Open Access. Powered by Scholars. Published by Universities.®
Physical Sciences and Mathematics Commons™
Open Access. Powered by Scholars. Published by Universities.®
Missouri University of Science and Technology
Electrical and Computer Engineering Faculty Research & Creative Works
- Discipline
- Keyword
-
- Neurocontrollers (14)
- Adaptive Control (11)
- Closed Loop Systems (10)
- Lyapunov Methods (10)
- Nonlinear Control Systems (8)
-
- Control System Synthesis (6)
- Lifelong learning (6)
- Neural Networks (6)
- Power System Control (6)
- Discrete-time systems (5)
- Learning (Artificial Intelligence) (5)
- Melanoma (5)
- Power System Stability (5)
- Wireless Sensor Networks (5)
- Clustering (4)
- Decentralized Control (4)
- Dermoscopy (4)
- Discrete Time Systems (4)
- Lyapunov Method (4)
- Neural Network (4)
- Observers (4)
- Optimal Control (4)
- Power Control (4)
- Access Protocols (3)
- Control Nonlinearities (3)
- Distributed Power Control (3)
- Experience replay (3)
- FACTS (3)
- Feedback (3)
- Kinematic/Dynamic Controller (3)
Articles 31 - 60 of 124
Full-Text Articles in Physical Sciences and Mathematics
Real Time Mission Planning, Emad William Saad, Stefan Richard Bieniawski, Paul Edward Riley Pigg, John Lyle Vian, Paul Michael Robinette, Donald C. Wunsch
Real Time Mission Planning, Emad William Saad, Stefan Richard Bieniawski, Paul Edward Riley Pigg, John Lyle Vian, Paul Michael Robinette, Donald C. Wunsch
Electrical and Computer Engineering Faculty Research & Creative Works
The different advantageous embodiments provide a system comprising a number of computers, a graphical user interface, first program code stored on the computer, and second program code stored on the computer. The graphical user interface is executed by a computer in the number of computers. The computer is configured to run the first program code to define a mission using a number of mission elements. The computer is configured to run the second program code to generate instructions for a number of assets to execute the mission and monitor the number of assets during execution of the mission.
Preface, Gennady Fridman, Jeremy Levesley, Ivan Tyukin, Donald C. Wunsch
Preface, Gennady Fridman, Jeremy Levesley, Ivan Tyukin, Donald C. Wunsch
Electrical and Computer Engineering Faculty Research & Creative Works
In August 2014 a conference on “Model reduction across disciplines” was held in Leicester, UK. As a scientific field, model reduction is an important part of mathematical modelling and data analysis with very wide areas of applications. The main scientific goal of the conference was to facilitate interdisciplinary discussion of model reduction and coarse-graining methodologies in order to reveal their general mathematical nature. This time, however, the conference had an additional personal and more profound mission – it was dedicated to the 60th birthday of Professor Alexander Gorban (albeit with some delay) whose fantastic achievements in applying model reduction techniques …
Methods And Systems For Biclustering Algorithm, Donald C. Wunsch, Rui Xu, Sejun Kim
Methods And Systems For Biclustering Algorithm, Donald C. Wunsch, Rui Xu, Sejun Kim
Electrical and Computer Engineering Faculty Research & Creative Works
Methods and systems for improved unsupervised learning are described. The unsupervised learning can consist of biclustering a data set, e.g., by biclustering subsets of the entire data set. In an example, the biclustering does not include feeding know and proven results into the biclustering methodology or system. A hierarchical approach can be used that feeds proven clusters back into the biclustering methodology or system as the input. Data that does not cluster may be discarded. Thus, a very large unknown data set can be acted on to learn about the data. The system is also amenable to parallelization.
