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- Electrical and Computer Engineering Faculty Research & Creative Works (30)
- Mechanical and Aerospace Engineering Faculty Research & Creative Works (13)
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Articles 1 - 30 of 45
Full-Text Articles in Engineering
A Displacement Controlled Fatigue Test Method For Additively Manufactured Materials, Mohammad Masud Parvez, Yitao Chen, Sreekar Karnati, Connor Coward, Joseph William Newkirk, Frank W. Liou
A Displacement Controlled Fatigue Test Method For Additively Manufactured Materials, Mohammad Masud Parvez, Yitao Chen, Sreekar Karnati, Connor Coward, Joseph William Newkirk, Frank W. Liou
Materials Science and Engineering Faculty Research & Creative Works
A novel adaptive displacement-controlled test setup was developed for fatigue testing on mini specimens. In property characterization of additive manufacturing materials, mini specimens are preferred due to the specimen preparation, and manufacturing cost but mini specimens demonstrate higher fatigue strength than standard specimens due to the lower probability of material defects resulting in fatigue. In this study, a dual gauge section Krouse type mini specimen was designed to conduct fatigue tests on additively manufactured materials. The large surface area of the specimen with a constant stress distribution and increased control volume as the gauge section may capture all different types …
An Adaptive Control Strategy For Dstatcom Applications In An Electric Ship Power System, Pinaki Mitra, Ganesh K. Venayagamoorthy
An Adaptive Control Strategy For Dstatcom Applications In An Electric Ship Power System, Pinaki Mitra, Ganesh K. Venayagamoorthy
Electrical and Computer Engineering Faculty Research & Creative Works
Distribution static compensator (DSTATCOM) is a shunt compensation device that is generally used to solve power quality problems in distribution systems. In an all-electric ship power system, power quality issues arise due to high-energy demand loads such as pulse loads. This paper presents the application of a DSTATCOM to improve the power quality in a ship power system during and after pulse loads. The control strategy of the DSTATCOM plays an important role in maintaining the voltage at the point of common coupling. A novel adaptive control strategy for the DSTATCOM based on artificial immune system (AIS) is presented in …
High Bandwidth Control Of Precision Motion Instrumentation, Douglas A. Bristow, Jingyan Dong, Andrew G. Alleyne, Srinivasa M. Salapaka, Placid M. Ferreira
High Bandwidth Control Of Precision Motion Instrumentation, Douglas A. Bristow, Jingyan Dong, Andrew G. Alleyne, Srinivasa M. Salapaka, Placid M. Ferreira
Mechanical and Aerospace Engineering Faculty Research & Creative Works
This article presents a high-bandwidth control design suitable for precision motion instrumentation. Iterative learning control (ILC), a feedforward technique that uses previous iterations of the desired trajectory, is used to leverage the repetition that occurs in many tasks, such as raster scanning in microscopy. Two ILC designs are presented. The first design uses the motion system dynamic model to maximize bandwidth. The second design uses a time-varying bandwidth that is particularly useful for nonsmooth trajectories such as raster scanning. Both designs are applied to a multiaxis piezoelectric-actuated flexure system and evaluated on a nonsmooth trajectory. The ILC designs demonstrate significant …
Joint Adaptive Distributed Rate And Power Control For Wireless Networks, James W. Fonda, Jagannathan Sarangapani, Steve Eugene Watkins
Joint Adaptive Distributed Rate And Power Control For Wireless Networks, James W. Fonda, Jagannathan Sarangapani, Steve Eugene Watkins
Electrical and Computer Engineering Faculty Research & Creative Works
A novel adaptive distributed rate and power control (ADRPC) protocol is introduced for wireless networks. The proposed controller contrasts from others by providing nonlinear compensation to the problem of transmission power and bit-rate adaptation. The protocol provides control of both signal-to-interference ratio (SIR) and quality-of-service (QoS) support to bit-rate adaptation. Bit-rate adaptation is performed by local estimation of congestion levels, rendering little packet overhead, using Lyapunov based adaptive control methods. Performance of the proposed control scheme is shown through analytical proof and simulation examples.
