Automatic tuning for model predictive control: Can particle swarm optimization find a better parameter?

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

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

7 Citations (Scopus)

Abstract

This paper presents an automatic tuning method of model predictive control (MPC) using particle swarm optimization (PSO). Although it is difficult for unskilled control designers to tune MPC weight parameters, PSO can solve 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 publication22nd IEEE International Symposium on Intelligent Control, ISIC 2007. Part of IEEE Multi-conference on Systems and Control
PublisherIEEE Computer Society
Pages646-651
Number of pages6
ISBN (Print)142440441X, 9781424404414
DOIs
Publication statusPublished - 2007 Jan 1
Event2007 IEEE 22nd International Symposium on Intelligent Control, ISIC 2007 - Singapore, Singapore
Duration: 2007 Oct 12007 Oct 3

Publication series

Name22nd IEEE International Symposium on Intelligent Control, ISIC 2007. Part of IEEE Multi-conference on Systems and Control

Other

Other2007 IEEE 22nd International Symposium on Intelligent Control, ISIC 2007
CountrySingapore
CitySingapore
Period07/10/107/10/3

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ASJC Scopus subject areas

  • Computer Science Applications
  • Control and Systems Engineering
  • Electrical and Electronic Engineering
  • Modelling and Simulation

Cite this

Kawai, F., Ito, H., Nakazawa, C., Matsui, T., Fukuyama, Y., Suzuki, R., & Aiyoshi, E. (2007). Automatic tuning for model predictive control: Can particle swarm optimization find a better parameter? In 22nd IEEE International Symposium on Intelligent Control, ISIC 2007. Part of IEEE Multi-conference on Systems and Control (pp. 646-651). [4450961] (22nd IEEE International Symposium on Intelligent Control, ISIC 2007. Part of IEEE Multi-conference on Systems and Control). IEEE Computer Society. https://doi.org/10.1109/ISIC.2007.4450961