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Title: A COMPARISON AND EVALUATIONOFCOMMON PID TUNING METHODS.
Creator: Youney, Justin, Haralambous, Michael, University of Central Florida
Abstract / Description: The motivation behind this thesis is to consolidate and evaluate the most common Proportional Integral Derivative (PID) controller tuning techniques used in industry. These are the tuning techniques used when the plant transfer function is not known. Many of these systems are poorly tuned because such consolidated information is not easily found in one single source such as this thesis. Once one of the tuning methods are applied almost always there will be further fine tuning needed to bring...
Show moreThe motivation behind this thesis is to consolidate and evaluate the most common Proportional Integral Derivative (PID) controller tuning techniques used in industry. These are the tuning techniques used when the plant transfer function is not known. Many of these systems are poorly tuned because such consolidated information is not easily found in one single source such as this thesis. Once one of the tuning methods are applied almost always there will be further fine tuning needed to bring the system into the required design criteria. The purpose here is to find out which tuning technique will yield the lowest percent overshoot and the shortest settling time for all situations. This will give the engineer a good starting point; to minimally further adjust parameters to achieve the desired design criteria. There will also be discussion on the various algorithms used in industry. Four tuning methods will be evaluated based on their ability to control different style plants. The comparison criteria will be percent overshoot and settling time for an applied step input. The tuning methods chosen were the Ziegler-Nichols Open Loop method, the CHR method for 0% overshoot, the Ziegler-Nichols Closed Loop method, and the Rule of Thumb method. It is shown that for a second order plant with a lag and pure integration in its transfer function, the Open Loop method yielded the lowest results in terms of percent overshoot, yet the Closed Loop method had the shortest settling time. For systems of higher order than two it was shown that the CHR method gave the best performance however as the order increased the Closed Loop method gave a shorter settling time. For systems of higher order with varying lags in series the CHR method gave the best results. The Rule of thumb method usually gave similar results to that of the Closed Loop method; however for higher order systems the Rule of Thumb method gave less percent overshoot but with a longer settling time than the Closed Loop method. Since these tuning methods are used when the plant transfer function is not known, and none of the rules were found to give consistently the lowest percent overshoot, and settling time for all plants tested, there can not be a recommendation as to which method an engineer should choose to use. If the plant transfer function is known or can be reasonably modeled then the following recommendations can be followed. When tuning systems with pure integrations in their transfer function the Open Loop or Closed Loop method be used. When tuning systems of order higher than two the CHR or Closed Loop method should be used, however with high order systems with varying lags the CHR method should be used. It is the responsibility of the engineer to know how and when to implement each of the tuning rules properly.
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Date Issued: 2007
Identifier: CFE0001716, ucf:47301
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0001716

Title: STABILIZATION AND TRACKING OF THE VAN DER POL OSCILLATOR.
Creator: Zhao, Xin, Haralambous, Michael, University of Central Florida
Abstract / Description: In this thesis, the stabilization and tracking problem of the Van der Pol oscillator is studied by using advanced control techniques. First, the linear state feedback and linear adaptive state feedback controllers for the stabilization problem are designed. Then, non-linear state feedback and output feedback controllers are proposed for the tracking problem with known parameters. Finally, a dynamic output feedback controller based on adaptive backstepping technique is introduced for the...
Show moreIn this thesis, the stabilization and tracking problem of the Van der Pol oscillator is studied by using advanced control techniques. First, the linear state feedback and linear adaptive state feedback controllers for the stabilization problem are designed. Then, non-linear state feedback and output feedback controllers are proposed for the tracking problem with known parameters. Finally, a dynamic output feedback controller based on adaptive backstepping technique is introduced for the tracking problem when all parameters of the Van der Pol system are unknown.
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Date Issued: 2005
Identifier: CFE0000569, ucf:46444
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0000569

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: Smart Grasping using Laser and Tactile Array Sensors for UCF-MANUS- An Intelligent Assistive Robotic Manipulator.
Creator: Prakash, Kiran, Behal, Aman, Boloni, Ladislau, Haralambous, Michael, University of Central Florida
Abstract / Description: This thesis presents three improvements in the UCF MANUS Assistive Robotic Manipulator's grasping abilities. Firstly, the robot can now grasp objects that are deformable, heavy and have uneven contact surfaces without undergoing slippage during robotic operations, e.g. paper cup, filled water bottle. This is achieved by installing a high precision non-contacting Laser sensor1 that runs with an algorithm that processes raw-input data from the sensor, registers smallest variation in the...
Show moreThis thesis presents three improvements in the UCF MANUS Assistive Robotic Manipulator's grasping abilities. Firstly, the robot can now grasp objects that are deformable, heavy and have uneven contact surfaces without undergoing slippage during robotic operations, e.g. paper cup, filled water bottle. This is achieved by installing a high precision non-contacting Laser sensor1 that runs with an algorithm that processes raw-input data from the sensor, registers smallest variation in the relative position of the object with respect to the gripper. Secondly, the robot can grasp objects that are as light and small as single cereal grain without deforming it. To achieve this a MEMS Barometer based tactile sensor array device that can measure force that are as small as 1 gram equivalent is embedded into the gripper to enhance pressure sensing capabilities. Thirdly, the robot gripper gloves are designed aesthetically and conveniently to accommodate existing and newly added sensors using a 3D printing technology that uses light weight ABS plastic as a fabrication material. The newly designed system was experimented and found that a high degree of adaptability for different kinds of objects can be attained with a better performance than the previous system.
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Date Issued: 2016
Identifier: CFE0006164, ucf:51119
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0006164

