC. In addition, to facilitate sensor characterizations, a robust antenna is developed in order to wirelessly interrogate the sensors. This specially-developed antenna is able to survive a record-setting temperature of 1300oC.
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Date Issued: 2014
Identifier: CFE0005473, ucf:50335
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0005473

Title: bio-inspired attitude control of micro air vehicles using rich information from airflow sensors.
Creator: Shen, He, Xu, Yunjun, Lin, Kuo-Chi, Kauffman, Jeffrey, An, Linan, University of Central Florida
Abstract / Description: Biological phenomena found in nature can be learned and customized to obtain innovative engineering solutions. In recent years, biologists found that birds and bats use their mechanoreceptors to sense the airflow information and use this information directly to achieve their agile flight performance. Inspired by this phenomenon, an attitude control system for micro air vehicles using rich amount of airflow sensor information is proposed, designed and tested. The dissertation discusses our...
Show moreBiological phenomena found in nature can be learned and customized to obtain innovative engineering solutions. In recent years, biologists found that birds and bats use their mechanoreceptors to sense the airflow information and use this information directly to achieve their agile flight performance. Inspired by this phenomenon, an attitude control system for micro air vehicles using rich amount of airflow sensor information is proposed, designed and tested. The dissertation discusses our research findings on this topic. First, we quantified the errors between the calculated and measured lift and moment profiles using a limited number of micro pressure sensors over a straight wing. Then, we designed a robust pitching controller using 20 micro pressure sensors and tested the closed-loop performance in a simulated environment. Additionally, a straight wing was designed for the pressure sensor based pitching control with twelve pressure sensors, which was then tested in our low-speed wind tunnel. The closed-loop pitching control system can track the commanded angle of attack with a rising time around two seconds and an overshoot around 10%. Third, we extended the idea to the three-axis attitude control scenarios, where both of the pressure and shear stress information are considered in the simulation. Finally, a fault tolerant controller with a guaranteed asymptotically stability is proposed to deal with sensor failures and calculation errors. The results show that the proposed fault tolerant controller is robust, adaptive, and can guarantee an asymptotically stable performance even in case that 50% of the airflow sensors fail in flight.
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Date Issued: 2014
Identifier: CFE0005711, ucf:50150
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0005711

Title: Batch and Online Implicit Weighted Gaussian Processes for Robust Novelty Detection.
Creator: Ramirez Padron, Ruben, Gonzalez, Avelino, Georgiopoulos, Michael, Stanley, Kenneth, Mederos, Boris, Wang, Chung-Ching, University of Central Florida
Abstract / Description: This dissertation aims mainly at obtaining robust variants of Gaussian processes (GPs) that do not require using non-Gaussian likelihoods to compensate for outliers in the training data. Bayesian kernel methods, and in particular GPs, have been used to solve a variety of machine learning problems, equating or exceeding the performance of other successful techniques. That is the case of a recently proposed approach to GP-based novelty detection that uses standard GPs (i.e. GPs employing...
Show moreThis dissertation aims mainly at obtaining robust variants of Gaussian processes (GPs) that do not require using non-Gaussian likelihoods to compensate for outliers in the training data. Bayesian kernel methods, and in particular GPs, have been used to solve a variety of machine learning problems, equating or exceeding the performance of other successful techniques. That is the case of a recently proposed approach to GP-based novelty detection that uses standard GPs (i.e. GPs employing Gaussian likelihoods). However, standard GPs are sensitive to outliers in training data, and this limitation carries over to GP-based novelty detection. This limitation has been typically addressed by using robust non-Gaussian likelihoods. However, non-Gaussian likelihoods lead to analytically intractable inferences, which require using approximation techniques that are typically complex and computationally expensive. Inspired by the use of weights in quasi-robust statistics, this work introduces a particular type of weight functions, called here data weighers, in order to obtain robust GPs that do not require approximation techniques and retain the simplicity of standard GPs. This work proposes implicit weighted variants of batch GP, online GP, and sparse online GP (SOGP) that employ weighted Gaussian likelihoods. Mathematical expressions for calculating the posterior implicit weighted GPs are derived in this work. In our experiments, novelty detection based on our weighted batch GPs consistently and significantly outperformed standard batch GP-based novelty detection whenever data was contaminated with outliers. Additionally, our experiments show that novelty detection based on online GPs can perform similarly to batch GP-based novelty detection. Membership scores previously introduced by other authors are also compared in our experiments.
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Date Issued: 2015
Identifier: CFE0005869, ucf:50858
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0005869

