Experimental study of SPSA approach to intelligent control systems

Experimental study of SPSA approach to intelligent control systems

Simultaneous perturbation stochastic approximation (SPSA) approach is a general approximate method to estimate the gradient of system performance function. The neural network-based SPSA does not need a priori knowledge of the plant. A direct adaptive SPSA control system with a diagonal recurrent neu...

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Bibliographic Details
Published in:Conference proceedings - Canadian Conference on Electrical and Computer Engineering Vol. 2; pp. 558 - 561 vol.2
Main Authors: Xiao D. Ji, Familoni, B.O.
Format: Conference Proceeding Journal Article
Language:English
Published: IEEE 1996
Subjects:
Adaptive control
Adaptive systems
Control systems
Fuzzy control
Fuzzy neural networks
Intelligent control
Neural networks
Programmable control
Stochastic systems
System performance
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Summary:Simultaneous perturbation stochastic approximation (SPSA) approach is a general approximate method to estimate the gradient of system performance function. The neural network-based SPSA does not need a priori knowledge of the plant. A direct adaptive SPSA control system with a diagonal recurrent neural network as controller was examined by simulation. To improve the system performance, a conventional PID controller was used as compensator to form a hybrid scheme. Applying the SPSA approach to a fuzzy neural network-based control (FNNC) system, a four-layer neural network architecture was proposed to implement the hybrid SPSA FNNC scheme. Simulation results are presented.
Bibliography:SourceType-Scholarly Journals-2
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ISBN:9780780331433
0780331435
ISSN:0840-7789
2576-7046
DOI:10.1109/CCECE.1996.548214