DocumentCode :
2341327
Title :
Application of self-tuning control to complicated, non-linear system by using neural network
Author :
Liu, Sizing ; Zhou, Zhaoying ; Zhang, Zhongjun
Author_Institution :
Dept. of Precision Instrum., Tsinghua Univ., Beijing, China
fYear :
1994
fDate :
10-12 May 1994
Firstpage :
163
Abstract :
This paper is concerned with building a model of Artificial Neural Network Predictor (ANP) for the self-tuning adaptive system. The learning algorithm of ANN is proposed accompanying with the analysis of its control strategy. Here, it could perhaps provide the active idea to solve such difficulty problem that is about how to use self-tuning algorithm to control the non-linear, complicated system. The results have demonstrated that use of ANP in self-tuning control can provide the better performance than can be achieved using the general strategy
Keywords :
artificial intelligence; control system analysis; control system synthesis; learning (artificial intelligence); neural nets; nonlinear control systems; self-adjusting systems; Artificial Neural Network Predictor; learning algorithm; neural network; nonlinear system; nonlinear, complicated system; self-tuning adaptive system; self-tuning algorithm; self-tuning control; Adaptive control; Adaptive systems; Artificial neural networks; Automatic control; Control systems; Neural networks; Nonlinear control systems; Nonlinear dynamical systems; Optimal control; Performance analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Instrumentation and Measurement Technology Conference, 1994. IMTC/94. Conference Proceedings. 10th Anniversary. Advanced Technologies in I & M., 1994 IEEE
Conference_Location :
Hamamatsu
Print_ISBN :
0-7803-1880-3
Type :
conf
DOI :
10.1109/IMTC.1994.352100
Filename :
352100
Link To Document :
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