DECENTRALIZED STATE FEEDBACK ADAPTIVE TRACKING FOR A CLASS OF STOCHASTIC NONLINEAR LARGE-SCALE SYSTEMS

摘要：

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.

关键词： Stochastic large-scale systems Decentralized control Tracking control Adaptive systems State feedback

作者: SAI WU FEI-QI DENG

作者单位: School of Economic Management, Guangdong University of Technology, Guangzhou 510520, China School of Automation Science and Engineering, South China University of Technology, Guangzhou 510640

会议类型: 国际会议

会议名称: 2008 International Conference on Machine Learning and Cybernetics(2008机器学习与控制论国际会议)

会议地点: 昆明

会议语种:英文

页码: 2287-2292

在线出版日期: 2008-07-12（万方平台首次上网日期，不代表论文的发表时间）