Implementation Of Neuroidentifiers Trained By Pso On A Plc Platform For A Multimachine Power System, Curtis Alan Parrott, Ganesh K. Venayagamoorthy
Implementation Of Neuroidentifiers Trained By Pso On A Plc Platform For A Multimachine Power System, Curtis Alan Parrott, Ganesh K. Venayagamoorthy
Electrical and Computer Engineering Faculty Research & Creative Works
Power systems are nonlinear with fast changing dynamics. In order to design a nonlinear adaptive controller for damping power system oscillations, it becomes necessary to identify the dynamics of the system. This paper demonstrates the implementation of a neural network based system identifier, referred to as a neuroidentifier, on a programmable logic controller (PLC) platform. Two separate neuroidentifiers are trained using the particle swarm optimization (PSO) algorithm to identify the dynamics in a two-area four machine power system, one neuroidentifier for Area 1 and the other for Area 2. The power system is simulated in real time on the Real …
Issues On Stability Of Adp Feedback Controllers For Dynamical Systems, S. N. Balakrishnan, Jie Ding, F. L. Lewis
Issues On Stability Of Adp Feedback Controllers For Dynamical Systems, S. N. Balakrishnan, Jie Ding, F. L. Lewis
Mechanical and Aerospace Engineering Faculty Research & Creative Works
This paper traces the development of neural-network (NN)-based feedback controllers that are derived from the principle of adaptive/approximate dynamic programming (ADP) and discusses their closed-loop stability. Different versions of NN structures in the literature, which embed mathematical mappings related to solutions of the ADP-formulated problems called “adaptive critics” or “action-critic” networks, are discussed. Distinction between the two classes of ADP applications is pointed out. Furthermore, papers in “model-free” development and model-based neurocontrollers are reviewed in terms of their contributions to stability issues. Recent literature suggests that work in ADP-based feedback controllers with assured stability is growing in diverse forms.
Nsf Career: Scalable Learning And Adaptation With Intelligent Techniques And Neural Networks For Reconfiguration And Survivability Of Complex Systems, Ganesh K. Venayagamoorthy
Nsf Career: Scalable Learning And Adaptation With Intelligent Techniques And Neural Networks For Reconfiguration And Survivability Of Complex Systems, Ganesh K. Venayagamoorthy
Electrical and Computer Engineering Faculty Research & Creative Works
The NSF CAREER program is a premier program that emphasizes the importance the foundation places on the early development of academic careers solely dedicated to stimulating the discovery process in which the excitement of research enriched by inspired teaching and enthusiastic learning. This paper describes the research and education experiences gained by the principal investigator and his research collaborators and students as a result of a NSF CAREER proposal been awarded by the power, control and adaptive networks (PCAN) program of the electrical, communications and cyber systems division, effective June 1, 2004. In addition, suggestions on writing a winning NSF …
Weighting Matrix Design For Robust Monotonic Convergence In Norm Optimal Iterative Learning Control, Douglas A. Bristow
Weighting Matrix Design For Robust Monotonic Convergence In Norm Optimal Iterative Learning Control, Douglas A. Bristow
Mechanical and Aerospace Engineering Faculty Research & Creative Works
In this paper we examine the robustness of norm optimal ILC with quadratic cost criterion for discrete-time, linear time-invariant, single-input single-output systems. A bounded multiplicative uncertainty model is used to describe the uncertain system and a sufficient condition for robust monotonic convergence is developed. We find that, for sufficiently large uncertainty, the performance weighting can not be selected arbitrarily large, and thus overall performance is limited. To maximize available performance, a time-frequency design methodology is presented to shape the weighting matrix based on the initial tracking error. The design is applied to a nanopositioning system and simulation results are presented.
