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Electrical and Computer Engineering Faculty Research & Creative Works

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Full-Text Articles in Engineering

Esd Susceptibility Characterization Of An Eut By Using 3d Esd Scanning System, Kai Wang, Jayong Koo, Giorgi Muchaidze, David Pommerenke Jan 2005

Esd Susceptibility Characterization Of An Eut By Using 3d Esd Scanning System, Kai Wang, Jayong Koo, Giorgi Muchaidze, David Pommerenke

Electrical and Computer Engineering Faculty Research & Creative Works

Electrostatic discharges (ESD) can lead to soft-errors (e.g., bit-errors, wrong resets etc.) in digital electronics. The use of lower threshold voltages and faster I/O increases the sensitivity. In the analysis of ESD problems, an exact knowledge of the affected pins and nets is essential for an optimal solution. In this paper, a three dimensional ESD scanning system which has been developed to record the ESD susceptibility map for printed circuit board is presented and the mechanisms that the ESD event couples into the digital devices is studied. The ESD susceptibility of a fast CMOS EUT is characterized by generating the …

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Evolving Combinational Logic Circuits Using A Hybrid Quantum Evolution And Particle Swarm Inspired Algorithm, Phillip W. Moore, Ganesh K. Venayagamoorthy Jan 2005

Evolving Combinational Logic Circuits Using A Hybrid Quantum Evolution And Particle Swarm Inspired Algorithm, Phillip W. Moore, Ganesh K. Venayagamoorthy

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, an algorithm inspired from quantum evolution and particle swarm to evolve combinational logic circuits is presented. This algorithm uses the framework of the local version of particle swarm optimization with quantum evolutionary algorithms, and integer encoding. A multi-objective fitness function is used to evolve the combinational logic circuits in order obtain feasible circuits with minimal number of gates in the design. A comparative study indicates the superior performance of the hybrid quantum evolution-particle swarm inspired algorithm over the particle swarm and other evolutionary algorithms (such as genetic algorithms) independently.

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Hardware Implementation Of A Mamdani Fuzzy Logic Controller For A Static Compensator In A Multimachine Power System, Salman Mohagheghi, Ganesh K. Venayagamoorthy, Satish Rajagopalan, Ronald G. Harley Jan 2005

Hardware Implementation Of A Mamdani Fuzzy Logic Controller For A Static Compensator In A Multimachine Power System, Salman Mohagheghi, Ganesh K. Venayagamoorthy, Satish Rajagopalan, Ronald G. Harley

Electrical and Computer Engineering Faculty Research & Creative Works

A Mamdani based fuzzy logic controller is designed and implemented for controlling a STATCOM, which is connected to a 10 bus multimachine power system. Such a controller does not need any prior knowledge of the plant to be controlled and can efficiently provide control signals for the STATCOM during different disturbances in the network The proposed controller is implemented using the M67 DSP board and is interfaced to the multimachine power system simulated on a real-time digital simulator (RTDS). Experimental results are provided, showing that the proposed controller provides more effective damping than the conventional PI controller in a typical …

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Iterative Equalization Using Improved Block Dfe For Synchronous Cdma Systems, Sang-Yick Leong, Kah-Ping Lee, Y. Rosa Zheng Jan 2005

Iterative Equalization Using Improved Block Dfe For Synchronous Cdma Systems, Sang-Yick Leong, Kah-Ping Lee, Y. Rosa Zheng

Electrical and Computer Engineering Faculty Research & Creative Works

Iterative equalization using optimal multiuser detector and trellis-based channel decoder in coded CDMA systems improves the bit error rate (BER) performance dramatically. However, given large number of users employed in the system over multipath channels causing significant multiple-access interference (MAI) and intersymbol interference (ISI), the optimal multiuser detector is thus prohibitively complex. Therefore, the sub-optimal detectors such as low-complexity linear and non-linear equalizers have to be considered. In this paper, a novel low-complexity block decision feedback equalizer (DFE) is proposed for the synchronous CDMA system. Based on the conventional block DFE, the new method is developed by computing the reliable …

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Effective Strategies For Choosing And Locating Printed Circuit Board Decoupling Capacitors, Todd H. Hubing Jan 2005

Effective Strategies For Choosing And Locating Printed Circuit Board Decoupling Capacitors, Todd H. Hubing

Electrical and Computer Engineering Faculty Research & Creative Works

No abstract provided.

