DocumentCode :
1752758
Title :
Direct Adaptive Decoupling Control of Nonlinear Systems Based on Neural Networks and Multiple Models
Author :
Fu, Yue ; Chai, Tianyou
Author_Institution :
Res. Center of Autom., Northeastern Univ., Shenyang
Volume :
1
fYear :
0
fDate :
0-0 0
Firstpage :
2475
Lastpage :
2479
Abstract :
A direct adaptive decoupling controller is presented for a class of uncertain nonlinear multivariable discrete time dynamical systems. The direct adaptive decoupling controller is composed of a linear direct adaptive decoupling controller, a neural network nonlinear direct 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, while the switching mechanism is utilized 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; linear systems; multivariable control systems; neurocontrollers; nonlinear control systems; nonlinear dynamical systems; uncertain systems; linear direct adaptive decoupling controller; multiple models; neural network nonlinear direct adaptive decoupling controller; switching mechanism; system performance; system stability; uncertain nonlinear multivariable discrete time dynamical systems; Adaptive control; Adaptive systems; Control system synthesis; Control systems; Neural networks; Nonlinear control systems; Nonlinear systems; Programmable control; Stability; System performance; Decoupling; Direct adaptive control; Multiple models; Neural network; Nonlinear;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on
Conference_Location :
Dalian
Print_ISBN :
1-4244-0332-4
Type :
conf
DOI :
10.1109/WCICA.2006.1712806
Filename :
1712806
Link To Document :
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