Systems, Methods And Devices For Vector Control Of Permanent Magnet Synchronous Machines Using Artificial Neural Networks, Shuhui Li, Michael Fairbank, Xingang Fu, Donald C. Wunsch, Eduardo Alonso
Systems, Methods And Devices For Vector Control Of Permanent Magnet Synchronous Machines Using Artificial Neural Networks, Shuhui Li, Michael Fairbank, Xingang Fu, Donald C. Wunsch, Eduardo Alonso
Electrical and Computer Engineering Faculty Research & Creative Works
An example method for controlling an AC electrical machine can include providing a PWM converter operably connected between an electrical power source and the AC electrical machine and providing a neural network vector control system operably connected to the PWM converter. The control system can include a current-loop neural network configured to receive a plurality of inputs. The current-loop neural network can be configured to optimize the compensating dq-control voltage. The inputs can be d- and q-axis currents, d- and q-axis error signals, predicted d- and q-axis current signals, and a feedback compensating dq-control voltage. The d- and q-axis error …
Big Data -- A 21st Century Science Maginot Line? No-Boundary Thinking: Shifting From The Big Data Paradigm, Xiuzhen Huang, Steven F. Jennings, Barry Bruce, Alison Buchan, Liming Cai, Pengyin Chen, Carole Cramer, Weihua Guan, Uwe Kk Hilgert, Hongmei Jiang, Zenglu Li, Gail Mcclure, Donald F. Mcmullen, Bindu Nanduri, Andy Perkins, Bhanu Rekepalli, Saeed Salem, Jennifer Specker, Karl Walker, Donald C. Wunsch, Donghai Xiong, Shuzhong Zhang, Yu Zhang, Zhongming Zhao, Jason H. Moore
Big Data -- A 21st Century Science Maginot Line? No-Boundary Thinking: Shifting From The Big Data Paradigm, Xiuzhen Huang, Steven F. Jennings, Barry Bruce, Alison Buchan, Liming Cai, Pengyin Chen, Carole Cramer, Weihua Guan, Uwe Kk Hilgert, Hongmei Jiang, Zenglu Li, Gail Mcclure, Donald F. Mcmullen, Bindu Nanduri, Andy Perkins, Bhanu Rekepalli, Saeed Salem, Jennifer Specker, Karl Walker, Donald C. Wunsch, Donghai Xiong, Shuzhong Zhang, Yu Zhang, Zhongming Zhao, Jason H. Moore
Electrical and Computer Engineering Faculty Research & Creative Works
Whether your interests lie in scientific arenas, the corporate world, or in government, you have certainly heard the praises of big data: Big data will give you new insights, allow you to become more efficient, and/or will solve your problems. While big data has had some outstanding successes, many are now beginning to see that it is not the Silver Bullet that it has been touted to be. Here our main concern is the overall impact of big data; the current manifestation of big data is constructing a Maginot Line in science in the 21st century. Big data is not …
Vehicle Base Station, Emad William Saad, John L. Vian, Matthew A. Vavrina, Jared A. Nisbett, Donald C. Wunsch
Vehicle Base Station, Emad William Saad, John L. Vian, Matthew A. Vavrina, Jared A. Nisbett, Donald C. Wunsch
Electrical and Computer Engineering Faculty Research & Creative Works
A system to load and unload material from a vehicle comprises a vehicle base station and an assembly to autonomously load and unload material from the vehicle.
Hidden Markov Model With Information Criteria Clustering And Extreme Learning Machine Regression For Wind Forecasting, Dao Lam, Shuhui Li, Donald C. Wunsch
Hidden Markov Model With Information Criteria Clustering And Extreme Learning Machine Regression For Wind Forecasting, Dao Lam, Shuhui Li, Donald C. Wunsch
Electrical and Computer Engineering Faculty Research & Creative Works
This paper proposes a procedural pipeline for wind forecasting based on clustering and regression. First, the data are clustered into groups sharing similar dynamic properties. Then, data in the same cluster are used to train the neural network that predicts wind speed. For clustering, a hidden Markov model (HMM) and the modified Bayesian information criteria (BIC) are incorporated in a new method of clustering time series data. to forecast wind, a new method for wind time series data forecasting is developed based on the extreme learning machine (ELM). the clustering results improve the accuracy of the proposed method of wind …
Adaptive Resonance Theory And Diffusion Maps For Clustering Applications In Pattern Analysis, Donald C. Wunsch, David J. Morris, Rui Xu
Adaptive Resonance Theory And Diffusion Maps For Clustering Applications In Pattern Analysis, Donald C. Wunsch, David J. Morris, Rui Xu
Electrical and Computer Engineering Faculty Research & Creative Works
Adaptive Resonance is primarily a theory that learning is regulated by resonance phenomena in neural circuits. Diffusion maps are a class of kernel methods on edge-weighted graphs. While either of these approaches have demonstrated success in image analysis, their combination is particularly effective. These techniques are reviewed and some example applications are given.
