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Engineering Commons

Open Access. Powered by Scholars. Published by Universities.®

1999

Missouri University of Science and Technology

Control System Analysis

Articles 1 - 3 of 3

Full-Text Articles in Engineering

Neurocontrol Of Turbogenerators With Adaptive Critic Designs, Ganesh K. Venayagamoorthy, Donald C. Wunsch, Ronald G. Harley Jan 1999

Neurocontrol Of Turbogenerators With Adaptive Critic Designs, Ganesh K. Venayagamoorthy, Donald C. Wunsch, Ronald G. Harley

Electrical and Computer Engineering Faculty Research & Creative Works

This paper presents the design of a neuro-controller for a turbogenerator using a novel technique based on adaptive critic designs (ACD). This adaptive critic design based neuro-controller augments/replaces the traditional automatic voltage regulator (AVR) and the turbine governor of the generator. Simulation results are presented to show that neural network controllers with the ACD have the potential to control turbogenerators when system conditions and configuration changes.


A Robust Artificial Neural Network Controller For A Turbogenerator When Line Configuration Changes, Ganesh K. Venayagamoorthy, Ronald G. Harley Jan 1999

A Robust Artificial Neural Network Controller For A Turbogenerator When Line Configuration Changes, Ganesh K. Venayagamoorthy, Ronald G. Harley

Electrical and Computer Engineering Faculty Research & Creative Works

This paper presents the design of a robust controller for a turbogenerator. The robust controller is an artificial neural network (ANN) that is trained offline on a family of ANN models of the turbogenerator. This ANN controller augments/replaces the traditional automatic voltage controller (AVR) and the turbine governor of the generator. Simulation results are presented to show that the ANN controller is robust when the transmission line configuration changes.


A Continually Online Trained Artificial Neural Network Identifier For A Turbogenerator, Ganesh K. Venayagamoorthy, Ronald G. Harley Jan 1999

A Continually Online Trained Artificial Neural Network Identifier For A Turbogenerator, Ganesh K. Venayagamoorthy, Ronald G. Harley

Electrical and Computer Engineering Faculty Research & Creative Works

The increasing complexity of modern power systems highlights the need for advanced modelling techniques for effective control of power systems. This paper presents results of simulation and practical studies carried out on identifying the dynamics of a single turbogenerator connected to an infinite bus through a short transmission line, using a continually online trained (COT) artificial neural network (ANN).