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
收藏
页码：61 / 70
页数：10
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