Decentralized State Feedback And Near Optimal Adaptive Neural Network Control Of Interconnected Nonlinear Discrete-Time Systems, Shahab Mehraeen, Jagannathan Sarangapani, Mariesa Crow
Decentralized State Feedback And Near Optimal Adaptive Neural Network Control Of Interconnected Nonlinear Discrete-Time Systems, Shahab Mehraeen, Jagannathan Sarangapani, Mariesa Crow
Electrical and Computer Engineering Faculty Research & Creative Works
In this paper, first a novel decentralized state feedback stabilization controller is introduced for a class of nonlinear interconnected discrete-time systems in affine form with unknown subsystem dynamics, control gain matrix, and interconnection dynamics by employing neural networks (NNs). Subsequently, the optimal control problem of decentralized nonlinear discrete-time system is considered with unknown internal subsystem and interconnection dynamics while assuming that the control gain matrix is known. For the near optimal controller development, the direct neural dynamic programming technique is utilized to solve the Hamilton-Jacobi-Bellman (HJB) equation forward-in-time. The decentralized optimal controller design for each subsystem utilizes the critic-actor structure …
A Novel Real-Time Approach To Unified Power Flow Controller Validation, Keyou Wang, Mariesa Crow, Bruce M. Mcmillin, Stan Atcitty
A Novel Real-Time Approach To Unified Power Flow Controller Validation, Keyou Wang, Mariesa Crow, Bruce M. Mcmillin, Stan Atcitty
Electrical and Computer Engineering Faculty Research & Creative Works
This paper presents the development of a real-time hardware/software laboratory to interface a soft real-time power system simulator with multiple unified power flow controllers (UPFC) via hardware-in-the-loop (HIL) to study their dynamic responses and validate control and placement approaches. This paper describes a unique laboratory facility that enables large-scale, soft real-time power system simulation coupled with the true physical behavior of a UPFC as opposed to the controller response captured by many other real-time simulators. The HIL line includes a synchronous machine, a UPFC, and a programmable load to reproduce the physical dynamics of the UPFC sub-network.
Nonlinear Control Of Facts Controllers For Damping Interarea Oscillations In Power Systems, Mahyar Zarghami, Jagannathan Sarangapani, Mariesa Crow
Nonlinear Control Of Facts Controllers For Damping Interarea Oscillations In Power Systems, Mahyar Zarghami, Jagannathan Sarangapani, Mariesa Crow
Electrical and Computer Engineering Faculty Research & Creative Works
This paper introduces a new nonlinear control of flexible ac transmission systems (FACTS) controllers for the purpose of damping interarea oscillations in power systems. FACTS controllers consist of series, shunt, or a combination of series-shunt devices which are interfaced with the bulk power system through injection buses. Controlling the angle of these buses can effectively damp low frequency interarea oscillations in the system. The proposed control method is based on finding an equivalent reduced affine nonlinear system for the network from which the dominant machines are extracted based on dynamic coherency. It is shown that if properly selected, measurements obtained …
Design Of A Conditioner For Smoothing Wind Turbine Output Power, Murali Bottu, Mariesa Crow, A. Curt Elmore
Design Of A Conditioner For Smoothing Wind Turbine Output Power, Murali Bottu, Mariesa Crow, A. Curt Elmore
Electrical and Computer Engineering Faculty Research & Creative Works
As a result of wind speed intermittency, highly variable wind power output can adversely impact local loads. We propose a conditioner to smooth the variable wind power by utilizing the energy of an ultracapacitor. The conditioner is based on a single phase voltage source inverter (VSI) connected between the grid interconnection point and the ultracapacitor. The shunt VSI injects or absorbs active power from the line to smooth the wind power by utilizing the short term storage capabilities of the ultracapacitor. The ultracapacitor is connected to the DC link through a DC-DC converter, which maintains the voltage of the DC …
A Novel Approach To Interarea Oscillation Damping By Unified Power Flow Controllers Utilizing Ultracapacitors, Mahyar Zarghami, Mariesa Crow, Jagannathan Sarangapani, Yilu Liu, Stan Atcitty
