Stability Analysis of Fuzzy Control for Nonlinear Systems

被引：11

作者：

Chen, Po-Chen ^{[1
]}

Yeh, Ken ^{[2
]}

Chen, Cheng-Wu ^{[3
]}

Lin, Shu-Hao ^{[2
]}

机构：

[1] Natl Cent Univ, Dept Civil Engn, Chungli, Taiwan

[2] De Lin Inst Technol, Dept Construct Sci & Technol, Taipei, Taiwan

[3] Shu Te Univ, Dept Logist Management, Kaohsiung, Taiwan

来源：

2009 FIRST ASIAN CONFERENCE ON INTELLIGENT INFORMATION AND DATABASE SYSTEMS | 2009年

关键词：

Neural network; Genetic algorithm; LYAPUNOV FUNCTION-APPROACH; DELAY-DEPENDENT STABILITY; INTERCONNECTED SYSTEMS; DESIGN; STABILIZATION;

D O I：

10.1109/ACIIDS.2009.83

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this study, we propose a method of stability analysis for a GA-Based reference ANNC capable of handling these types of problems for a nonlinear system. The initial values of the consequent parameter vector are decided via a genetic algorithm (GA) after which a modified adaptive law is derived based on Lyapunov stability theory to control the nonlinear system for tracking a user-defined reference model. The requirement of Kalman-Yacubovich lemma is fulfilling. A boundary-layer function is introduced into these updating laws to cover parameter and modeling errors, and to guarantee that the state errors converge into a specified error bound. After this, an adaptive neural network controller (ANNC) is derived to simultaneously stabilize and control the system.

引用

页码：238 / +

页数：3

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