Title :
Adaptive approximately optimal control of unknown nonlinear systems based on locally weighted learning
Author :
Dong, Wenjie ; Farrell, Jay A.
Author_Institution :
Dept. of Electr. Eng., Univ. of Texas-Pan American, Edinburg, TX, USA
Abstract :
This paper considers the optimal control of unknown nonlinear systems. Adaptive approximately optimal controllers are proposed with the aid of learning techniques. The proposed controllers can update themselves according to the estimates of the value functions and converge to the optimal controller. To show effectiveness of the proposed controllers, numerical simulations are presented.
Keywords :
adaptive control; learning (artificial intelligence); nonlinear control systems; numerical analysis; optimal control; adaptive approximately optimal control; locally weighted learning; numerical simulations; unknown nonlinear systems; value functions estimation; Adaptive control; Adaptive systems; Algorithm design and analysis; Control systems; Dynamic programming; Nonlinear equations; Nonlinear systems; Optimal control; Partial differential equations; Programmable control; Optimal control; approximately optimal control; learning; nonlinear system; uncertain systems;
Conference_Titel :
Decision and Control, 2009 held jointly with the 2009 28th Chinese Control Conference. CDC/CCC 2009. Proceedings of the 48th IEEE Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-3871-6
Electronic_ISBN :
0191-2216
DOI :
10.1109/CDC.2009.5400918