Design Of A Linear Time-Varying Cross-Coupled Iterative Learning Controller, K. L. Barton, Douglas A. Bristow, Andrew G. Alleyne
Design Of A Linear Time-Varying Cross-Coupled Iterative Learning Controller, K. L. Barton, Douglas A. Bristow, Andrew G. Alleyne
Mechanical and Aerospace Engineering Faculty Research & Creative Works
In many manufacturing applications contour tracking is more important than individual axis tracking. Many control techniques, including iterative learning control (ILC), target individual axis error. Because individual axis error only indirectly relates to contour error, these approaches may not be very effective for contouring applications. Cross-coupled ILC (CCILC) is a variation on traditional ILC that targets the contour tracking directly. In contour trajectories with rapid changes, high frequency control is necessary in order to meet tracking requirements. This paper presents an improved CCILC that uses a linear time-varying (LTV) filter to provide high frequency control for short durations. The improved …
Frequency Domain Analysis And Design Of Iterative Learning Control For Systems With Stochastic Disturbances, Douglas A. Bristow
Frequency Domain Analysis And Design Of Iterative Learning Control For Systems With Stochastic Disturbances, Douglas A. Bristow
Mechanical and Aerospace Engineering Faculty Research & Creative Works
In this work we examine the performance of iterative learning control (ILC) for systems with non-repeating disturbances and random noise. Single-input, single- output linear time-invariant systems and iteration-invariant learning filters are considered. We find that a tradeoff exists between the convergence rate and converged error spectrum. Optimal filter designs, which are dependant on the disturbance and noise spectra, are developed. We also present simple design guidelines for the case when explicit models of disturbance and noise spectra are not available. A numerical design example is presented.
Artificial Immune System Based Dstatcom Control For An Electric Ship Power System, Pinaki Mitra, Ganesh K. Venayagamoorthy
Artificial Immune System Based Dstatcom Control For An Electric Ship Power System, Pinaki Mitra, Ganesh K. Venayagamoorthy
Electrical and Computer Engineering Faculty Research & Creative Works
Distribution static compensator (DSTATCOM) is a shunt compensation device which is generally used to solve power quality problems in distribution systems. In an all-electric ship power system, these power quality problems mainly arise due to the pulsed loads, which causes the degradation of the entire system performance. This paper presents the application of DSTATCOM to improve the power quality in a ship power system during and after pulsed loads. The control strategy of the DSTATCOM plays an important role in maintaining the voltage at the point of common coupling. A novel adaptive control strategy for the DSTATCOM based on artificial …
Output Feedback Controller For Operation Of Spark Ignition Engines At Lean Conditions Using Neural Networks, Jonathan B. Vance, Brian C. Kaul, Jagannathan Sarangapani, J. A. Drallmeier
Output Feedback Controller For Operation Of Spark Ignition Engines At Lean Conditions Using Neural Networks, Jonathan B. Vance, Brian C. Kaul, Jagannathan Sarangapani, J. A. Drallmeier
Electrical and Computer Engineering Faculty Research & Creative Works
Spark ignition (SI) engines operating at very lean conditions demonstrate significant nonlinear behavior by exhibiting cycle-to-cycle bifurcation of heat release. Past literature suggests that operating an engine under such lean conditions can significantly reduce NO emissions by as much as 30% and improve fuel efficiency by as much as 5%-10%. At lean conditions, the heat release per engine cycle is not close to constant, as it is when these engines operate under stoichiometric conditions where the equivalence ratio is 1.0. A neural network controller employing output feedback has shown ability in simulation to reduce the nonlinear cyclic dispersion observed under …
Monotonic Convergence Of Iterative Learning Control For Uncertain Systems Using A Time-Varying Filter, Douglas A. Bristow, Andrew G. Alleyne
Monotonic Convergence Of Iterative Learning Control For Uncertain Systems Using A Time-Varying Filter, Douglas A. Bristow, Andrew G. Alleyne
Mechanical and Aerospace Engineering Faculty Research & Creative Works
Iterative learning control (ILC) is a learning technique used to improve the performance of systems that execute the same task multiple times. Learning transient behavior has emerged as an important topic in the design and analysis of ILC systems. In practice, the learning control is often low-pass filtered with a ldquoQ-filterrdquo to prevent transient growth, at the cost of performance. In this note, we consider linear time-invariant, discrete-time, single-input single-output systems, and convert frequency-domain uncertainty models to a time-domain representation for analysis. We then develop robust monotonic convergence conditions, which depend directly on the choice of the Q-filter and are …