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Effects Of A Statcom, A Scrc And A Upfc On The Dynamic Behavior Of A 45 Bus Section Of The Brazilian Power System, Ganesh K. Venayagamoorthy, Salman Mohagheghi, Wei Qiao, Swakshar Ray, Ronald G. Harley, Djalma M. Falcao, Glauco N. Taranto, Tatiana M. L. Assis, Yamille Del Valle Jan 2005

Effects Of A Statcom, A Scrc And A Upfc On The Dynamic Behavior Of A 45 Bus Section Of The Brazilian Power System, Ganesh K. Venayagamoorthy, Salman Mohagheghi, Wei Qiao, Swakshar Ray, Ronald G. Harley, Djalma M. Falcao, Glauco N. Taranto, Tatiana M. L. Assis, Yamille Del Valle

Electrical and Computer Engineering Faculty Research & Creative Works

No abstract provided.

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Engine Data Classification With Simultaneous Recurrent Network Using A Hybrid Pso-Ea Algorithm, Xindi Cai, Donald C. Wunsch Jan 2005

Engine Data Classification With Simultaneous Recurrent Network Using A Hybrid Pso-Ea Algorithm, Xindi Cai, Donald C. Wunsch

Electrical and Computer Engineering Faculty Research & Creative Works

We applied an architecture which automates the design of simultaneous recurrent network (SRN) using a new evolutionary learning algorithm. This new evolutionary learning algorithm is based on a hybrid of particle swarm optimization (PSO) and evolutionary algorithm (EA). By combining the searching abilities of these two global optimization methods, the evolution of individuals is no longer restricted to be in the same generation, and better performed individuals may produce offspring to replace those with poor performance. The novel algorithm is then applied to the simultaneous recurrent network for the engine data classification. The experimental results show that our approach gives …

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Gene Regulatory Networks Inference With Recurrent Neural Network Models, Rui Xu, Donald C. Wunsch Jan 2005

Gene Regulatory Networks Inference With Recurrent Neural Network Models, Rui Xu, Donald C. Wunsch

Electrical and Computer Engineering Faculty Research & Creative Works

Large-scale time series gene expression data generated from DNA microarray experiments provide us a new means to reveal fundamental cellular processes, investigate functions of genes, and understand their relations and interactions. To infer gene regulatory networks from these data with effective computational tools has attracted intensive efforts from artificial intelligence and machine learning. Here, we use a recurrent neural network (RNN), trained with particle swarm optimization (PSO), to investigate the behaviors of regulatory networks. The experimental results, on a synthetic data set and a real data set, show that the proposed model and algorithm can effectively capture the dynamics of …

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Fuzzy Pso: A Generalization Of Particle Swarm Optimization, S. Abdelshahid, Donald C. Wunsch, Ashraf M. Abdelbar Jan 2005

Fuzzy Pso: A Generalization Of Particle Swarm Optimization, S. Abdelshahid, Donald C. Wunsch, Ashraf M. Abdelbar

Electrical and Computer Engineering Faculty Research & Creative Works

In standard particle swarm optimization (PSO), the best particle in each neighborhood exerts its influence over other particles in the neighborhood. In this paper, we propose fuzzy PSO, a generalization which differs from standard PSO in the following respect: charisma is defined to be a fuzzy variable, and more than one particle in each neighborhood can have a non-zero degree of charisma, and, consequently, is allowed to influence others to a degree that depends on its charisma. We evaluate our model on the weighted maximum satisfiability (maxsat) problem, comparing performance to standard PSO and to Walk-Sat.

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Improving The Performance Of Particle Swarm Optimization Using Adaptive Critics Designs, Ganesh K. Venayagamoorthy, Sheetal Doctor Jan 2005

Improving The Performance Of Particle Swarm Optimization Using Adaptive Critics Designs, Ganesh K. Venayagamoorthy, Sheetal Doctor

Electrical and Computer Engineering Faculty Research & Creative Works

Swarm intelligence algorithms are based on natural behaviors. Particle swarm optimization (PSO) is a stochastic search and optimization tool. Changes in the PSO parameters, namely the inertia weight and the cognitive and social acceleration constants, affect the performance of the search process. This paper presents a novel method to dynamically change the values of these parameters during the search. Adaptive critic design (ACD) has been applied for dynamically changing the values of the PSO parameters.

