Stability Analysis of Fuzzy Control for Nonlinear Systems

被引：5
|
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
收藏
页码：238 / +
页数：3
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