Comparisons Of An Adaptive Neural Network Based Controller And An Optimized Conventional Power System Stabilizer, Wenxin Liu, Ganesh K. Venayagamoorthy, Jagannathan Sarangapani, Donald C. Wunsch, Mariesa Crow, Li Liu, David A. Cartes
Comparisons Of An Adaptive Neural Network Based Controller And An Optimized Conventional Power System Stabilizer, Wenxin Liu, Ganesh K. Venayagamoorthy, Jagannathan Sarangapani, Donald C. Wunsch, Mariesa Crow, Li Liu, David A. Cartes
Electrical and Computer Engineering Faculty Research & Creative Works
Power system stabilizers are widely used to damp out the low frequency oscillations in power systems. In power system control literature, there is a lack of stability analysis for proposed controller designs. This paper proposes a Neural Network (NN) based stabilizing controller design based on a sixth order single machine infinite bus power system model. The NN is used to compensate the complex nonlinear dynamics of power system. To speed up the learning process, an adaptive signal is introduced to the NN's weights updating rule. The NN can be directly used online without offline training process. Magnitude constraint of the …
Reinforcement Learning Based Output-Feedback Control Of Nonlinear Nonstrict Feedback Discrete-Time Systems With Application To Engines, Peter Shih, Jonathan B. Vance, Brian C. Kaul, Jagannathan Sarangapani, J. A. Drallmeier
Reinforcement Learning Based Output-Feedback Control Of Nonlinear Nonstrict Feedback Discrete-Time Systems With Application To Engines, Peter Shih, Jonathan B. Vance, Brian C. Kaul, Jagannathan Sarangapani, J. A. Drallmeier
Electrical and Computer Engineering Faculty Research & Creative Works
A novel reinforcement-learning based output-adaptive neural network (NN) controller, also referred as the adaptive-critic NN controller, is developed to track a desired trajectory for a class of complex nonlinear discrete-time systems in the presence of bounded and unknown disturbances. The controller includes an observer for estimating states and the outputs, critic, and two action NNs for generating virtual, and actual control inputs. The critic approximates certain strategic utility function and the action NNs are used to minimize both the strategic utility function and their outputs. All NN weights adapt online towards minimization of a performance index, utilizing gradient-descent based rule. …
Neural Network Controller Development And Implementation For Spark Ignition Engines With High Egr Levels, Jonathan B. Vance, Atmika Singh, Brian C. Kaul, Jagannathan Sarangapani, J. A. Drallmeier
Neural Network Controller Development And Implementation For Spark Ignition Engines With High Egr Levels, Jonathan B. Vance, Atmika Singh, Brian C. Kaul, Jagannathan Sarangapani, J. A. Drallmeier
Electrical and Computer Engineering Faculty Research & Creative Works
Past research has shown substantial reductions in the oxides of nitrogen (NOx) concentrations by using 10% -25% exhaust gas recirculation (EGR) in spark ignition (SI) engines (see Dudek and Sain, 1989). However, under high EGR levels, the engine exhibits strong cyclic dispersion in heat release which may lead to instability and unsatisfactory performance preventing commercial engines to operate with high EGR levels. A neural network (NN)-based output feedback controller is developed to reduce cyclic variation in the heat release under high levels of EGR even when the engine dynamics are unknown by using fuel as the control input. A separate …
Online Reinforcement Learning Neural Network Controller Design For Nanomanipulation, Qinmin Yang, Jagannathan Sarangapani
Online Reinforcement Learning Neural Network Controller Design For Nanomanipulation, Qinmin Yang, Jagannathan Sarangapani
Electrical and Computer Engineering Faculty Research & Creative Works
In this paper, a novel reinforcement learning neural network (NN)-based controller, referred to adaptive critic controller, is proposed for affine nonlinear discrete-time systems with applications to nanomanipulation. In the online NN reinforcement learning method, one NN is designated as the critic NN, which approximates the long-term cost function by assuming that the states of the nonlinear systems is available for measurement. An action NN is employed to derive an optimal control signal to track a desired system trajectory while minimizing the cost function. Online updating weight tuning schemes for these two NNs are also derived. By using the Lyapunov approach, …
Intelligent Integration Of A Wind Farm To An Utility Power Network With Improved Voltage Stability, V. K. Polisetty, Sandhya R. Jetti, Ganesh K. Venayagamoorthy, Ronald G. Harley