Title: Developing a Group Decision Support System (GDSS) for decision making under uncertainty.
Creator: Mokhtari, Soroush, Abdel-Aty, Mohamed, Madani Larijani, Kaveh, Wang, Dingbao, Xanthopoulos, Petros, University of Central Florida
Abstract / Description: Multi-Criteria Decision Making (MCDM) problems are often associated with tradeoffs between performances of the available alternative solutions under decision making criteria. These problems become more complex when performances are associated with uncertainty. This study proposes a stochastic MCDM procedure that can handle uncertainty in MCDM problems. The proposed method coverts a stochastic MCDM problem into many deterministic ones through a Monte-Carlo (MC) selection. Each deterministic...
Show moreMulti-Criteria Decision Making (MCDM) problems are often associated with tradeoffs between performances of the available alternative solutions under decision making criteria. These problems become more complex when performances are associated with uncertainty. This study proposes a stochastic MCDM procedure that can handle uncertainty in MCDM problems. The proposed method coverts a stochastic MCDM problem into many deterministic ones through a Monte-Carlo (MC) selection. Each deterministic problem is then solved using a range of MCDM methods and the ranking order of the alternatives is established for each deterministic MCDM. The final ranking of the alternatives can be determined based on winning probabilities and ranking distribution of the alternatives. Ranking probability distributions can help the decision-maker understand the risk associated with the overall ranking of the options. Therefore, the final selection of the best alternative can be affected by the risk tolerance of the decision-makers. A Group Decision Support System (GDSS) is developed here with a user-friendly interface to facilitate the application of the proposed MC-MCDM approach in real-world multi-participant decision making for an average user. The GDSS uses a range of decision making methods to increase the robustness of the decision analysis outputs and to help understand the sensitivity of the results to level of cooperation among the decision-makers. The decision analysis methods included in the GDSS are: 1) conventional MCDM methods (Maximin, Lexicographic, TOPSIS, SAW and Dominance), appropriate when there is a high cooperation level among the decision-makers; 2) social choice rules or voting methods (Condorcet Choice, Borda scoring, Plurality, Anti-Plurality, Median Voting, Hare System of voting, Majoritarian Compromise ,and Condorcet Practical), appropriate for cases with medium cooperation level among the decision-makers; and 3) Fallback Bargaining methods (Unanimity, Q-Approval and Fallback Bargaining with Impasse), appropriate for cases with non-cooperative decision-makers. To underline the utility of the proposed method and the developed GDSS in providing valuable insights into real-world hydro-environmental group decision making, the GDSS is applied to a benchmark example, namely the California's Sacramento-San Joaquin Delta decision making problem. The implications of GDSS' outputs (winning probabilities and ranking distributions) are discussed. Findings are compared with those of previous studies, which used other methods to solve this problem, to highlight the sensitivity of the results to the choice of decision analysis methods and/or different cooperation levels among the decision-makers.
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Date Issued: 2013
Identifier: CFE0004723, ucf:49821
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0004723

