DocumentCode :
1606197
Title :
Nonlinear multiple models adaptive decoupling PID control based on generalized predictive control
Author :
Wang, Yonggang ; Chai, Tianyou ; Zhai, Lianfei
Author_Institution :
Key Lab. of Process Ind. Autom., Northeastern Univ., Shenyang, China
fYear :
2009
Firstpage :
1079
Lastpage :
1084
Abstract :
A nonlinear multivariable adaptive decoupling PID control strategy based on multiple models and neural network is proposed for a class of uncertain discrete time nonlinear dynamical systems. The adaptive decoupling PID controller is composed of a linear adaptive PID decoupling controller, a neural network nonlinear adaptive PID decoupling controller and a switch mechanism. The PID parameters of such controller are determined by multivariable generalized predictive control law. The linear adaptive PID controller can ensure the boundedness of the input and output signals in the closed-loop system and the nonlinear adaptive PID controller can improve the performance of the system. Stability and convergence analysis of the proposed adaptive method are given. Finally, simulation examples are included to demonstrate the effectiveness of the proposed method.
Keywords :
adaptive control; closed loop systems; control system analysis; discrete time systems; multivariable control systems; neurocontrollers; nonlinear control systems; nonlinear dynamical systems; predictive control; stability; three-term control; uncertain systems; closed-loop system; convergence analysis; generalized predictive control; input-output signal boundedness; multiple model; neural network; nonlinear multivariable model adaptive decoupling PID control; stability analysis; switch mechanism; uncertain discrete time nonlinear dynamical system; Adaptive control; Adaptive systems; Control systems; Neural networks; Nonlinear control systems; Predictive control; Predictive models; Programmable control; Switches; Three-term control;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Asian Control Conference, 2009. ASCC 2009. 7th
Conference_Location :
Hong Kong
Print_ISBN :
978-89-956056-2-2
Electronic_ISBN :
978-89-956056-9-1
Type :
conf
Filename :
5276383
Link To Document :
بازگشت