Automatic tuning of model predictive control using particle swarm optimization

Ryohei Suzuki; Fukiko Kawai; Hideyuki Ito; Chikashi Nakazawa; Yoshikazu Fukuyama; Eitaro Aiyoshi

doi:10.1109/SIS.2007.367941

Automatic tuning of model predictive control using particle swarm optimization

Ryohei Suzuki, Fukiko Kawai, Hideyuki Ito, Chikashi Nakazawa, Yoshikazu Fukuyama, Eitaro Aiyoshi

Department of Applied Physics and Physico-Informatics

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

15 Citations (Scopus)

Abstract

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 MPC 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.

Original language	English
Title of host publication	Proceedings of the 2007 IEEE Swarm Intelligence Symposium, SIS 2007
Pages	221-226
Number of pages	6
DOIs	https://doi.org/10.1109/SIS.2007.367941
Publication status	Published - 2007 Sep 25
Event	2007 IEEE Swarm Intelligence Symposium, SIS 2007 - Honolulu, HI, United States Duration: 2007 Apr 1 → 2007 Apr 5

Publication series

Name	Proceedings of the 2007 IEEE Swarm Intelligence Symposium, SIS 2007

Other

Other	2007 IEEE Swarm Intelligence Symposium, SIS 2007
Country	United States
City	Honolulu, HI
Period	07/4/1 → 07/4/5

ASJC Scopus subject areas

Artificial Intelligence

Access to Document

10.1109/SIS.2007.367941

Fingerprint Dive into the research topics of 'Automatic tuning of model predictive control using particle swarm optimization'. Together they form a unique fingerprint.

Cite this

Automatic tuning of model predictive control using particle swarm optimization. / Suzuki, Ryohei; Kawai, Fukiko; Ito, Hideyuki; Nakazawa, Chikashi; Fukuyama, Yoshikazu; Aiyoshi, Eitaro.

Proceedings of the 2007 IEEE Swarm Intelligence Symposium, SIS 2007. 2007. p. 221-226 4223178 (Proceedings of the 2007 IEEE Swarm Intelligence Symposium, SIS 2007).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Suzuki, R, Kawai, F, Ito, H, Nakazawa, C, Fukuyama, Y & Aiyoshi, E 2007, Automatic tuning of model predictive control using particle swarm optimization. in Proceedings of the 2007 IEEE Swarm Intelligence Symposium, SIS 2007., 4223178, Proceedings of the 2007 IEEE Swarm Intelligence Symposium, SIS 2007, pp. 221-226, 2007 IEEE Swarm Intelligence Symposium, SIS 2007, Honolulu, HI, United States, 07/4/1. https://doi.org/10.1109/SIS.2007.367941

@inproceedings{058d393a0fb84e69b3b19b4e01572668,

title = "Automatic tuning of model predictive control using particle swarm optimization",

abstract = "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 MPC 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.",

author = "Ryohei Suzuki and Fukiko Kawai and Hideyuki Ito and Chikashi Nakazawa and Yoshikazu Fukuyama and Eitaro Aiyoshi",

year = "2007",

month = sep,

day = "25",

doi = "10.1109/SIS.2007.367941",

language = "English",

isbn = "1424407087",

series = "Proceedings of the 2007 IEEE Swarm Intelligence Symposium, SIS 2007",

pages = "221--226",

booktitle = "Proceedings of the 2007 IEEE Swarm Intelligence Symposium, SIS 2007",

note = "2007 IEEE Swarm Intelligence Symposium, SIS 2007 ; Conference date: 01-04-2007 Through 05-04-2007",

}

TY - GEN

T1 - Automatic tuning of model predictive control using particle swarm optimization

AU - Suzuki, Ryohei

AU - Kawai, Fukiko

AU - Ito, Hideyuki

AU - Nakazawa, Chikashi

AU - Fukuyama, Yoshikazu

AU - Aiyoshi, Eitaro

PY - 2007/9/25

Y1 - 2007/9/25

N2 - 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 MPC 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.

AB - 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 MPC 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.

UR - http://www.scopus.com/inward/record.url?scp=34548743532&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=34548743532&partnerID=8YFLogxK

U2 - 10.1109/SIS.2007.367941

DO - 10.1109/SIS.2007.367941

M3 - Conference contribution

AN - SCOPUS:34548743532

SN - 1424407087

SN - 9781424407088

T3 - Proceedings of the 2007 IEEE Swarm Intelligence Symposium, SIS 2007

SP - 221

EP - 226

BT - Proceedings of the 2007 IEEE Swarm Intelligence Symposium, SIS 2007

T2 - 2007 IEEE Swarm Intelligence Symposium, SIS 2007

Y2 - 1 April 2007 through 5 April 2007

ER -