Swarm-based approximate dynamic optimization process for discrete particle swarm optimization system

被引：8

作者：

Kang, Qi ^{[1
]}

Wang, Lei ^{[1
]}

Wu, Qidi ^{[1
]}

机构：

[1] Tongji Univ, Dept Control Sci & Engn, Shanghai 201804, Peoples R China

来源：

INTERNATIONAL JOURNAL OF BIO-INSPIRED COMPUTATION | 2009年 / 1卷 / 1-2期

关键词：

particle swarm optimization; PSO; approximate dynamic programming; dynamic optimization; STABILITY;

D O I：

10.1504/IJBIC.2009.022774

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper presents a convergence analysis of particle swarm optimization system by treating it as a discrete-time linear time-variant system firstly. And then, based on the results of system convergence conditions, dynamic optimal control of a deterministic PSO system for parameters optimization is studied by using dynamic programming; and an approximate dynamic programming algorithm - swarm-based approximate dynamic programming (swarm-ADP) is proposed in this paper. Finally, numerical simulations proved the validated of this presented dynamic optimization method.

引用

页码：61 / 70

页数：10