Abstract
This paper compares two indirect adaptive neurocontrollers, namely a multilayer perceptron neurocontroller (MLPNC) and a radial basis function neurocontroller (RBFNC) to control a synchronous generator. The different damping and transient performances of two neurocontrollers are compared with those of conventional linear controllers, and analyzed based on the Lyapunov direct method.
Recommended Citation
J. Park et al., "Indirect Adaptive Control for Synchronous Generator: Comparison of MLP/RBF Neural Networks Approach with Lyapunov Stability Analysis," IEEE Transactions on Neural Networks, Institute of Electrical and Electronics Engineers (IEEE), Jan 2004.
The definitive version is available at https://doi.org/10.1109/TNN.2004.824260
Department(s)
Electrical and Computer Engineering
Sponsor(s)
Duke Power Company
National Science Foundation (U.S.)
Keywords and Phrases
Lyapunov Transient Stability Analysis; Indirect Adaptive Control; Multilayer Perceptron Neural Network (MLPN); On-Line Training; Radial Basis Function Neural Network (RBFN); Synchronous generators
International Standard Serial Number (ISSN)
1045-9227
Document Type
Article - Journal
Document Version
Final Version
File Type
text
Language(s)
English
Rights
© 2004 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.
Publication Date
01 Jan 2004