Intelligent Integration Of A Wind Farm To An Utility Power Network With Improved Voltage Stability, V. K. Polisetty, Sandhya R. Jetti, Ganesh K. Venayagamoorthy, Ronald G. Harley
Electrical and Computer Engineering Faculty Research & Creative Works
The increasing effect of wind energy generation will influence the dynamic behavior of power systems by interacting with conventional generation and loads. Due to the inherent characteristics of wind turbines, non-uniform power production causes variations in system voltage and frequency. Therefore, a wind farm requires high reactive power compensation. Flexible AC transmission systems (FACTS) devices such as SVCs inject reactive power into the system which helps in maintaining a better voltage profile. This paper presents the design of a linear and a nonlinear coordinating controller between a SVC and the wind farm inverter at the point of interconnection. The performances …
Nanomanipulation Using Atomic Force Microscope With Drift Compensation, Qinmin Yang, Jagannathan Sarangapani
Nanomanipulation Using Atomic Force Microscope With Drift Compensation, Qinmin Yang, Jagannathan Sarangapani
Electrical and Computer Engineering Faculty Research & Creative Works
This paper proposes an atomic force microscope (AFM) based force controller to push nanoparticles on the substrates since it is tedious for human. A block phase correlation-based algorithm is embedded into the controller for compensating the thermal drift during nanomanipulation. Further, a neural network (NN) is employed to approximate the unknown nanoparticle and substrate contact dynamics including the roughness effects. Using the NN-based adaptive force controller the task of pushing nanoparticles is demonstrated. Finally, using the Lyapunov-based stability analysis, the uniform ultimately boundedness (UUB) of the closed-loop signals is demonstrated
Adaptive Neural Network Control And Wireless Sensor Network Based Localization For Uav Formation, H. Wu, Jagannathan Sarangapani
Adaptive Neural Network Control And Wireless Sensor Network Based Localization For Uav Formation, H. Wu, Jagannathan Sarangapani
Electrical and Computer Engineering Faculty Research & Creative Works
We consider a team of unmanned aerial vehicles (UAV's) equipped with sensors and motes for wireless communication for the task of navigating to a desired location in a formation. First a neural network (NN)-based control scheme is presented that allows the UAVs to track a desired position and orientation with reference to the neighboring UAVs or obstacles in the environment. Second, we discuss a graph theory-based scheme for discovery, localization and cooperative control. The purpose of the NN cooperative controller is to achieve and maintain the desired formation shape in the presence of unmodeled dynamics and bounded unknown disturbances. Numerical …
Decentralized Power Control With Implementation For Rfid Networks, Kainan Cha, Anil Ramachandran, David Pommerenke, Jagannathan Sarangapani
Decentralized Power Control With Implementation For Rfid Networks, Kainan Cha, Anil Ramachandran, David Pommerenke, Jagannathan Sarangapani
Electrical and Computer Engineering Faculty Research & Creative Works
In radio frequency identification (RFID) systems, the detection range and read rates will suffer from interference among high power reading devices. This problem grows severely and degrades system performance in dense RFID networks. In this paper, we investigate a suite of feasible power control schemes to ensure overall coverage area of the system while maintaining a desired read rate. The power control scheme and MAC protocol dynamically adjusts the RFID reader power output in response to the interference level seen locally during tag reading for an acceptable signal-to-noise ratio (SNR). We present novel distributed adaptive power control (DAPC) and probabilistic …
Intelligent Optimal Control Of Excitation And Turbine Systems In Power Networks, Ganesh K. Venayagamoorthy, Ronald G. Harley
Intelligent Optimal Control Of Excitation And Turbine Systems In Power Networks, Ganesh K. Venayagamoorthy, Ronald G. Harley
Electrical and Computer Engineering Faculty Research & Creative Works
The increasing complexity of the modern power grid highlights the need for advanced modeling and control techniques for effective control of excitation and turbine systems. The crucial factors affecting the modern power systems today is voltage control and system stabilization during small and large disturbances. Simulation studies and real-time laboratory experimental studies carried out are described and the results show the successful control of the power system excitation and turbine systems with adaptive and optimal neurocontrol approaches. Performances of the neurocontrollers are compared with the conventional PI controllers for damping under different operating conditions for small and large disturbances.