Title: Characterization of a Spiking Neuron Model via a Linear Approach.
Creator: Jabalameli, Amirhossein, Behal, Aman, Hickman, James, Haralambous, Michael, University of Central Florida
Abstract / Description: In the past decade, characterizing spiking neuron models has been extensively researched as anessential issue in computational neuroscience. In this thesis, we examine the estimation problemof two different neuron models. In Chapter 2, We propose a modified Izhikevich model withan adaptive threshold. In our two-stage estimation approach, a linear least squares method anda linear model of the threshold are derived to predict the location of neuronal spikes. However,desired results are not...
Show moreIn the past decade, characterizing spiking neuron models has been extensively researched as anessential issue in computational neuroscience. In this thesis, we examine the estimation problemof two different neuron models. In Chapter 2, We propose a modified Izhikevich model withan adaptive threshold. In our two-stage estimation approach, a linear least squares method anda linear model of the threshold are derived to predict the location of neuronal spikes. However,desired results are not obtained and the predicted model is unsuccessful in duplicating the spikelocations. Chapter 3 is focused on the parameter estimation problem of a multi-timescale adaptivethreshold (MAT) neuronal model. Using the dynamics of a non-resetting leaky integrator equippedwith an adaptive threshold, a constrained iterative linear least squares method is implemented tofit the model to the reference data. Through manipulation of the system dynamics, the thresholdvoltage can be obtained as a realizable model that is linear in the unknown parameters. This linearlyparametrized realizable model is then utilized inside a prediction error based framework to identifythe threshold parameters with the purpose of predicting single neuron precise firing times. Thisestimation scheme is evaluated using both synthetic data obtained from an exact model as well asthe experimental data obtained from in vitro rat somatosensory cortical neurons. Results show theability of this approach to fit the MAT model to different types of reference data.
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Date Issued: 2015
Identifier: CFE0005958, ucf:50803
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0005958

Title: Modeling and Compensation for Efficient Human Robot Interaction.
Creator: Paperno, Nicholas, Behal, Aman, Haralambous, Michael, Boloni, Ladislau, University of Central Florida
Abstract / Description: The purpose of this research is to first: identify the important human factors to performance when operating an assistive robotic manipulator, second: develop a predictive model that will be able to determine a user's performance based on their known human factors, and third: develop compensators based on the determined important human factors that will help improve user performance and satisfaction. An extensive literature search led to the selection of ten potential human factors to be...
Show moreThe purpose of this research is to first: identify the important human factors to performance when operating an assistive robotic manipulator, second: develop a predictive model that will be able to determine a user's performance based on their known human factors, and third: develop compensators based on the determined important human factors that will help improve user performance and satisfaction. An extensive literature search led to the selection of ten potential human factors to be analyzed including reaction time, spatial abilities (orientation and visualization), working memory, visual perception, dexterity (gross and fine), depth perception, and visual acuity of both eyes (classified as strongest and weakest). 93 participants were recruited to perform six different pick-and-place and retrieval tasks using an assistive robotic device. During this time, a participants Time-on-Task, Number-of-Moves, and Number-of-Moves per minute were recorded. From this it was determined that all the human factors except visual perception were considered important to at least one aspect of a user's performance. Predictive models were then developed using random forest, linear models, and polynomial models. To compensate for deficiencies in certain human factors, the GUI was redesigned based on a heuristic analysis and user feedback. Multimodal feedback as well as adjustments in the sensitivity of the input device and reduction in the robot's speed of movement were also implemented. From a user study using 15 participants it was found that certain compensation did improve satisfaction of the users, particularly the multimodal feedback and sensitivity adjustment. The reduction of speed was met with mixed reviews from the participants.
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Date Issued: 2016
Identifier: CFE0006370, ucf:51504
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0006370

Title: A New Path Planning Guidance Law For Improved Impact Time Control of Missiles and Precision Munitions.
Creator: Snyder, Mark, Qu, Zhihua, Haralambous, Michael, Xu, Yunjun, University of Central Florida
Abstract / Description: A new missile guidance law is proposed for the control of impact time which provides an improved time-to-go calculation by removing error due to trajectory curvature and also provides a family of trajectories for trajectory planning purposes. Unlike conventional optimal guidance laws, the proposed law is non explicit in time-to-go and the linearization of the engagement kinematics in order to gain a closed form solution is not necessary.
Date Issued: 2016
Identifier: CFE0006398, ucf:51506
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0006398

Title: A Triangulation Based Coverage Path Planning For a Mobile Robot With Circular Sensing Range.
Creator: An, Vatana, Qu, Zhihua, Haralambous, Michael, Mikhael, Wasfy, University of Central Florida
Abstract / Description: In this dissertation, two coverage path planning (CPP) approaches for a nonholonomic mobile robot are proposed. The first approach is the Local Coverage Path Planning (LCPP) approach which is designed for all sensing ranges. The second approach is the Global Coverage Path Planning (GCPP) approach which is designed for sufficient sensing range that can observe all points of interests in the target region (TR). The LCPP approach constructs CP after finding observer points for all local regions...
Show moreIn this dissertation, two coverage path planning (CPP) approaches for a nonholonomic mobile robot are proposed. The first approach is the Local Coverage Path Planning (LCPP) approach which is designed for all sensing ranges. The second approach is the Global Coverage Path Planning (GCPP) approach which is designed for sufficient sensing range that can observe all points of interests in the target region (TR). The LCPP approach constructs CP after finding observer points for all local regions in the TR. The GCPP approach computes observer points after CP construction. Beginning with the sample TR, the LCPP approach requires 8 algorithms to find a smooth CP and sufficient number of observers for complete coverage. The Global Coverage Path Planning approach requires 17 algorithms to find the smooth CP with sufficient number of observers for completed coverage. The worst case running time for both approaches are quadratic which is consider to be very fast as compared to previous works reported in the literature. The main technical contributions of both approaches are to provide a holistic solution that segments any TR, uses triangulation to determine the line of sights and observation points, and then compute the smooth and collision-free CP. Both approaches provide localization, speed control, curvature control, CP length control, and smooth CP control. The first approach has applications in automate vacuum cleaning, search and rescue mission, spray painting, and etc. The second approach is best used in military and space applications as it requires infinite sensing range which only resource rich organizations can afford. At the very least, the second approach provides simulation opportunity and upper bound cost estimate for CPP. Both approaches will lead to a search strategy that provides the shortest CP with the minimum number of observer and with the shortest running time for any sensing range.
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Date Issued: 2017
Identifier: CFE0006853, ucf:51745
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0006853

