DocumentCode :
2854278
Title :
Robust adaptive optimal control for unknown dynamical systems
Author :
Sadamoto, T. ; Yamakita, M.
Author_Institution :
Dept. of Mech. & Control Eng., Tokyo Inst. of Technol., Tokyo, Japan
fYear :
2011
fDate :
June 29 2011-July 1 2011
Firstpage :
4207
Lastpage :
4212
Abstract :
In this paper, we propose an algorithm of adaptive optimal control scheme for systems whose dynamics are unknown and the states are contaminated by noises. The basic control law is Policy Iteration which can solve HJB equation recursively. In the proposed method, the value function is estimated using a nonlinear filtering but the state of the system is not estimated since the system model is not available. Since the proposed method can reduce the effects of the noises without using the system model, we can apply this method to many practical systems without model and parameters.
Keywords :
adaptive control; nonlinear filters; optimal control; partial differential equations; robust control; HJB equation; Hamilton-Jacobi-Bellman equation; nonlinear filtering; policy iteration control law; robust adaptive optimal control; unknown dynamical system; Approximation algorithms; Cost function; Equations; Estimation; Mathematical model; Noise; Optimal control;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
American Control Conference (ACC), 2011
Conference_Location :
San Francisco, CA
ISSN :
0743-1619
Print_ISBN :
978-1-4577-0080-4
Type :
conf
DOI :
10.1109/ACC.2011.5991234
Filename :
5991234
Link To Document :
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