Decentralized state feedback adaptive tracking for a class of stochastic nonlinear large-scale systems

Author

Wu, Sai ; Deng, Fei-qi

Author_Institution

Sch. of Economic Manage., Guangdong Univ. of Technol., Guangzhou

Volume

4

fYear

2008

fDate

12-15 July 2008

Firstpage

2287

Lastpage

2292

Abstract

In this paper, decentralized adaptive tracking problem is studied for a class of stochastic nonlinear large-scale systems, which can be parameterized. The systems are transformed into parameterized strict-feedback nonlinear large-scale form through coordinate transformation at first. By employing the stochastic Lyapunov-like theorem and the backstepping design technique, the adaptive state feedback decentralized controller and parameters adaptive law are developed. The output of the closed-loop system is proven to follow the desired trajectory asymptotically in probability.

Keywords

Lyapunov methods; adaptive control; closed loop systems; decentralised control; large-scale systems; nonlinear control systems; state feedback; stochastic systems; backstepping design technique; closed-loop system; decentralized state feedback adaptive tracking; parameterized strict-feedback nonlinear large-scale; stochastic Lyapunov-like theorem; stochastic nonlinear large-scale systems; Adaptive control; Backstepping; Control systems; Distributed control; Large-scale systems; Machine learning; Nonlinear systems; Programmable control; State feedback; Stochastic systems; Adaptive systems; Decentralized control; State feedback; Stochastic large-scale systems; Tracking control;

fLanguage

English

Publisher

ieee

Conference_Titel

Machine Learning and Cybernetics, 2008 International Conference on

Conference_Location

Kunming

Print_ISBN

978-1-4244-2095-7

Electronic_ISBN

978-1-4244-2096-4

Type

conf

DOI

10.1109/ICMLC.2008.4620786

Filename

4620786