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