Title: Learning to Grasp Unknown Objects using Weighted Random Forest Algorithm from Selective Image and Point Cloud Feature.
Creator: Iqbal, Md Shahriar, Behal, Aman, Boloni, Ladislau, Haralambous, Michael, University of Central Florida
Abstract / Description: This method demonstrates an approach to determine the best grasping location on an unknown object using Weighted Random Forest Algorithm. It used RGB-D value of an object as input to find a suitable rectangular grasping region as the output. To accomplish this task, it uses a subspace of most important features from a very high dimensional extensive feature space that contains both image and point cloud features. Usage of most important features in the grasping algorithm has enabled the...
Show moreThis method demonstrates an approach to determine the best grasping location on an unknown object using Weighted Random Forest Algorithm. It used RGB-D value of an object as input to find a suitable rectangular grasping region as the output. To accomplish this task, it uses a subspace of most important features from a very high dimensional extensive feature space that contains both image and point cloud features. Usage of most important features in the grasping algorithm has enabled the system to be computationally very fast while preserving maximum information gain. In this approach, the Random Forest operates using optimum parameters e.g. Number of Trees, Number of Features at each node, Information Gain Criteria etc. ensures optimization in learning, with highest possible accuracy in minimum time in an advanced practical setting. The Weighted Random Forest chosen over Support Vector Machine (SVM), Decision Tree and Adaboost for implementation of the grasping system outperforms the stated machine learning algorithms both in training and testing accuracy and other performance estimates. The Grasping System utilizing learning from a score function detects the rectangular grasping region after selecting the top rectangle that has the largest score. The system is implemented and tested in a Baxter Research Robot with Parallel Plate Gripper in action.
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Date Issued: 2014
Identifier: CFE0005509, ucf:50358
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0005509

Title: Online Path Planning and Control Solution for a Coordinated Attack of Multiple Unmanned Aerial Vehicles in a Dynamic Environment.
Creator: Vega-Nevarez, Juan, Qu, Zhihua, Haralambous, Michael, Xu, Yunjun, University of Central Florida
Abstract / Description: The role of the unmanned aerial vehicle (UAV) has significantly expanded in the military sector during the last decades mainly due to their cost effectiveness and their ability to eliminate the human life risk. Current UAV technology supports a variety of missions and extensive research and development is being performed to further expand its capabilities. One particular field of interest is the area of the low cost expendable UAV since its small price tag makes it an attractive solution for...
Show moreThe role of the unmanned aerial vehicle (UAV) has significantly expanded in the military sector during the last decades mainly due to their cost effectiveness and their ability to eliminate the human life risk. Current UAV technology supports a variety of missions and extensive research and development is being performed to further expand its capabilities. One particular field of interest is the area of the low cost expendable UAV since its small price tag makes it an attractive solution for target suppression. A swarm of these low cost UAVs can be utilized as guided munitions or kamikaze UAVs to attack multiple targets simultaneously. The focus of this thesis is the development of a cooperative online path planning algorithm that coordinates the trajectories of these UAVs to achieve a simultaneous arrival to their dynamic targets. A nonlinear autopilot design based on the dynamic inversion technique is also presented which stabilizes the dynamics of the UAV in its entire operating envelope. A nonlinear high fidelity six degrees of freedom model of a fixed wing aircraft was developed as well that acted as the main test platform to verify the performance of the presented algorithms
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Date Issued: 2012
Identifier: CFE0004613, ucf:49925
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0004613

Title: Modeling and Simulation of All-electric Aircraft Power Generation and Actuation.
Creator: Woodburn, David, Wu, Xinzhang, Batarseh, Issa, Georgiopoulos, Michael, Haralambous, Michael, Chow, Louis, University of Central Florida
Abstract / Description: Modern aircraft, military and commercial, rely extensively on hydraulic systems. However, there is great interest in the avionics community to replace hydraulic systems with electric systems. There are physical challenges to replacing hydraulic actuators with electromechanical actuators (EMAs), especially for flight control surface actuation. These include dynamic heat generation and power management.Simulation is seen as a powerful tool in making the transition to all-electric aircraft by...
Show moreModern aircraft, military and commercial, rely extensively on hydraulic systems. However, there is great interest in the avionics community to replace hydraulic systems with electric systems. There are physical challenges to replacing hydraulic actuators with electromechanical actuators (EMAs), especially for flight control surface actuation. These include dynamic heat generation and power management.Simulation is seen as a powerful tool in making the transition to all-electric aircraft by predicting the dynamic heat generated and the power flow in the EMA. Chapter 2 of this dissertation describes the nonlinear, lumped-element, integrated modeling of a permanent magnet (PM) motor used in an EMA. This model is capable of representing transient dynamics of an EMA, mechanically, electrically, and thermally.Inductance is a primary parameter that links the electrical and mechanical domains and, therefore, is of critical importance to the modeling of the whole EMA. In the dynamic mode of operation of an EMA, the inductances are quite nonlinear. Chapter 3 details the careful analysis of the inductances from finite element software and the mathematical modeling of these inductances for use in the overall EMA model.Chapter 4 covers the design and verification of a nonlinear, transient simulation model of a two-step synchronous generator with three-phase rectifiers. Simulation results are shown.
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Date Issued: 2013
Identifier: CFE0005074, ucf:49975
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0005074