Title: Weighted Low-Rank Approximation of Matrices:Some Analytical and Numerical Aspects.
Creator: Dutta, Aritra, Li, Xin, Sun, Qiyu, Mohapatra, Ram, Nashed, M, Shah, Mubarak, University of Central Florida
Abstract / Description: This dissertation addresses some analytical and numerical aspects of a problem of weighted low-rank approximation of matrices. We propose and solve two different versions of weighted low-rank approximation problems. We demonstrate, in addition, how these formulations can be efficiently used to solve some classic problems in computer vision. We also present the superior performance of our algorithms over the existing state-of-the-art unweighted and weighted low-rank approximation algorithms...
Show moreThis dissertation addresses some analytical and numerical aspects of a problem of weighted low-rank approximation of matrices. We propose and solve two different versions of weighted low-rank approximation problems. We demonstrate, in addition, how these formulations can be efficiently used to solve some classic problems in computer vision. We also present the superior performance of our algorithms over the existing state-of-the-art unweighted and weighted low-rank approximation algorithms.Classical principal component analysis (PCA) is constrained to have equal weighting on the elements of the matrix, which might lead to a degraded design in some problems. To address this fundamental flaw in PCA, Golub, Hoffman, and Stewart proposed and solved a problem of constrained low-rank approximation of matrices: For a given matrix $A = (A_1\;A_2)$, find a low rank matrix $X = (A_1\;X_2)$ such that ${\rm rank}(X)$ is less than $r$, a prescribed bound, and $\|A-X\|$ is small.~Motivated by the above formulation, we propose a weighted low-rank approximation problem that generalizes the constrained low-rank approximation problem of Golub, Hoffman and Stewart.~We study a general framework obtained by pointwise multiplication with the weight matrix and consider the following problem:~For a given matrix $A\in\mathbb{R}^{m\times n}$ solve:\begin{eqnarray*}\label{weighted problem}\min_{\substack{X}}\|\left(A-X\right)\odot W\|_F^2~{\rm subject~to~}{\rm rank}(X)\le r,\end{eqnarray*}where $\odot$ denotes the pointwise multiplication and $\|\cdot\|_F$ is the Frobenius norm of matrices.In the first part, we study a special version of the above general weighted low-rank approximation problem.~Instead of using pointwise multiplication with the weight matrix, we use the regular matrix multiplication and replace the rank constraint by its convex surrogate, the nuclear norm, and consider the following problem:\begin{eqnarray*}\label{weighted problem 1}\hat{X} (&)=(&) \arg \min_X \{\frac{1}{2}\|(A-X)W\|_F^2 +\tau\|X\|_\ast\},\end{eqnarray*}where $\|\cdot\|_*$ denotes the nuclear norm of $X$.~Considering its resemblance with the classic singular value thresholding problem we call it the weighted singular value thresholding~(WSVT)~problem.~As expected,~the WSVT problem has no closed form analytical solution in general,~and a numerical procedure is needed to solve it.~We introduce auxiliary variables and apply simple and fast alternating direction method to solve WSVT numerically.~Moreover, we present a convergence analysis of the algorithm and propose a mechanism for estimating the weight from the data.~We demonstrate the performance of WSVT on two computer vision applications:~background estimation from video sequences~and facial shadow removal.~In both cases,~WSVT shows superior performance to all other models traditionally used. In the second part, we study the general framework of the proposed problem.~For the special case of weight, we study the limiting behavior of the solution to our problem,~both analytically and numerically.~In the limiting case of weights,~as $(W_1)_{ij}\to\infty, W_2=\mathbbm{1}$, a matrix of 1,~we show the solutions to our weighted problem converge, and the limit is the solution to the constrained low-rank approximation problem of Golub et. al. Additionally, by asymptotic analysis of the solution to our problem,~we propose a rate of convergence.~By doing this, we make explicit connections between a vast genre of weighted and unweighted low-rank approximation problems.~In addition to these, we devise a novel and efficient numerical algorithm based on the alternating direction method for the special case of weight and present a detailed convergence analysis.~Our approach improves substantially over the existing weighted low-rank approximation algorithms proposed in the literature.~Finally, we explore the use of our algorithm to real-world problems in a variety of domains, such as computer vision and machine learning. Finally, for a special family of weights, we demonstrate an interesting property of the solution to the general weighted low-rank approximation problem. Additionally, we devise two accelerated algorithms by using this property and present their effectiveness compared to the algorithm proposed in Chapter 4.
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Date Issued: 2016
Identifier: CFE0006833, ucf:51789
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0006833

