Automatic mining of model predictive control using particle swarm optimization

被引：16

作者：

Suzuki, Ryohei ^{[1
]}

Kawai, Fukiko ^{[2
]}

Ito, Hideyuki ^{[2
]}

Nakazawa, Chikashi ^{[2
]}

Fukuyama, Yoshikazu ^{[2
]}

Aiyoshi, Eitaro ^{[1
]}

机构：

[1] Keio Univ, Kohoku Ku, 3-14-1 Hiyoshi, Yokohama, Kanagawa 2238522, Japan

[2] Fuji Elect Adv Technol Co Ltd, Tokyo 1918502, Japan

来源：

2007 IEEE SWARM INTELLIGENCE SYMPOSIUM | 2007年

关键词：

D O I：

10.1109/SIS.2007.367941

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 an automatic tuning method of model predictive control (MPC) using particle swarm optimization (PSO). Although conventional PID is difficult to treat constraints and future plant dynamics, MPC can treat this issues and practical control can be realized in various industrial problems. One of the challenges in WC is how control parameters can be tuned for various target plants and usage of PSO for automatic tuning is one of the solutions. The numerical results show the effectiveness of the proposed PSO-based automatic tuning method.

引用

页码：221 / +

页数：2

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