Title :
Adaptive neural control of a class of MIMO nonlinear systems
Author :
Ge, Shuzhi S. ; Wang, Cong
Author_Institution :
Dept. of Electr. & Comput. Eng., Nat. Univ. of Singapore, Singapore
Abstract :
In this paper, an adaptive neural control scheme is proposed for a class of uncertain MIMO nonlinear systems in block-triangular form. By exploiting the special structural property of the MIMO system, the developed scheme avoids the controller singularity problem completely without calculating the inverse of the estimated "decoupling matrix". Moreover, the stability of the whole closed-loop system is concluded in a nested iterative manner. The proposed scheme offers a systematic design procedure for the control of a class of uncertain MIMO nonlinear systems
Keywords :
MIMO systems; adaptive control; closed loop systems; neurocontrollers; nonlinear control systems; stability; MIMO nonlinear systems; adaptive control; block-triangular form; closed-loop system; neural control scheme; stability; uncertain systems; Adaptive control; Control systems; Couplings; Lyapunov method; MIMO; Neural networks; Nonlinear control systems; Nonlinear systems; Programmable control; Projection algorithms;
Conference_Titel :
Decision and Control, 2001. Proceedings of the 40th IEEE Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
0-7803-7061-9
DOI :
10.1109/.2001.980406
