Automatic tuning of model predictive control using particle swarm optimization

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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

14 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 languageEnglish
Title of host publicationProceedings of the 2007 IEEE Swarm Intelligence Symposium, SIS 2007
Pages221-226
Number of pages6
DOIs
Publication statusPublished - 2007 Sep 25
Event2007 IEEE Swarm Intelligence Symposium, SIS 2007 - Honolulu, HI, United States
Duration: 2007 Apr 12007 Apr 5

Publication series

NameProceedings of the 2007 IEEE Swarm Intelligence Symposium, SIS 2007

Other

Other2007 IEEE Swarm Intelligence Symposium, SIS 2007
CountryUnited States
CityHonolulu, HI
Period07/4/107/4/5

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ASJC Scopus subject areas

  • Artificial Intelligence

Cite this

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 (pp. 221-226). [4223178] (Proceedings of the 2007 IEEE Swarm Intelligence Symposium, SIS 2007). https://doi.org/10.1109/SIS.2007.367941