A Novel Approach To Interarea Oscillation Damping By Unified Power Flow Controllers Utilizing Ultracapacitors, Mahyar Zarghami, Mariesa Crow, Jagannathan Sarangapani, Yilu Liu, Stan Atcitty
Electrical and Computer Engineering Faculty Research & Creative Works
This paper discusses a novel approach for damping interarea oscillations in a bulk power network using multiple unified power flow controllers (UPFCs) utilizing ultracapacitors, also known more generally as electrochemical capacitors (ECs). In this paper, a new control is introduced to mitigate interarea oscillations by directly controlling the UPFCs' sending and receiving bus voltages that better utilizes the stored energy in the ECs. The results of this controller are compared with and without ECs. The proposed control provides better interarea oscillation mitigation when applied to multiple UPFCs in the 118-bus IEEE test system.
Novel Dynamic Representation And Control Of Power Systems With Facts Devices, Shahab Mehraeen, Jagannathan Sarangapani, Mariesa Crow
Novel Dynamic Representation And Control Of Power Systems With Facts Devices, Shahab Mehraeen, Jagannathan Sarangapani, Mariesa Crow
Electrical and Computer Engineering Faculty Research & Creative Works
FACTS devices have been shown to be useful in damping power system oscillations. However, in large power systems, the FACTS control design is complex due to the combination of differential and algebraic equations required to model the power system. In this paper, a new method to generate a nonlinear dynamic representation of the power network is introduced to enable more sophisticated control design. Once the new representation is obtained, a back stepping methodology for the UPFC is utilized to mitigate the generator oscillations. Finally, the neural network approximation property is utilized to relax the need for knowledge of the power …
Adaptive Distributed Fair Scheduling For Multiple Channels In Wireless Sensor Networks, Maciej Jan Zawodniok, Jagannathan Sarangapani, Steve Eugene Watkins, James W. Fonda
Adaptive Distributed Fair Scheduling For Multiple Channels In Wireless Sensor Networks, Maciej Jan Zawodniok, Jagannathan Sarangapani, Steve Eugene Watkins, James W. Fonda
Electrical and Computer Engineering Faculty Research & Creative Works
A novel adaptive and distributed fair scheduling (ADFS) scheme for wireless sensor networks (WSN) in the presence of multiple channels (MC-ADFS) is developed. The proposed MC-ADFS increases available network capacity and focuses on quality-of-service (QoS) issues. when nodes access a shared channel, the proposed MC-ADFS allocates the channel bandwidth proportionally to the packet's weight which indicates the priority of the packet's flow. The packets are dynamically assigned to channels based on the packet weight and current channel utilization. The dynamic assignment of channels is facilitated by use of receiver-based allocation and alternative routes. Moreover, MC-ADFS allows the dynamic allocation of …
Reinforcement-Learning-Based Output-Feedback Control Of Nonstrict Nonlinear Discrete-Time Systems With Application To Engine Emission Control, Peter Shih, Brian C. Kaul, Jagannathan Sarangapani, J. A. Drallmeier
Reinforcement-Learning-Based Output-Feedback Control Of Nonstrict Nonlinear Discrete-Time Systems With Application To Engine Emission Control, Peter Shih, 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, which is also referred to as the adaptive-critic NN controller, is developed to deliver the desired tracking performance for a class of nonlinear discrete-time systems expressed in nonstrict feedback form in the presence of bounded and unknown disturbances. The adaptive-critic NN controller consists of an observer, a critic, and two action NNs. The observer estimates the states and output, and the two action NNs provide virtual and actual control inputs to the nonlinear discrete-time system. The critic approximates a certain strategic utility function, and the action NNs minimize the strategic utility …
Reliability Analysis For The Advanced Electric Power Grid: From Cyber Control And Communication To Physical Manifestations Of Failure, Ayman Z. Faza, Sahra Sedigh, Bruce M. Mcmillin