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Measuring Scalability Of Resource Management Systems, A. Mitra, Muthucumaru Maheswaran, Shoukat Ali Jan 2005

Measuring Scalability Of Resource Management Systems, A. Mitra, Muthucumaru Maheswaran, Shoukat Ali

Electrical and Computer Engineering Faculty Research & Creative Works

Scalability refers to the extent of configuration modifications over which a system continues to be economically deployable. Until now, scalability of resource management systems (RMSs) has been examined implicitly by studying different performance measures of the RMS designs for different parameters. However, a framework is yet to be developed for quantitatively evaluating scalability to unambiguously examine the trade-offs among the different RMS designs. In this paper, we present a methodology to study scalability of RMSs based on overhead cost estimation. First, we present a performance model for a managed distributed system (e.g., Grid computing system) that separates the manager and …

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Multiuser Channel Estimation For Cdma Systems Over Frequency-Selective Fading Channels, Jingxian Wu, Chengshan Xiao, Khaled Ben Letaief Jan 2005

Multiuser Channel Estimation For Cdma Systems Over Frequency-Selective Fading Channels, Jingxian Wu, Chengshan Xiao, Khaled Ben Letaief

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, a pilot-assisted minimum mean square error (MMSE) multiuser channel estimation algorithm is proposed for quasi-synchronous code-division multiple-access (CDMA) systems that undergo frequency-selective channel fading. The frequency-selective multiuser fading channel is represented as a symbol-wise time-varying chip-spaced tapped delay line filter with correlated filter taps. The multiuser channel tap coefficients at pilot symbol positions are estimated under the MMSE criterion with the help of the channel intertap correlation matrix, which is determined by the combined effects of the physical fading channel, transmit filter, and receive filter. In the development of the estimation algorithm, the channel intertap correlation matrix …

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Negative Reinforcement And Backtrack-Points For Recurrent Neural Networks For Cost-Based Abduction, Donald C. Wunsch, Ashraf M. Abdelbar, M. A. El-Hemaly, Emad A. M. Andrews Jan 2005

Negative Reinforcement And Backtrack-Points For Recurrent Neural Networks For Cost-Based Abduction, Donald C. Wunsch, Ashraf M. Abdelbar, M. A. El-Hemaly, Emad A. M. Andrews

Electrical and Computer Engineering Faculty Research & Creative Works

Abduction is the process of proceeding from data describing a set of observations or events, to a set of hypotheses which best explains or accounts for the data. Cost-based abduction (CKA) is an AI formalism in which evidence to be explained is treated as a goal to be proven, proofs have costs based on how much needs to be assumed to complete the proof, and the set of assumptions needed to complete the least-cost proof are taken as the best explanation for the given evidence. In this paper, we introduce two techniques for improving the performance of high order recurrent …

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Neural Network-Based Control Of Nonlinear Discrete-Time Systems In Non-Strict Form, Jagannathan Sarangapani, Zheng Chen, Pingan He Jan 2005

Neural Network-Based Control Of Nonlinear Discrete-Time Systems In Non-Strict Form, Jagannathan Sarangapani, Zheng Chen, Pingan He

Electrical and Computer Engineering Faculty Research & Creative Works

A novel reinforcement learning-based adaptive neural network (NN) controller, also referred as the adaptive-critic NN controller, is developed to deliver a desired tracking performance for a class of non-strict feedback nonlinear discrete-time systems in the presence of bounded and unknown disturbances. The adaptive critic NN controller architecture includes a critic NN and two action NNs. The critic NN approximates certain strategic utility function whereas the action neural networks are used to minimize both the strategic utility function and the unknown dynamics estimation errors. The NN weights are tuned online so as to minimize certain performance index. By using gradient descent-based …

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Power System Optimization And Coordination Of Damping Controls By Series Facts Devices, Jung-Wook Park, Ganesh K. Venayagamoorthy, Ronald G. Harley Jan 2005

Power System Optimization And Coordination Of Damping Controls By Series Facts Devices, Jung-Wook Park, Ganesh K. Venayagamoorthy, Ronald G. Harley

Electrical and Computer Engineering Faculty Research & Creative Works

No abstract provided.

