Title

Novel Optimal Neurocontrol for a Synchronous Generator Using Radial Basis Function Neural Network

Abstract

This paper presents the design of an infinite horizon optimal neurocontroller to replace the conventional controllers such as the automatic voltage regulator and governor for the control of a synchronous generator connected to an electric power grid. The neurocontroller design uses the dual heuristic programming (DHP) algorithm, which provides the most robust control capability among the adaptive critic designs (ACDs) family. The radial basis function neural network (RBFNN) is used as the function approximator to implement the DHP. The performances of the proposed optimal neurocontroller are evaluated and its stability issue in real-time operation is analyzed.

Department(s)

Electrical and Computer Engineering

Keywords and Phrases

Dual Heuristic Programming; Optimal Control; Radial Basis Function Neural Network

Library of Congress Subject Headings

Synchronous generators

Document Type

Article - Conference proceedings

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2003 Elsevier, All rights reserved.

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