Robust adaptive dynamic programming for continuous-time linear stochastic systems

Author

Tao Bian ; Zhong-Ping Jiang

Author_Institution

Dept. of Electr. & Comput. Eng., New York Univ., New York, NY, USA

fYear

2014

fDate

8-10 Oct. 2014

Firstpage

536

Lastpage

541

Abstract

In this paper, a robust optimal control problem is investigated for continuous-time linear stochastic systems with dynamic uncertainties. A non-model based stochastic robust optimal control design methodology is employed to iteratively update the control policy online by directly using the online information. A robust adaptive dynamic programming (RADP) algorithm is developed, together with rigorous convergence and stability analysis. The effectiveness of the proposed method is also illustrated by an example of two connected inverted pendulums.

Keywords

adaptive control; continuous time systems; control system synthesis; dynamic programming; linear systems; nonlinear control systems; optimal control; pendulums; robust control; stochastic systems; RADP; connected inverted pendulums; continuous-time linear stochastic systems; control policy; convergence; nonmodel based stochastic robust optimal control design methodology; online information; robust adaptive dynamic programming; stability analysis; Algorithm design and analysis; Noise; Optimal control; Robustness; Stability analysis; Stochastic processes; Stochastic systems;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Control (ISIC), 2014 IEEE International Symposium on

Conference_Location

Juan Les Pins

Type

conf

DOI

10.1109/ISIC.2014.6967601

Filename

6967601