Title: AUTONOMOUS ROBOTIC GRASPING IN UNSTRUCTURED ENVIRONMENTS.
Creator: Jabalameli, Amirhossein, Behal, Aman, Haralambous, Michael, Pourmohammadi Fallah, Yaser, Boloni, Ladislau, Xu, Yunjun, University of Central Florida
Abstract / Description: A crucial problem in robotics is interacting with known or novel objects in unstructured environments. While the convergence of a multitude of research advances is required to address this problem, our goal is to describe a framework that employs the robot's visual perception to identify and execute an appropriate grasp to pick and place novel objects. Analytical approaches explore for solutions through kinematic and dynamic formulations. On the other hand, data-driven methods retrieve grasps...
Show moreA crucial problem in robotics is interacting with known or novel objects in unstructured environments. While the convergence of a multitude of research advances is required to address this problem, our goal is to describe a framework that employs the robot's visual perception to identify and execute an appropriate grasp to pick and place novel objects. Analytical approaches explore for solutions through kinematic and dynamic formulations. On the other hand, data-driven methods retrieve grasps according to their prior knowledge of either the target object, human experience, or through information obtained from acquired data. In this dissertation, we propose a framework based on the supporting principle that potential contacting regions for a stable grasp can be foundby searching for (i) sharp discontinuities and (ii) regions of locally maximal principal curvature in the depth map. In addition to suggestions from empirical evidence, we discuss this principle by applying the concept of force-closure and wrench convexes. The key point is that no prior knowledge of objects is utilized in the grasp planning process; however, the obtained results show thatthe approach is capable to deal successfully with objects of different shapes and sizes. We believe that the proposed work is novel because the description of the visible portion of objects by theaforementioned edges appearing in the depth map facilitates the process of grasp set-point extraction in the same way as image processing methods with the focus on small-size 2D image areas rather than clustering and analyzing huge sets of 3D point-cloud coordinates. In fact, this approach dismisses reconstruction of objects. These features result in low computational costs and make it possible to run the proposed algorithm in real-time. Finally, the performance of the approach is successfully validated by applying it to the scenes with both single and multiple objects, in both simulation and real-world experiment setups.
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Date Issued: 2019
Identifier: CFE0007892, ucf:52757
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0007892

Title: Design and Implementation of PV-Firming and Optimization Algorithms For Three-Port Microinverters.
Creator: Alharbi, Mahmood, Batarseh, Issa, Haralambous, Michael, Mikhael, Wasfy, Yuan, Jiann-Shiun, Kutkut, Nasser, University of Central Florida
Abstract / Description: With the demand increase for electricity, the ever-increasing awareness of environmental issues, coupled with rolling blackouts, the role of renewable energy generation is increasing along with the thirst for electricity and awareness of environmental issues. This dissertation proposes the design and implementation of PV-firming and optimization algorithms for three-port microinverters.Novel strategies are proposed in Chapters 3 and 4 for harvesting stable solar power in spite of intermittent...
Show moreWith the demand increase for electricity, the ever-increasing awareness of environmental issues, coupled with rolling blackouts, the role of renewable energy generation is increasing along with the thirst for electricity and awareness of environmental issues. This dissertation proposes the design and implementation of PV-firming and optimization algorithms for three-port microinverters.Novel strategies are proposed in Chapters 3 and 4 for harvesting stable solar power in spite of intermittent solar irradiance. PV firming is implemented using a panel-level three-port grid-tied PV microinverter system instead of the traditional high-power energy storage and management system at the utility scale. The microinverter system consists of a flyback converter and an H-bridge inverter/rectifier, with a battery connected to the DC-link. The key to these strategies lies in using static and dynamic algorithms to generate a smooth PV reference power. The outcomes are applied to various control methods to charge/discharge the battery so that a stable power generation profile is obtained. In addition, frequency-based optimization for the inverter stage is presented.One of the design parameters of grid-tied single-phase H-bridge sinusoidal pulse-width modulation (SPWM) microinverters is switching frequency. The selection of the switching frequency is a tradeoff between improving the power quality by reducing the total harmonic distortion (THD), and improving the efficiency by reducing the switching loss. In Chapter 5, two algorithms are proposed for optimizing both the power quality and the efficiency of the microinverter. They do this by using a frequency tracking technique that requires no hardware modification. The first algorithm tracks the optimal switching frequency for maximum efficiency at a given THD value. The second maximizes the power quality of the H-bridge micro-inverter by tracking the switching frequency that corresponds to the minimum THD.Real-time PV intermittency and usable capacity data were evaluated and then further analyzed in MATLAB/SIMULINK to validate the PV firming control. The proposed PV firming and optimization algorithms were experimentally verified, and the results evaluated. Finally, Chapter 6 provides a summary of key conclusions and future work to optimize the presented topology and algorithms.
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Date Issued: 2018
Identifier: CFE0007305, ucf:52166
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0007305