Neuroadaptive Model Following Controller Design For A Nonaffine Uav Model, Nishant Unnikrishnan, S. N. Balakrishnan
Neuroadaptive Model Following Controller Design For A Nonaffine Uav Model, Nishant Unnikrishnan, S. N. Balakrishnan
Mechanical and Aerospace Engineering Faculty Research & Creative Works
This paper proposes a new model-following adaptive control design technique for nonlinear systems that are nonaffine in control. The adaptive controller uses online neural networks that guarantee tracking in the presence of unmodeled dynamics and/or parameter uncertainties present in the system model through an online control adaptation procedure. The controller design is carried out in two steps: (i) synthesis of a set of neural networks which capture the unmodeled (neglected) dynamics or model uncertainties due to parametric variations and (ii) synthesis of a controller that drives the state of the actual plant to that of a reference model. This method …
Dynamic Simulation Of A Mems Cantilever Switch, James W. Fonda, Steve Eugene Watkins
Dynamic Simulation Of A Mems Cantilever Switch, James W. Fonda, Steve Eugene Watkins
Electrical and Computer Engineering Faculty Research & Creative Works
The dynamic behavior of a micro-electro-mechanicalsystem (MEMS) cantilever switch is investigated. Overactuation of the switch can degrade bounce characteristics and reduce the lifetime of the contacts. This work concerns the development of a control system that limits the number of switch bounces and reduces the impact force on the beam tip. A limited mass-spring analysis of the tip-position is given and an associated control approach is applied. Input limiting, state-feedback, and adaptive control methods are compared. All results demonstrate improved switch bounce characteristics for the simplified beam model with the adaptive showing the best performance improvement. A comprehensive finite element …
Hdp Based Optimal Control Of A Grid Independent Pv System, Richard L. Welch, Ganesh K. Venayagamoorthy
Hdp Based Optimal Control Of A Grid Independent Pv System, Richard L. Welch, Ganesh K. Venayagamoorthy
Electrical and Computer Engineering Faculty Research & Creative Works
This paper presents an adaptive optimal control scheme for a grid independent photovoltaic (PV) system consisting of a PV collector array, a storage battery, and loads (critical and non-critical loads). The optimal control algorithm is based on the model-free heuristic dynamic programming (HDP), an adaptive critic design (ACD) technique which optimizes the control performance based on a utility function. The HDP critic network is used in a PV system simulation study to train a neurocontroller to provide optimal control for varying PV system output energy and load demands. The emphasis of the optimal controller is primarily to supply the critical …
Adaptive Critic Designs For Optimal Control Of Power Systems, Ganesh K. Venayagamoorthy, Ronald G. Harley
Adaptive Critic Designs For Optimal Control Of Power Systems, Ganesh K. Venayagamoorthy, Ronald G. Harley
Electrical and Computer Engineering Faculty Research & Creative Works
The increasing complexity of the modern power grid highlights the need for advanced modeling and control techniques for effective control of excitation, turbine and flexible AC transmission systems (FACTS). The crucial factors affecting the modern power systems today is voltage and load flow control. Simulation studies in the PSCAD/EMTDC environment and realtime laboratory experimental studies carried out are described and the results show the successful control of the power system elements and the entire power system with adaptive and optimal neurocontrol schemes. Performances of the neurocontrollers are compared with the conventional PI controllers for damping under different operating conditions for …
A Robust Controller For The Manipulation Of Micro Scale Objects, Qinmin Yang, Jagannathan Sarangapani
A Robust Controller For The Manipulation Of Micro Scale Objects, Qinmin Yang, Jagannathan Sarangapani