Reliability Analysis For The Advanced Electric Power Grid: From Cyber Control And Communication To Physical Manifestations Of Failure, Ayman Z. Faza, Sahra Sedigh, Bruce M. Mcmillin
Electrical and Computer Engineering Faculty Research & Creative Works
The advanced electric power grid is a cyber-physical system comprised of physical components, such as transmission lines and generators, and a network of embedded systems deployed for their cyber control. The objective of this paper is to qualitatively and quantitatively analyze the reliability of this cyber-physical system. The original contribution of the approach lies in the scope of failures analyzed, which crosses the cyber-physical boundary by investigating physical manifestations of failures in cyber control. As an example of power electronics deployed to enhance and control the operation of the grid, we study Flexible AC Transmission System (FACTS) devices, which are …
Rfid-Based Smart Freezer, Ahmet Soylemezoglu, Maciej Jan Zawodniok, Jagannathan Sarangapani
Rfid-Based Smart Freezer, Ahmet Soylemezoglu, Maciej Jan Zawodniok, Jagannathan Sarangapani
Electrical and Computer Engineering Faculty Research & Creative Works
This paper presents a novel radio-frequency identification (RFID)-based smart freezer using a new inventory-management scheme for extremely low temperature environments. The proposed solution utilizes backpressure inventory control, systematic selection of antenna configuration, and antenna power control. The proposed distributed-inventory-control (DIC) scheme dictates the amount of items transferred through the supply chain. when a high item visibility is ensured, the control scheme maintains the desired level of inventory at each supply-chain echelon. The performance of the DIC scheme is guaranteed using a Lyapunov-based analysis. The proposed RFID antenna-configuration design methodology coupled with locally asymptotically stable distributed power control ensures a 99% …
Dynamic Channel Allocation In Wireless Networks Using Adaptive Learning Automata, Behdis Eslamnour, Maciej Jan Zawodniok, Jagannathan Sarangapani
Dynamic Channel Allocation In Wireless Networks Using Adaptive Learning Automata, Behdis Eslamnour, Maciej Jan Zawodniok, Jagannathan Sarangapani
Electrical and Computer Engineering Faculty Research & Creative Works
The bandwidth utilization of a single channel-based wireless networks decreases due to congestion and interference from other sources and therefore transmission on multiple channels are needed. In this paper, we propose a distributed dynamic channel allocation scheme for wireless networks using adaptive learning automata whose nodes are equipped with single radio interfaces so that a more suitable channel can be selected. The proposed scheme, adaptive pursuit reward-inaction, runs periodically on the nodes, and adaptively finds the suitable channel allocation in order to attain a desired performance. A novel performance index, which takes into account the throughput and the energy consumption, …
A Multi-Interface Multi-Channel Routing (Mmcr) Protocol For Wireless Ad Hoc Networks, Reghu Anguswamy, Maciej Jan Zawodniok, Jagannathan Sarangapani
A Multi-Interface Multi-Channel Routing (Mmcr) Protocol For Wireless Ad Hoc Networks, Reghu Anguswamy, Maciej Jan Zawodniok, Jagannathan Sarangapani
Electrical and Computer Engineering Faculty Research & Creative Works
Multiple non-interfering channels are available in 802.11 and 802.15.4 based wireless networks. Capacity of such channels can be combined to achieve a better performance thus providing a higher quality of service (QoS) than for a single channel network. However, existing routing protocols often are not suited to fully take advantage of these channels. The proposed multi-interface multi-channel routing (MMCR) protocol considers various QoS parameters such as throughput, end-to-end delay, and energy utilization as a single unified cost metric and identifies the route that optimizes the cost metric and balances the traffic among the channels on a per flow basis. Multipoint …
Neural Network Control Of Mobile Robot Formations Using Rise Feedback, Jagannathan Sarangapani, Travis Alan Dierks
Neural Network Control Of Mobile Robot Formations Using Rise Feedback, Jagannathan Sarangapani, Travis Alan Dierks