Title: Nonlinear Control Synthesis for Facilitation of Human-Robot Interaction.
Creator: Ding, Zhangchi, Behal, Aman, Pourmohammadi Fallah, Yaser, Haralambous, Michael, Boloni, Ladislau, Xu, Yunjun, University of Central Florida
Abstract / Description: Human-robot interaction is an area of interest that is becoming increasingly important in robotics research. Nonlinear control design techniques allow researchers to guarantee stability, performance, as well as safety, especially in cases involving physical human-robot interaction (PHRI). In this dissertation, we will propose two different nonlinear controllers and detail the design of an assistive robotic system to facilitate human-robot interaction. In Chapter 2, to facilitate physical...
Show moreHuman-robot interaction is an area of interest that is becoming increasingly important in robotics research. Nonlinear control design techniques allow researchers to guarantee stability, performance, as well as safety, especially in cases involving physical human-robot interaction (PHRI). In this dissertation, we will propose two different nonlinear controllers and detail the design of an assistive robotic system to facilitate human-robot interaction. In Chapter 2, to facilitate physical human-robot interaction, the problem of making a safe compliant contact between a human and an assistive robot is considered. Users with disabilities have a need to utilize their assistive robots for physical interaction during activities such as hair-grooming, scratching, face-sponging, etc. Specifically, we propose a hybrid force/velocity/attitude control for our physical human-robot interaction system which is based on measurements from a force/torque sensor mounted on the robot wrist. While automatically aligning the end-effector surface with the unknown environmental (human) surface, a desired commanded force is applied in the normal direction while following desired velocity commands in the tangential directions. A Lyapunov based stability analysis is provided to prove both convergence as well as passivity of the interaction to ensure both performance and safety. Simulation as well as experimental results verify the performance and robustness of the proposed hybrid force/velocity/attitude controller in the presence of dynamic uncertainties as well as safety compliance of human-robot interactions for a redundant robot manipulator.Chapter 3 presents the design, analysis, and experimental implementation of an adaptive control enabled intelligent algorithm to facilitate 1-click grasping of novel objects by a robotic gripper since one of the most common types of tasks for an assistive robot is pick and place/object retrieval tasks. But there are a variety of objects in our daily life all of which need different optimal force to grasp them. This algorithm facilitates automated grasping force adjustment. The use of object-geometry free modeling coupled with utilization of interaction force and slip velocity measurements allows for the design of an adaptive backstepping controller that is shown to be asymptotically stable via a Lyapunov-based analysis. Experiments with multiple objects using a prototype gripper with embedded sensing show that the proposed scheme is able to effectively immobilize novel objects within the gripper fingers. Furthermore, it is seen that the adaptation allows for close estimation of the minimum grasp force required for safe grasping which results in minimal deformation of the grasped object.In Chapter 4, we present the design and implementation of the motion controllerand adaptive interface for the second generation of the UCF-MANUSintelligent assistive robotic manipulator system. Based on usability testingfor the system, several features were implemented in the interface thatcould reduce the complexity of the human-robot interaction while alsocompensating for the deficits in different human factors, such as WorkingMemory, Response Inhibition, Processing Speed; , Depth Perception, SpatialAbility, Contrast Sensitivity. For the controller part, we designed severalnew features to provide the user has a less complex and safer interactionwith the robot, such as `One-click mode', `Move suggestion mode' and`Gripper Control Assistant'. As for the adaptive interface design, wedesigned and implemented compensators such as `Contrast Enhancement',`Object Proximity Velocity Reduction' and `Orientation Indicator'.
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Date Issued: 2019
Identifier: CFE0007798, ucf:52360
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0007798

Title: Interactive Perception in Robotics.
Creator: Baghbahari Baghdadabad, Masoud, Behal, Aman, Haralambous, Michael, Lin, Mingjie, Sukthankar, Gita, Xu, Yunjun, University of Central Florida
Abstract / Description: Interactive perception is a significant and unique characteristic of embodied agents. An agent can discover plenty of knowledge through active interaction with its surrounding environment. Recently, deep learning structures introduced new possibilities to interactive perception in robotics. The advantage of deep learning is in acquiring self-organizing features from gathered data; however,it is computationally impractical to implement in real-time interaction applications. Moreover, it can be...
Show moreInteractive perception is a significant and unique characteristic of embodied agents. An agent can discover plenty of knowledge through active interaction with its surrounding environment. Recently, deep learning structures introduced new possibilities to interactive perception in robotics. The advantage of deep learning is in acquiring self-organizing features from gathered data; however,it is computationally impractical to implement in real-time interaction applications. Moreover, it can be difficult to attach a physical interpretation. An alternative suggested framework in such cases is integrated perception-action.In this dissertation, we propose two integrated interactive perception-action algorithms for real-time automated grasping of novel objects using pure tactile sensing. While visual sensing andprocessing is necessary for gross reaching movements, it can slow down the grasping process if it is the only sensing modality utilized. To overcome this issue, humans primarily utilize tactile perceptiononce the hand is in contact with the object. Inspired by this, we first propose an algorithm to define similar ability for a robot by formulating the required grasping steps.Next, we develop the algorithm to achieve force closure constraint via suggesting a human-like behavior for the robot to interactively identify the object. During this process, the robot adjuststhe hand through an interactive exploration of the object's local surface normal vector. After the robot finds the surface normal vector, it then tries to find the object edges to have a graspable finalrendezvous with the object. Such achievement is very important in order to find the objects edges for rectangular objects before fully grasping the object. We implement the proposed approacheson an assistive robot to demonstrate the performance of interactive perception-action strategies to accomplish grasping task in an automatic manner.
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Date Issued: 2019
Identifier: CFE0007780, ucf:52361
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0007780

