A Particle Swarm Optimization Approach for Parameter Identification of Lorenz Chaotic System

被引：1

作者：

Modarres, Hamidreza ^{[1
]}

Alfi, Alireza ^{[1
]}

机构：

[1] Shahrood Univ Technol, Fac Elect & Robot Engn, Shahrood 3619995161, Iran

来源：

IECON: 2009 35TH ANNUAL CONFERENCE OF IEEE INDUSTRIAL ELECTRONICS, VOLS 1-6 | 2009年

关键词：

VARIABLE-STRUCTURE CONTROL; ADAPTIVE SYNCHRONIZATION; COMMUNICATION;

D O I：

10.1109/IECON.2009.5415058

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

An important problem in engineering is the identification of nonlinear systems, among them chaotic systems have received particular attention due to their complex and unpredictable behaviors. In this paper, a Particle Swarm Optimization (PSO) technique is applied for online parameter identification of Lorenz chaotic system. The difficulties of online implementation mainly come from the unavoidable computational time to find a solution. Due to this, first an Improved Particle Swarm Optimization (IPSO) is proposed to increase the convergence speed and accuracy of the Standard Particle Swarm Optimization (SPSO) to save tremendous computation time. Second. IPSO is also improved to detect and determine the variation of parameters. Finally, a numerical example is given to verify the effectiveness of the proposed method compared to Genetic Algorithm (GA) and SPSO.

引用

页码：3127 / +

页数：2

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