Robust indirect adaptive fuzzy control using Nussbaum gain for a class of SISO nonlinear systems with unknown directions

被引：0
|
作者：
Bounemeur, A. [1 ]
Chemachema, M. [1 ]
Essounbouli, N. [2 ]
机构：
[1] Univ Constantine, Fac Technol, Dept Elect, Constantine, Algeria
[2] Tech Inst Troyes, Dept Mech Engn, F-10026 Troyes, France
来源：
201415TH INTERNATIONAL CONFERENCE ON SCIENCES & TECHNIQUES OF AUTOMATIC CONTROL & COMPUTER ENGINEERING (STA'2014) | 2014年
关键词：
adaptive fuzzy control; nonlinear systems; Lyapunov stability; NEURAL-CONTROL; DELAY SYSTEMS; KNOWLEDGE; ESTIMATOR;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper deals with indirect adaptive control using fuzzy systems for a class of uncertain SISO systems with unknown control gain sign. The uncertain nonlinearities of the systems are captured by fuzzy systems that have been proven to be universal approximators and the Nussbaum -type function is used to deal with the unknown control gain sign. The proposed control scheme completely overcomes the singularity problem that occurs in the indirect adaptive feedback linearizing control. Projection in the estimate parameters is not required and the stability analysis of the closed-loop system is performed using Lyapunov approach. Simulation results are provided to verify the effectiveness of the proposed design.
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页码：748 / +
页数：7
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