Title: Complex-valued adaptive digital signal enhancement for applications in wireless communication systems.
Creator: Liu, Ying, Mikhael, Wasfy, Batarseh, Issa, Yang, Thomas, Hunter, Matthew, Haralambous, Michael, Myers, Brent, University of Central Florida
Abstract / Description: In recent decades, the wireless communication industry has attracted a great deal of research efforts to satisfy rigorous performance requirements and preserve high spectral efficiency. Along with this trend, I/Q modulation is frequently applied in modern wireless communications to develop high performance and high data rate systems. This has necessitated the need for applying efficient complex-valued signal processing techniques to highly-integrated, multi-standard receiver devices.In this...
Show moreIn recent decades, the wireless communication industry has attracted a great deal of research efforts to satisfy rigorous performance requirements and preserve high spectral efficiency. Along with this trend, I/Q modulation is frequently applied in modern wireless communications to develop high performance and high data rate systems. This has necessitated the need for applying efficient complex-valued signal processing techniques to highly-integrated, multi-standard receiver devices.In this dissertation, novel techniques for complex-valued digital signal enhancement are presented and analyzed for various applications in wireless communications. The first technique is a unified block processing approach to generate the complex-valued conjugate gradient Least Mean Square (LMS) techniques with optimal adaptations. The proposed algorithms exploit the concept of the complex conjugate gradients to find the orthogonal directions for updating the adaptive filter coefficients at each iteration. Along each orthogonal direction, the presented algorithms employ the complex Taylor series expansion to calculate time-varying convergence factors tailored for the adaptive filter coefficients. The performance of the developed technique is tested in the applications of channel estimation, channel equalization, and adaptive array beamforming. Comparing with the state of the art methods, the proposed techniques demonstrate improved performance and exhibit desirable characteristics for practical use.The second complex-valued signal processing technique is a novel Optimal Block Adaptive algorithm based on Circularity, OBA-C. The proposed OBA-C method compensates for a complex imbalanced signal by restoring its circularity. In addition, by utilizing the complex Taylor series expansion, the OBA-C method optimally updates the adaptive filter coefficients at each iteration. This algorithm can be applied to mitigate the frequency-dependent I/Q mismatch effects in analog front-end. Simulation results indicate that comparing with the existing methods, OBA-C exhibits superior convergence speed while maintaining excellent accuracy. The third technique is regarding interference rejection in communication systems. The research on both LMS and Independent Component Analysis (ICA) based techniques continues to receive significant attention in the area of interference cancellation. The performance of the LMS and ICA based approaches is studied for signals with different probabilistic distributions. Our research indicates that the ICA-based approach works better for super-Gaussian signals, while the LMS-based method is preferable for sub-Gaussian signals. Therefore, an appropriate choice of interference suppression algorithms can be made to satisfy the ever-increasing demand for better performance in modern receiver design.
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Date Issued: 2012
Identifier: CFE0004572, ucf:49192
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0004572

Title: Microgrid Control and Protection: Stability and Security.
Creator: Keshavarztalebi, Morteza, Behal, Aman, Haralambous, Michael, Sun, Wei, Jain, Amit Kumar, Kutkut, Nasser, University of Central Florida
Abstract / Description: When the microgrid disconnects from the main grid in response to, say, upstream disturbance orvoltage fluctuation and goes to islanding mode, both voltage and frequency at all locations in themicrogrid have to be regulated to nominal values in a short amount of time before the operation ofprotective relays. Motivated by this, we studied the application of intelligent pinning of distributed cooperative secondary control of distributed generators in islanded microgrid operation in a power...
Show moreWhen the microgrid disconnects from the main grid in response to, say, upstream disturbance orvoltage fluctuation and goes to islanding mode, both voltage and frequency at all locations in themicrogrid have to be regulated to nominal values in a short amount of time before the operation ofprotective relays. Motivated by this, we studied the application of intelligent pinning of distributed cooperative secondary control of distributed generators in islanded microgrid operation in a power system. In the first part, the problem of single and multi-pinning of distributed cooperative secondary control of DGs in a microgrid is formulated. It is shown that the intelligent selection of a pinning set based on the number of its connections and distance of leader DG/DGs from the rest of the network, i.e., degree of connectivity, strengthens microgrid voltage and frequency regulation performance both in transient and steady state. The proposed control strategy and algorithm are validated by simulation in MATLAB/SIMULINK using different microgrid topologies. It is shown that it is much easier to stabilize the microgrid voltage and frequency in islanding mode operationby specifically placing the pinning node on the DGs with high degrees of connectivity than byrandomly placing pinning nodes into the network. In all of these research study cases, DGs areonly required to communicate with their neighboring units which facilitates the distributed controlstrategy.Historically, the models for primary control are developed for power grids with centralized powergeneration, in which the transmission lines are assumed to be primarily inductive. However, fordistributed power generation, this assumption does not hold since the network has significant resistive impedance as well. Hence, it is of utmost importance to generalize the droop equations, i.e., primary control, to arrive at a proper model for microgrid systems. Motivated by this, we proposed the secondary adaptive voltage and frequency control of distributed generators for low and medium voltage microgrid in autonomous mode to overcome the drawback of existing classical droop based control techniques. Our proposed secondary control strategy is adaptive with line parameters and can be applied to all types of microgrids to address the simultaneous impacts of active and reactive power on the microgrids voltage and frequency. Also, since the parameters in the network model are unknown or uncertain, the second part of our research studies adaptive distributed estimation/compensation. It is shown that this is an effective method to robustly regulate the microgrid variables to their desired values.The security of power systems against malicious cyberphysical data attacks is the third topic of this dissertation. The adversary always attempts to manipulate the information structure of the power system and inject malicious data to deviate state variables while evading the existing detection techniques based on residual test. The solutions proposed in the literature are capable of immunizing the power system against false data injection but they might be too costly and physically not practical in the expansive distribution network. To this end, we define an algebraic condition for trustworthy power system to evade malicious data injection. The proposed protection scheme secures the power system by deterministically reconfiguring the information structure and corresponding residual test. More importantly, it does not require any physical effort in either microgrid or network level. The identification scheme of finding meters being attacked is proposed as well. Eventually, a well-known IEEE 30-bus system is adopted to demonstrate the effectiveness of the proposed schemes.
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Date Issued: 2016
Identifier: CFE0006338, ucf:51569
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0006338