Electrical and Computer Engineering Faculty Research & Creative Works
In this paper, an asymptotically stable (AS) combined kinematic/torque control law is developed for leader-follower-based formation control using backstepping in order to accommodate the complete dynamics of the robots and the formation, and a neural network (NN) is introduced along with robust integral of the sign of the error feedback to approximate the dynamics of the follower as well as its leader using online weight tuning. It is shown using Lyapunov theory that the errors for the entire formation are as and that the NN weights are bounded as opposed to uniformly ultimately bounded stability which is typical with most …
Generalized Neuron Based Secure Media Access Control Protocol For Wireless Sensor Networks, Raghavendra V. Kulkarni, Ganesh K. Venayagamoorthy, Abhishek V. Thakur, Sanjay Kumar Madria
Generalized Neuron Based Secure Media Access Control Protocol For Wireless Sensor Networks, Raghavendra V. Kulkarni, Ganesh K. Venayagamoorthy, Abhishek V. Thakur, Sanjay Kumar Madria
Electrical and Computer Engineering Faculty Research & Creative Works
Security plays a pivotal role in most applications of wireless sensor networks. It is common to find inadequately secure networks confined only to controlled environments. The issue of security in wireless sensor networks is a hot research topic for over a decade. This paper presents a compact generalized neuron (GN) based medium access protocol that renders a CSMA/CD network secure against denial-of-service attacks launched by adversaries. The GN enhances the security by constantly monitoring multiple parameters that reflect the possibility that an attack is launched by an adversary. Particle swarm optimization, a popular bio-inspired evolutionary-like optimization algorithm is used for …
An Improved Upfc Control For Oscillation Damping, Jagannathan Sarangapani, Mariesa Crow, Jianjun Guo
An Improved Upfc Control For Oscillation Damping, Jagannathan Sarangapani, Mariesa Crow, Jianjun Guo
Electrical and Computer Engineering Faculty Research & Creative Works
This paper proposes a new control approach for a unified power flow controller (UPFC) for power system oscillation damping. This control is simple to implement, yet is valid over a wide range of operating conditions. It is also effective in the presence of multiple modes of oscillation. The proposed control is implemented in several test systems and is compared against a traditional PI control.
Neural Network Output Feedback Control Of A Quadrotor Uav, Jagannathan Sarangapani, Travis Alan Dierks
Neural Network Output Feedback Control Of A Quadrotor Uav, Jagannathan Sarangapani, Travis Alan Dierks
Electrical and Computer Engineering Faculty Research & Creative Works
A neural network (NN) based output feedback controller for a quadrotor unmanned aerial vehicle (UAV) is proposed. The NNs are utilized in the observer and for generating virtual and actual control inputs, respectively, where the NNs learn the nonlinear dynamics of the UAV online including uncertain nonlinear terms like aerodynamic friction and blade flapping. It is shown using Lyapunov theory that the position, orientation, and velocity tracking errors, the virtual control and observer estimation errors, and the NN weight estimation errors for each NN are all semi-globally uniformly ultimately bounded (SGUUB) in the presence of bounded disturbances and NN functional …
Neural-Network-Based State Feedback Control Of A Nonlinear Discrete-Time System In Nonstrict Feedback Form, Pingan He, Jagannathan Sarangapani
Neural-Network-Based State Feedback Control Of A Nonlinear Discrete-Time System In Nonstrict Feedback Form, Pingan He, Jagannathan Sarangapani
Electrical and Computer Engineering Faculty Research & Creative Works
In this paper, a suite of adaptive neural network (NN) controllers is designed to deliver a desired tracking performance for the control of an unknown, second-order, nonlinear discrete-time system expressed in nonstrict feedback form. In the first approach, two feedforward NNs are employed in the controller with tracking error as the feedback variable whereas in the adaptive critic NN architecture, three feedforward NNs are used. In the adaptive critic architecture, two action NNs produce virtual and actual control inputs, respectively, whereas the third critic NN approximates certain strategic utility function and its output is employed for tuning action NN weights …
