Title :
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
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;
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
DOI :
10.1109/ICMLC.2008.4620786
