Title :
Nonlinear indirect adaptive decoupling control based on neural networks and multiple models
Author :
Fu, Yue ; Chai, Tianyou ; Wang, Hong
Author_Institution :
Res. Center of Autom., Northeastern Univ.
Abstract :
In this paper, an indirect adaptive decoupling controller is presented for a class of uncertain nonlinear multivariable discrete time dynamical systems. The indirect adaptive decoupling controller is composed of a linear robust indirect adaptive decoupling controller, a neural network nonlinear indirect adaptive decoupling controller and a switching mechanism. The linear decoupling controller can provide boundedness of the input and output signals, and the nonlinear decoupling controller can improve performance of the system. The purpose of using the switching mechanism is to obtain the improved system performance and stability simultaneously. Theory analysis and simulation results are presented to show the effectiveness of the proposed method
Keywords :
adaptive control; discrete time systems; multivariable control systems; neurocontrollers; nonlinear control systems; nonlinear dynamical systems; stability; uncertain systems; neural networks; nonlinear indirect adaptive decoupling control; stability; switching mechanism; uncertain nonlinear multivariable discrete time dynamical systems; Adaptive control; Adaptive systems; Analytical models; Control systems; Neural networks; Nonlinear control systems; Programmable control; Robust control; Stability; System performance;
Conference_Titel :
American Control Conference, 2006
Conference_Location :
Minneapolis, MN
Print_ISBN :
1-4244-0209-3
Electronic_ISBN :
1-4244-0209-3
DOI :
10.1109/ACC.2006.1657292