Electrical and Computer Engineering Faculty Research & Creative Works
A suite of novel robust controllers is presented for the manipulation and handling of micro-scale objects in a micro-electromechanical system (MEMS) where adhesive, surface tension, friction and van der Waals forces are dominant. Moreover, these forces are typically unknown. The robust controller overcomes the unknown system dynamics and ensures the performance in the presence of actuator constraints by assuming that the upper bounds on these forces are known. On the other hand, for the robust adaptive controller, the unknown forces are estimated online. Using the Lyapunov approach, the uniformly ultimate boundedness (UUB) of the closed-loop manipulation error is shown for …
An Adaptive Mamdani Fuzzy Logic Based Controller For A Static Compensator In A Multimachine Power System, Salman Mohagheghi, Ganesh K. Venayagamoorthy, Ronald G. Harley
An Adaptive Mamdani Fuzzy Logic Based Controller For A Static Compensator In A Multimachine Power System, Salman Mohagheghi, Ganesh K. Venayagamoorthy, Ronald G. Harley
Electrical and Computer Engineering Faculty Research & Creative Works
An adaptive Mamdani based fuzzy logic controller has been designed for controlling a static compensator (STATCOM) in a multimachine power system. Such a controller does not need any prior knowledge of the plant to be controlled and can efficiently control a STATCOM during different disturbances in the network. A model free approach using the controller output error is applied for training purposes that adaptively changes the controller output parameters based on a gradient descent method. Moreover, shrinking span membership functions are used for a more stable and accurate control performance. Simulation results show that the proposed controller outperforms the conventional …
Optimal Control Synthesis Of A Class Of Nonlinear Systems Using Single Network Adaptive Critics, Radhakant Padhi, Nishant Unnikrishnan, S. N. Balakrishnan
Optimal Control Synthesis Of A Class Of Nonlinear Systems Using Single Network Adaptive Critics, Radhakant Padhi, Nishant Unnikrishnan, S. N. Balakrishnan
Mechanical and Aerospace Engineering Faculty Research & Creative Works
Adaptive critic (AC) neural network solutions to optimal control designs using dynamic programming has reduced the need of complex computations and storage requirements that typical dynamic programming requires. In this paper, a "single network adaptive critic" (SNAC) is presented. This approach is applicable to a class of nonlinear systems where the optimal control (stationary) equation is explicitly solvable for control in terms of state and costate variables. The SNAC architecture offers three potential advantages; a simpler architecture, significant savings of computational load and reduction in approximation errors. In order to demonstrate these benefits, a real-life micro-electro-mechanical-system (MEMS) problem has been …
Neuroidentification Of System Parameters Of The Upfc In A Multimachine Power System, Radha P. Kalyani, Ganesh K. Venayagamoorthy
Neuroidentification Of System Parameters Of The Upfc In A Multimachine Power System, Radha P. Kalyani, Ganesh K. Venayagamoorthy
Electrical and Computer Engineering Faculty Research & Creative Works
The crucial factor affecting the modern power systems today is load flow control. The Unified Power Flow Controller is an effective means for controlling the power flow. The UPFC is controlled conventionally using PI controllers. This paper presents the designs of neuroidentifiers that models the system dynamics one-time step ahead making the pathway for the design of adaptive neurocontrollers. Two neuroidentifiers are used for identifying the nonlinear dynamics of a multimachine power system and UPFC, one neuroidentifier for the shunt inverter and another for the series inverter. Simulation results carried out in the PSCAD/EMTDC environments on multimachine power system are …