Title: Design of High-Efficiency Rare-Earth Permanent Magnet Synchronous Motor and Drive System.
Creator: Liu, Hanzhou, Wu, Thomas, Batarseh, Issa, Haralambous, Michael, Lin, Mingjie, Chow, Louis, University of Central Florida
Abstract / Description: Utilization of renewable energy has become the future trend in the trucking industry. Electrical power generated from renewable energy can replace part of the fuel usage. There is usually limited space for storing on-board battery. Thus, to better utilize the battery power, it becomes critical to have an efficient energy conversion device that can transfer energy from battery to amenities such as air conditioner, microwave, TV, mini refrigerator, etc. In this dissertation, a designed...
Show moreUtilization of renewable energy has become the future trend in the trucking industry. Electrical power generated from renewable energy can replace part of the fuel usage. There is usually limited space for storing on-board battery. Thus, to better utilize the battery power, it becomes critical to have an efficient energy conversion device that can transfer energy from battery to amenities such as air conditioner, microwave, TV, mini refrigerator, etc. In this dissertation, a designed permanent magnet synchronous motor (PMSM) can be such energy conversion device for an electric Auxiliary Power Unit (APU) application, which will have a desired output power of 2 kW at 2krpm, and maintain an efficiency greater than 90%. The design calls for good performance over a speed range of 1.5 krpm to 2.5 krpm. The current air conditioning system for automobile works only by (")on(") or (")off(") mode. For the heat mode, that means it is on with heat once the cabin temperature drops down to a level and off if the temperature rises back above that level. For the cool mode, that means it is on with cold air once the cabin temperature rises above a level, and off if the temperature drops back to that level. This is because the motor does not have the speed control functionality according to the temperature variation and people in the cabin do not feel much comfortable for that temperature change periodically as well as the inefficient energy consumption. With our novel technology, the designed motor can adjust its speed through the embedded system of our novel DC to AC inverter to provide a variable load. For example, with high efficiency, the fully charged battery sets (48 volts) can supply the electrical power and cooling to the cabin forabout 10 hours without recharging using the main engine.Copper loss is the most significant part of all the losses in low speed electric machines. Reducing the copper loss is the key to build highly efficient machine. We use copper wires with the current density lower than traditional design which result in large cross section of the wire and thus reduce the copper loss and improve the efficiency. This also makes thermal management easier and reduces the need to use active cooling methodologies (such as fan, liquid cooling or spray cooling); and hence the overall power density of the whole system (including cooling devices) will not decease much. In traditional machine design, the torque angle is designed to be in the rangeof 15 to 30 degrees at the rated power and speed. In our high efficiency motor design, we propose to use much lower torque angle of 2 to 15 degrees at the rated power and speed. Such design caneffectively increase the overload power handling capability and efficiency. Besides, small torque angle will result in large airgap size and increased thickness of the permanent magnets. Large airgap helps to reduce the windage loss of the machine and generates a lot less mechanical noise based on our design experience. Increased thickness of the permanent magnets helps to avoid thedemagnetization.As the technology of advanced micro-controller develops, fast response power electronic devices can be used in the motor controller. A novel design of DC to AC inverter with the fieldoriented control scheme and sliding mode observer algorithm for driving the designed motor is developed. The inverter has the capability of driving the motor with its output power at 2 kW.
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Date Issued: 2015
Identifier: CFE0006224, ucf:51064
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0006224

Title: Modified System Design and Implementation of an Intelligent Assistive Robotic Manipulator.
Creator: Paperno, Nicholas, Behal, Aman, Haralambous, Michael, Sukthankar, Gita, Boloni, Ladislau, Smither, Janan, University of Central Florida
Abstract / Description: This thesis presents three improvements to the current UCF MANUS systems. The first improvement modifies the existing fine motion controller into PI controller that has been optimized to prevent the object from leaving the view of the cameras used for visual servoing. This is achieved by adding a weight matrix to the proportional part of the controller that is constrained by an artificial ROI. When the feature points being used are approaching the boundaries of the ROI, the optimized...
Show moreThis thesis presents three improvements to the current UCF MANUS systems. The first improvement modifies the existing fine motion controller into PI controller that has been optimized to prevent the object from leaving the view of the cameras used for visual servoing. This is achieved by adding a weight matrix to the proportional part of the controller that is constrained by an artificial ROI. When the feature points being used are approaching the boundaries of the ROI, the optimized controller weights are calculated using quadratic programming and added to the nominal proportional gain portion of the controller. The second improvement was a compensatory gross motion method designed to ensure that the desired object can be identified. If the object cannot be identified after the initial gross motion, the end-effector will then be moved to one of three different locations around the object until the object is identified or all possible positions are checked. This framework combines the Kanade-Lucase-Tomasi local tracking method with the ferns global detector/tracker to create a method that utilizes the strengths of both systems to overcome their inherent weaknesses. The last improvement is a particle-filter based tracking algorithm that robustifies the visual servoing function of fine motion. This method performs better than the current global detector/tracker that was being implemented by allowing the tracker to successfully track the object in complex environments with non-ideal conditions.
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Date Issued: 2015
Identifier: CFE0005681, ucf:50180
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0005681