Title: Quantifying Trust and Reputation for Defense against Adversaries in Multi-Channel Dynamic Spectrum Access Networks.
Creator: Bhattacharjee, Shameek, Chatterjee, Mainak, Guha, Ratan, Zou, Changchun, Turgut, Damla, Catbas, Necati, University of Central Florida
Abstract / Description: Dynamic spectrum access enabled by cognitive radio networks are envisioned to drivethe next generation wireless networks that can increase spectrum utility by opportunisticallyaccessing unused spectrum. Due to the policy constraint that there could be no interferenceto the primary (licensed) users, secondary cognitive radios have to continuously sense forprimary transmissions. Typically, sensing reports from multiple cognitive radios are fusedas stand-alone observations are prone to errors...
Show moreDynamic spectrum access enabled by cognitive radio networks are envisioned to drivethe next generation wireless networks that can increase spectrum utility by opportunisticallyaccessing unused spectrum. Due to the policy constraint that there could be no interferenceto the primary (licensed) users, secondary cognitive radios have to continuously sense forprimary transmissions. Typically, sensing reports from multiple cognitive radios are fusedas stand-alone observations are prone to errors due to wireless channel characteristics. Suchdependence on cooperative spectrum sensing is vulnerable to attacks such as SecondarySpectrum Data Falsification (SSDF) attacks when multiple malicious or selfish radios falsifythe spectrum reports. Hence, there is a need to quantify the trustworthiness of radios thatshare spectrum sensing reports and devise malicious node identification and robust fusionschemes that would lead to correct inference about spectrum usage.In this work, we propose an anomaly monitoring technique that can effectively cap-ture anomalies in the spectrum sensing reports shared by individual cognitive radios duringcooperative spectrum sensing in a multi-channel distributed network. Such anomalies areused as evidence to compute the trustworthiness of a radio by its neighbours. The proposedanomaly monitoring technique works for any density of malicious nodes and for any physicalenvironment. We propose an optimistic trust heuristic for a system with a normal risk attitude and show that it can be approximated as a beta distribution. For a more conservativesystem, we propose a multinomial Dirichlet distribution based conservative trust framework,where Josang's Belief model is used to resolve any uncertainty in information that mightarise during anomaly monitoring. Using a machine learning approach, we identify maliciousnodes with a high degree of certainty regardless of their aggressiveness and variations intro-duced by the pathloss environment. We also propose extensions to the anomaly monitoringtechnique that facilitate learning about strategies employed by malicious nodes and alsoutilize the misleading information they provide. We also devise strategies to defend against a collaborative SSDF attack that islaunched by a coalition of selfish nodes. Since, defense against such collaborative attacks isdifficult with popularly used voting based inference models or node centric isolation techniques, we propose a channel centric Bayesian inference approach that indicates how much the collective decision on a channels occupancy inference can be trusted. Based on the measured observations over time, we estimate the parameters of the hypothesis of anomalous andnon-anomalous events using a multinomial Bayesian based inference. We quantitatively define the trustworthiness of a channel inference as the difference between the posterior beliefsassociated with anomalous and non-anomalous events. The posterior beliefs are updated based on a weighted average of the prior information on the belief itself and the recently observed data.Subsequently, we propose robust fusion models which utilize the trusts of the nodes to improve the accuracy of the cooperative spectrum sensing decisions. In particular, we propose three fusion models: (i) optimistic trust based fusion, (ii) conservative trust based fusion, and (iii) inversion based fusion. The former two approaches exclude untrustworthy sensing reports for fusion, while the last approach utilizes misleading information. Allschemes are analyzed under various attack strategies. We propose an asymmetric weightedmoving average based trust management scheme that quickly identifies on-off SSDF attacks and prevents quick trust redemption when such nodes revert back to temporal honest behavior. We also provide insights on what attack strategies are more effective from the adversaries' perspective.Through extensive simulation experiments we show that the trust models are effective in identifying malicious nodes with a high degree of certainty under variety of network and radio conditions. We show high true negative detection rates even when multiple malicious nodes launch collaborative attacks which is an improvement over existing voting based exclusion and entropy divergence techniques. We also show that we are able to improve the accuracy of fusion decisions compared to other popular fusion techniques. Trust based fusion schemes show worst case decision error rates of 5% while inversion based fusion show 4% as opposed majority voting schemes that have 18% error rate. We also show that the proposed channel centric Bayesian inference based trust model is able to distinguish between attacked and non-attacked channels for both static and dynamic collaborative attacks. We are also able to show that attacked channels have significantly lower trust values than channels that are not(-) a metric that can be used by nodes to rank the quality of inference on channels.
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Date Issued: 2015
Identifier: CFE0005764, ucf:50081
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0005764