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Calibration And Compensation Of Near-Field Scan Measurements, Masahiro Yamaguchi, Richard E. Dubroff, Kevin P. Slattery, Michael A. Cracraft, Jin Shi Jan 2005

Calibration And Compensation Of Near-Field Scan Measurements, Masahiro Yamaguchi, Richard E. Dubroff, Kevin P. Slattery, Michael A. Cracraft, Jin Shi

Electrical and Computer Engineering Faculty Research & Creative Works

A procedure for the calibration and compensation of near-field scanning is described and demonstrated. Ultimately, the objective is to quantify the individual field components associated with electromagnetic interference (EMI) from high speed circuitry and devices. Specific examples of these methods are shown. The effects of compensation are small but noticeable when the uncompensated output signal from near field scanning is already a very good representation of the field being measured. In other cases, the improvement provided by compensation can be significant when the uncompensated output signal bears little resemblance to the underlying field.

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Modulation Of Millimeter Waves By Acoustically Controlled Hexagonal Ferrite Resonator, Marina Koledintseva, Alexander A. Kitaytsev Jan 2005

Modulation Of Millimeter Waves By Acoustically Controlled Hexagonal Ferrite Resonator, Marina Koledintseva, Alexander A. Kitaytsev

Electrical and Computer Engineering Faculty Research & Creative Works

To develop millimeter-wave modulators, high-anisotropy uniaxial monocrystalline hexagonal ferrite resonators (HFRs) can be used. One of the ways to modulate the hexagonal ferrite resonator's resonance frequency is to periodically vary the angle between the equilibrium magnetic moment and the external magnetization field. This angular control can be exercised by the mechanical (acoustic) oscillations excited in a piezoelectric slab having a good acoustic contact with the HFR. We consider a quasi-static mathematical model of the uniaxial HFR with the angular control of its resonance frequency. We analyze the amplitudes of harmonics of the modulated millimeter-wave signal, and we derive the optimal …

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Derivation Of A Closed-Form Approximate Expression For The Self-Capacitance Of A Printed Circuit Board Trace, Todd H. Hubing, Hwan-Woo Shim Jan 2005

Derivation Of A Closed-Form Approximate Expression For The Self-Capacitance Of A Printed Circuit Board Trace, Todd H. Hubing, Hwan-Woo Shim

Electrical and Computer Engineering Faculty Research & Creative Works

The electric fields that couple traces on printed circuit boards to attached cables can generate common-mode currents that result in significant radiated emissions. Previous work has shown that these radiated emissions can be estimated based on the self-capacitances of the microstrip structures on a board . In general, the determination of these self-capacitances must be done numerically using three-dimensional static modeling software. In this paper, an approximate closed-form expression for the self-capacitance of microstrip traces is derived. This expression can be used to estimate the voltage-driven common-mode emissions from boards with various microstrip trace geometries. The expression also provides insight …

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Genetic Algorithms Based Economic Dispatch With Application To Coordination Of Nigerian Thermal Power Plants, Ganesh K. Venayagamoorthy, G. A. Bakare, U. O. Aliyu, Y. K. Shu'aibu Jan 2005

Genetic Algorithms Based Economic Dispatch With Application To Coordination Of Nigerian Thermal Power Plants, Ganesh K. Venayagamoorthy, G. A. Bakare, U. O. Aliyu, Y. K. Shu'aibu

Electrical and Computer Engineering Faculty Research & Creative Works

The main focus of this paper is on the application of genetic algorithm (GA) to search for an optimal solution to a realistically formulated economic dispatch (ED) problem. GA is a global search technique based on principles inspired from the genetic and evolution mechanism observed in natural biological systems. A major drawback of the conventional GA (CGA) approach is that it can be time consuming. The micro-GA (µGA) approach has been proposed as a better time efficient alternative for some engineering problems. The effectiveness of CGA and µGA. to solving ED problem is initially verified on an IEEE 3-generating unit, …

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Mlp/Rbf Neural-Networks-Based Online Global Model Identification Of Synchronous Generator, Jung-Wook Park, Ganesh K. Venayagamoorthy, Ronald G. Harley Jan 2005

Mlp/Rbf Neural-Networks-Based Online Global Model Identification Of Synchronous Generator, Jung-Wook Park, Ganesh K. Venayagamoorthy, Ronald G. Harley