Title: Optimal distribution network reconfiguration using meta-heuristic algorithms.
Creator: Asrari, Arash, Wu, Thomas, Lotfifard, Saeed, Haralambous, Michael, Atia, George, Pazour, Jennifer, University of Central Florida
Abstract / Description: Finding optimal configuration of power distribution systems topology is an NP-hard combinatorial optimization problem. It becomes more complex when time varying nature of loads in large-scale distribution systems is taken into account. In the second chapter of this dissertation, a systematic approach is proposed to tackle the computational burden of the procedure. To solve the optimization problem, a novel adaptive fuzzy based parallel genetic algorithm (GA) is proposed that employs the...
Show moreFinding optimal configuration of power distribution systems topology is an NP-hard combinatorial optimization problem. It becomes more complex when time varying nature of loads in large-scale distribution systems is taken into account. In the second chapter of this dissertation, a systematic approach is proposed to tackle the computational burden of the procedure. To solve the optimization problem, a novel adaptive fuzzy based parallel genetic algorithm (GA) is proposed that employs the concept of parallel computing in identifying the optimal configuration of the network. The integration of fuzzy logic into GA enhances the efficiency of the parallel GA by adaptively modifying the migration rates between different processors during the optimization process. A computationally efficient graph encoding method based on Dandelion coding strategy is developed which automatically generates radial topologies and prevents the construction of infeasible radial networks during the optimization process. The main shortcoming of the proposed algorithm in Chapter 2 is that it identifies only one single solution. It means that the system operator will not have any option but relying on the found solution. That is why a novel hybrid optimization algorithm is proposed in the third chapter of this dissertation that determines Pareto frontiers, as candidate solutions, for multi-objective distribution network reconfiguration problem. Implementing this model, the system operator will have more flexibility in choosing the best configuration among the alternative solutions. The proposed hybrid optimization algorithm combines the concept of fuzzy Pareto dominance (FPD) with shuffled frog leaping algorithm (SFLA) to recognize non-dominated suboptimal solutions identified by SFLA. The local search step of SFLA is also customized for power systems applications so that it automatically creates and analyzes only the feasible and radial configurations in its optimization procedure which significantly increases the convergence speed of the algorithm. In the fourth chapter, the problem of optimal network reconfiguration is solved for the case in which the system operator is going to employ an optimization algorithm that is automatically modifying its parameters during the optimization process. Defining three fuzzy functions, the probability of crossover and mutation will be adaptively tuned as the algorithm proceeds and the premature convergence will be avoided while the convergence speed of identifying the optimal configuration will not decrease. This modified genetic algorithm is considered a step towards making the parallel GA, presented in the second chapter of this dissertation, more robust in avoiding from getting stuck in local optimums. In the fifth chapter, the concentration will be on finding a potential smart grid solution to more high-quality suboptimal configurations of distribution networks. This chapter is considered an improvement for the third chapter of this dissertation for two reasons: (1) A fuzzy logic is used in the partitioning step of SFLA to improve the proposed optimization algorithm and to yield more accurate classification of frogs. (2) The problem of system reconfiguration is solved considering the presence of distributed generation (DG) units in the network. In order to study the new paradigm of integrating smart grids into power systems, it will be analyzed how the quality of suboptimal solutions can be affected when DG units are continuously added to the distribution network.The heuristic optimization algorithm which is proposed in Chapter 3 and is improved in Chapter 5 is implemented on a smaller case study in Chapter 6 to demonstrate that the identified solution through the optimization process is the same with the optimal solution found by an exhaustive search.
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Date Issued: 2015
Identifier: CFE0005575, ucf:50238
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0005575

Adaptive (2)	+ -
Adaptive Control (2)	+ -
Assistive Robotics (2)	+ -
Control (2)	+ -
Grasping (2)	+ -

Robotics (2)	+ -
Tracking (2)	+ -
(2D)^2PCA (1)	+ -
2DPCA (1)	+ -
Adaboost (1)	+ -
Algorithms (1)	+ -
Amplitude Estimation (1)	+ -
Aortic Valve Dynamics (1)	+ -
Assistive Robotic (1)	+ -
Autonomous (1)	+ -
Baxter Research Robot (1)	+ -
Bio-mechanical modeling (1)	+ -
Classification (1)	+ -
Computer Vision (1)	+ -
Control Systems (1)	+ -
Cooperative Control (1)	+ -
Cyber Physical Attack (1)	+ -
DC/AC inverter (1)	+ -
DC/DC converter (1)	+ -
DCT (1)	+ -
Decentralized control (1)	+ -
Decision Tree (1)	+ -
Depth Map (1)	+ -
Differential game (1)	+ -
Distributed Algorithm (1)	+ -

Haralambous, Michael (29)	+ -
University of Central Florida (29)	+ -
Behal, Aman (12)	+ -
Boloni, Ladislau (8)	+ -
Qu, Zhihua (8)	+ -

Mikhael, Wasfy (6)	+ -
Xu, Yunjun (6)	+ -
Batarseh, Issa (4)	+ -
Kutkut, Nasser (3)	+ -
Simaan, Marwan (3)	+ -
Wu, Xinzhang (3)	+ -
Atia, George (2)	+ -
Chow, Louis (2)	+ -
Divo, Eduardo (2)	+ -
Jabalameli, Amirhossein (2)	+ -
Kassab, Alain (2)	+ -
Lin, Mingjie (2)	+ -
Lotfifard, Saeed (2)	+ -
Myers, Brent (2)	+ -
Paperno, Nicholas (2)	+ -
Pourmohammadi Fallah, Yaser (2)	+ -
Sukthankar, Gita (2)	+ -
Wu, Thomas (2)	+ -
Yuan, Jiann-Shiun (2)	+ -
Alharbi, Mahmood (1)	+ -
Alhosani, Mohamed (1)	+ -
Alrasheed, Waleed (1)	+ -
An, Vatana (1)	+ -
Asrari, Arash (1)	+ -
Baghbahari Baghdadabad, Masoud (1)	+ -

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