DocumentCode :
468986
Title :
Adaptive PID decoupling control based on RBF neural network and its application
Author :
Zhang, Ming-Guang ; Wang, Zhao-gang ; Wang, Peng
Author_Institution :
Lanzhou Univ. of Technol., Lanzhou
Volume :
2
fYear :
2007
fDate :
2-4 Nov. 2007
Firstpage :
727
Lastpage :
731
Abstract :
An adaptive PID decoupling control strategy based on Radial Basis Function (RBF) neural network (NN) is presented in this paper for nonlinear multivariable system. Based on the theory of optimization in groups, the parameters such as proportion, integration and differentiation of PID controller are tuned on-line using the self-learning ability of RBFNN. And the corresponding decoupling control law is achieved by conventional PID control algorithm. Simulation results show that the dynamic decoupling and completely static decoupling are obtained, the closed loop system has the advantages of higher speed response and stronger robustness.
Keywords :
adaptive control; multivariable control systems; neurocontrollers; nonlinear control systems; radial basis function networks; three-term control; RBF neural network; adaptive PID decoupling control; closed loop system; nonlinear multivariable system; radial basis function; self-learning ability; Adaptive control; Closed loop systems; Control systems; MIMO; Neural networks; Nonlinear control systems; Nonlinear dynamical systems; Programmable control; Proportional control; Three-term control; Adaptive PID control; RBF neural network; decoupling control; nonlinear system;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Wavelet Analysis and Pattern Recognition, 2007. ICWAPR '07. International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-1065-1
Electronic_ISBN :
978-1-4244-1066-8
Type :
conf
DOI :
10.1109/ICWAPR.2007.4420764
Filename :
4420764
Link To Document :
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