Electrical and Computer Engineering Faculty Research & Creative Works

This paper compares the performances of a multilayer perceptron neural network (MLPN) and a radial basis function neural network (RBFN) for online identification of the nonlinear dynamics of a synchronous generator in a power system. The computational requirement to process the data during the online training, local convergence, and online global convergence properties are investigated by time-domain simulations. The performances of the identifiers as a global model, which are trained at different stable operating conditions, are compared using the actual signals as well as the deviation signals for the inputs of the identifiers. Such an online-trained identifier with fixed optimal …

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Model For Estimating Radiated Emissions From A Printed Circuit Board With Attached Cables Due To Voltage-Driven Sources, Todd H. Hubing, Hwan-Woo Shim Jan 2005

Model For Estimating Radiated Emissions From A Printed Circuit Board With Attached Cables Due To Voltage-Driven Sources, Todd H. Hubing, Hwan-Woo Shim

Electrical and Computer Engineering Faculty Research & Creative Works

Common-mode currents induced on cables attached to printed circuit boards (PCBs) can be a significant source of unintentional radiated emissions. This paper develops a model for estimating the amount of common-mode cable current that can be induced by the signal voltage on microstrip trace structures or heatsinks on a PCB. The model employs static electric field solvers or closed-form expressions to estimate the effective self-capacitances of the board, trace, and/or heatsink. These capacitances are then used to determine the amplitude of an equivalent common-mode voltage source that drives the attached cables. The model shows that these voltage-driven common-mode cable currents …

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Robust Resource Allocations In Parallel Computing Systems: Model And Heuristics, V. Shestak, Shoukat Ali, Howard Jay Siegel, A. A. Maciejewski Jan 2005

Robust Resource Allocations In Parallel Computing Systems: Model And Heuristics, V. Shestak, Shoukat Ali, Howard Jay Siegel, A. A. Maciejewski

Electrical and Computer Engineering Faculty Research & Creative Works

The resources in parallel computer systems (including heterogeneous clusters) should be allocated to the computational applications in a way that maximizes some system performance measure. However, allocation decisions and associated performance prediction are often based on estimated values of application and system parameters. The actual values of these parameters may differ from the estimates; for example, the estimates may represent only average values, the models used to generate the estimates may have limited accuracy, and there may be changes in the environment. Thus, an important research problem is the development of resource management strategies that can guarantee a particular system …

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Simulation-Based Performance Modeling For War Fighter In Loop Minefield Detection System, Abhilash Rajagopal, Sanjeev Agarwal, Sreeram Ramakrishnan Jan 2005

Simulation-Based Performance Modeling For War Fighter In Loop Minefield Detection System, Abhilash Rajagopal, Sanjeev Agarwal, Sreeram Ramakrishnan

Electrical and Computer Engineering Faculty Research & Creative Works

No abstract provided.

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Using An Lu Recombination Method To Improve The Performance Of The Boundary Element Method At Very Low Frequencies, Haixin Ke, Todd H. Hubing Jan 2005

Using An Lu Recombination Method To Improve The Performance Of The Boundary Element Method At Very Low Frequencies, Haixin Ke, Todd H. Hubing

Electrical and Computer Engineering Faculty Research & Creative Works

Many numerical electromagnetic modeling techniques that work very well at high frequencies do not work well at lower frequencies. This is directly or indirectly due to the weak coupling between the electric and magnetic fields at low frequencies. One technique for improving the performance of boundary element techniques at low frequencies is through the use of loop-tree basis functions, which decouple the contributions from the vector and scalar electric potential. However, loop-tree basis functions can be difficult to define for large, complex geometries. This paper describes a new method for improving the low-frequency performance of boundary element techniques. The proposed …

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Wide Area Power System Protection Using A Learning Vector Quantization Network, Ganesh K. Venayagamoorthy, Mahyar Zarghami Jan 2005

Wide Area Power System Protection Using A Learning Vector Quantization Network, Ganesh K. Venayagamoorthy, Mahyar Zarghami

Electrical and Computer Engineering Faculty Research & Creative Works

This paper presents a wide area monitoring and protection technique based on a learning vector quantization (LVQ) neural network. Phasor measurements of the power network buses are monitored continuously by a LVQ network in order to alert the control room operators of possible faults. The proposed scheme could be used in a wide area monitored network to provide remedial action when primary local protection schemes for transmission lines fail to function. This technique could also be extended to the actuation of the secondary protection schemes, hence, preserving the integrity of the power network especially when the faults are spreading over …

