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
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