ROBUST SELF-TUNING FUZZY TRACKER DESIGN OF TIME-VARYING NONLINEAR SYSTEMS

摘要：

This paper presents a search strategy to identify nonlinear dynamic systems as time-varying fuzzy model by modeling performance index. We introduce the fuzzy Lyapunov function to design the robust fuzzy tracker of the unknown nonlinear system with an H∞ performance index based on the modeling error. In addition, we propose a compound search strategy of robust gains called conditional linear matrix inequality (CLMI) approach which was composed of the proposed improved random optimal algorithms (IROA). Moreover, the self-tuning gains are optimized by the cost function of IROA. Finally, a chaotic example is given to illustrate the utility of the proposed design method.

关键词： Time-varying fuzzy model self-tuning gains improved random optimal algorithms (IROA)

作者: JIING-DONG HWANG ZHI-REN TSAI JIAN-YU CHEN

作者单位: Institute of Computer and Communication Engineering, Jinwen University of Science and Technology, Ta Department of Computer Science and Information Electronic Engineering, Asia University, Taichung Cou

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: 3354-3360

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）