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A Dynamic Recurrent Neural Network For Wide Area Identification Of A Multimachine Power System With A Facts Device, Salman Mohagheghi, Ganesh K. Venayagamoorthy, Ronald G. Harley Jan 2005

A Dynamic Recurrent Neural Network For Wide Area Identification Of A Multimachine Power System With A Facts Device, Salman Mohagheghi, Ganesh K. Venayagamoorthy, Ronald G. Harley

Electrical and Computer Engineering Faculty Research & Creative Works

Multilayer perceptron and radial basis function neural networks have been traditionally used for plant identification in power systems applications of neural networks. While being efficient in tracking the plant dynamics in a relatively small system, their performance degrades as the dimensions of the plant to be identified are increased, for example in supervisory level identification of a multimachine power system for wide area control purposes. Recurrent neural networks can deal with such a problem by modeling the system as a set of differential equations and with less order of complexity. Such a recurrent neural network identifier is designed and implemented …

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A Measure Of Robustness Against Multiple Kinds Of Perturbations, Shoukat Ali, Behdis Eslamnour Jan 2005

A Measure Of Robustness Against Multiple Kinds Of Perturbations, Shoukat Ali, Behdis Eslamnour

Electrical and Computer Engineering Faculty Research & Creative Works

Parallel and distributed heterogeneous computing systems may operate in an environment that undergoes unpredictable changes causing certain system performance features to degrade. Such systems need robustness to guarantee limited degradation despite fluctuations in the behavior of its component parts or environment. Our previous work in this area presented a method for generating a measure of robustness for a given system. However, the focus of that approach was on a scenario where all perturbations were of the same kind, e.g., all perturbations were in message sizes or computation times, but not both message sizes and computation times. This paper gives an …

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A Neural Network Based Optimal Wide Area Control Scheme For A Power System, Ganesh K. Venayagamoorthy, Swakshar Ray Jan 2005

A Neural Network Based Optimal Wide Area Control Scheme For A Power System, Ganesh K. Venayagamoorthy, Swakshar Ray

Electrical and Computer Engineering Faculty Research & Creative Works

With deregulation of the power industry, many tie lines between control areas are driven to operate near their maximum capacity, especially those serving heavy load centers. Wide area control systems (WACSs) using wide-area or global signals can provide remote auxiliary control signals to local controllers such as automatic voltage regulators, power system stabilizers, etc to damp out inter-area oscillations. This paper presents the design and the DSP implementation of a nonlinear optimal wide area controller based on adaptive critic designs and neural networks for a power system on the real-time digital simulator (RTDS©). The performance of the WACS as a …

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A Neural Network Based Wide Area Monitor For A Power System, Xiaomeng Li, Ganesh K. Venayagamoorthy Jan 2005

A Neural Network Based Wide Area Monitor For A Power System, Xiaomeng Li, Ganesh K. Venayagamoorthy

Electrical and Computer Engineering Faculty Research & Creative Works

With the deregulation of power industry, many tie lines between control areas are driven to operate near their maximum capacity, especially those serving heavy load centers. Wide area controllers (WACs) using wide-area or global signals can provide remote auxiliary control signals to local controllers such as automatic voltage regulators, power system stabilizers, etc to damp out inter-area oscillations. The power system is highly nonlinear system with fast changing dynamics. In order to have an efficient WAC, an online system monitor/predictor is required to provide inter-area information to the WAC from time to time. This paper presents the design of an …

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A New Microsensor System For Plant Root Zone Monitoring, Chang-Soo Kim, Sandeep Sathyan, D. M. Porterfield Jan 2005

A New Microsensor System For Plant Root Zone Monitoring, Chang-Soo Kim, Sandeep Sathyan, D. M. Porterfield

Electrical and Computer Engineering Faculty Research & Creative Works

The objective of this work is to develop a new microsensor system that can monitor dissolved oxygen and hydration environment at the plant root zone. A miniaturized plant growth system is prepared including the root zone layer, either a porous ceramic tube or porous ceramic wafer on which the plant is grown, and an underlying fluidic channel to deliver nutrients and water to the root zone. We demonstrate the feasibility of using a flexible microsensor array for dissolved oxygen detection, and a four-electrode impedance microelectrode for wetness detection on the surface of a porous tube nutrient delivery system. The unique …

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