A Model Based Fault Detection And Prognostic Scheme For Uncertain Nonlinear Discrete-Time Systems, Balaje T. Thumati, Jagannathan Sarangapani
A Model Based Fault Detection And Prognostic Scheme For Uncertain Nonlinear Discrete-Time Systems, Balaje T. Thumati, Jagannathan Sarangapani
Electrical and Computer Engineering Faculty Research & Creative Works
A new fault detection and prognostics (FDP) framework is introduced for uncertain nonlinear discrete time system by using a discrete-time nonlinear estimator which consists of an online approximator. A fault is detected by monitoring the deviation of the system output with that of the estimator output. Prior to the occurrence of the fault, this online approximator learns the system uncertainty. In the event of a fault, the online approximator learns both the system uncertainty and the fault dynamics. A stable parameter update law in discrete-time is developed to tune the parameters of the online approximator. This update law is also …
Novel Dynamic Representation And Control Of Power Networks Embedded With Facts Devices, Shahab Mehraeen, Jagannathan Sarangapani, Mariesa Crow
Novel Dynamic Representation And Control Of Power Networks Embedded With Facts Devices, Shahab Mehraeen, Jagannathan Sarangapani, Mariesa Crow
Electrical and Computer Engineering Faculty Research & Creative Works
FACTS devices have been shown to be powerful in damping power system oscillations caused by faults; however, in the multi machine control using FACTS, the control problem involves solving differential-algebraic equations of a power network which renders the available control schemes ineffective due to heuristic design and lack of know how to incorporate FACTS into the network. A method to generate nonlinear dynamic representation of a power system consisting of differential equations alone with universal power flow controller (UPFC) is introduced since differential equations are typically preferred for controller development. Subsequently, backstepping methodology is utilized to reduce the generator oscillations …
A Model Based Fault Detection Scheme For Nonlinear Multivariable Discrete-Time Systems, Balaje T. Thumati, Jagannathan Sarangapani
A Model Based Fault Detection Scheme For Nonlinear Multivariable Discrete-Time Systems, Balaje T. Thumati, Jagannathan Sarangapani
Electrical and Computer Engineering Faculty Research & Creative Works
In this paper, a novel robust scheme is developed for detecting faults in nonlinear discrete time multi-input and multi-output systems in contrast with the available schemes that are developed in continuous-time. Both state and output faults are addressed by considering separate time profiles. The faults, which could be incipient or abrupt, are modeled using input and output signals of the system. By using nonlinear estimation techniques, the discrete-time system is monitored online. Once a fault is detected, its dynamics are characterized using an online approximator. A stable parameter update law is developed for the online approximator scheme in discrete-time. The …
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.
Optimal Energy-Delay Routing Protocol With Trust Levels For Wireless Ad Hoc Networks, Eyad Taqieddin, Ann K. Miller, Jagannathan Sarangapani
Optimal Energy-Delay Routing Protocol With Trust Levels For Wireless Ad Hoc Networks, Eyad Taqieddin, Ann K. Miller, Jagannathan Sarangapani
Electrical and Computer Engineering Faculty Research & Creative Works
This paper presents the Trust Level Routing (TLR) pro- tocol, an extension of the optimized energy-delay rout- ing (OEDR) protocol, focusing on the integrity, reliability and survivability of the wireless network. TLR is similar to OEDR in that they both are link state routing proto- cols that run in a proactive mode and adopt the concept of multi-point relay (MPR) nodes. However, TLR aims at incorporating trust levels into routing by frequently changing the MPR nodes as well as authenticating the source node and contents of control packets. TLR calcu- lates the link costs based on a composite metric (delay …