Title :
Optimal Regulation of Unknown Nonlinear Systems Based on Locally Weighted Learning
Author :
Dong, Wenjie ; Farrell, Jay A.
Author_Institution :
Dept. of Electr. Eng., Univ. of California, Riverside, CA
Abstract :
This paper considers the optimal control of unknown nonlinear systems. To deal with the uncertainties in the system, a locally weighted learning observer (LWLO) is proposed. Using the functions approximated within the LWLO, analytic optimal controllers are proposed in the sense of pointwise min-norm. To show effectiveness of the proposed controllers, numerical simulations are presented.
Keywords :
function approximation; nonlinear control systems; observers; optimal control; uncertain systems; function approximation; locally weighted learning observer; optimal control; optimal regulation; pointwise min-norm; uncertain system; unknown nonlinear systems; Control systems; Cost function; Nonlinear control systems; Nonlinear equations; Nonlinear systems; Open loop systems; Optimal control; Partial differential equations; Riccati equations; Stability;
Conference_Titel :
Intelligent Control, 2008. ISIC 2008. IEEE International Symposium on
Conference_Location :
San Antonio, TX
Print_ISBN :
978-1-4244-2224-1
Electronic_ISBN :
2158-9860
DOI :
10.1109/ISIC.2008.4635938