Title: OPTIMAL DETOUR PLANNING AROUND BLOCKED CONSTRUCTION ZONES.
Creator: Jardaneh , Mutasem, Khalafallah, Ahmed, University of Central Florida
Abstract / Description: Construction zones are traffic way areas where construction, maintenance or utility work is identified by warning signs, signals and indicators, including those on transport devices that mark the beginning and end of construction zones. Construction zones are among the most dangerous work areas, with workers facing workplace safety challenges that often lead to catastrophic injuries or fatalities. In addition, daily commuters are also impacted by construction zone detours that affect their...
Show moreConstruction zones are traffic way areas where construction, maintenance or utility work is identified by warning signs, signals and indicators, including those on transport devices that mark the beginning and end of construction zones. Construction zones are among the most dangerous work areas, with workers facing workplace safety challenges that often lead to catastrophic injuries or fatalities. In addition, daily commuters are also impacted by construction zone detours that affect their safety and daily commute time. These problems represent major challenges to construction planners as they are required to plan vehicle routes around construction zones in such a way that maximizes the safety of construction workers and reduces the impact on daily commuters. This research aims at developing a framework for optimizing the planning of construction detours. The main objectives of the research are to first identify all the decision variables that affect the planning of construction detours and secondly, implement a model based on shortest path formulation to identify the optimal alternatives for construction detours. The ultimate goal of this research is to offer construction planners with the essential guidelines to improve construction safety and reduce construction zone hazards as well as a robust tool for selecting and optimizing construction zone detours.
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Date Issued: 2011
Identifier: CFE0003586, ucf:48900
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0003586

Robust (3)	+ -
Robustness (3)	+ -
robust control (3)	+ -
Robust Control (2)	+ -
Adaptive (1)	+ -

Adaptive Control (1)	+ -
Aerodynamics (1)	+ -
Alternating Direction Method (1)	+ -
Ant Colony Optimization (1)	+ -
Background Estimation (1)	+ -
Bayesian and Machine Learning based Trust Models (1)	+ -
Bayesian machine learning (1)	+ -
Boundedly Rational (1)	+ -
Cavity resonator (1)	+ -
Cognitive Radio Networks (1)	+ -
Construction Detour Safety (1)	+ -
Construction detours (1)	+ -
Construction zone hazards (1)	+ -
Construction zones (1)	+ -
Control (1)	+ -
Cost Associated with Construction Detours (1)	+ -
Decision Support System (1)	+ -
Detours (1)	+ -
Diodes (1)	+ -
Dynamic Spectrum Access Networks (1)	+ -
ESD (1)	+ -
Edge Termination (1)	+ -
Electricity Generation (1)	+ -
Electrostatic discharge (ESD) (1)	+ -
FRD (1)	+ -

University of Central Florida (20)	+ -
Xu, Yunjun (5)	+ -
An, Linan (3)	+ -
Lin, Kuo-Chi (3)	+ -
Zheng, Qipeng (3)	+ -

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