Parameter optimization of model predictive control by PSO

Ryohei Suzuki, Fukiko Kawai, Chikashi Nakazawa, Tetsuro Matsui, Eitaro Aiyoshi

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)


Among various control methods, model predictive control (MPC) becomes one of the major control strategies and has many successful applications. This paper presents an automatic tuning method of MPC using particle swarm optimization (PSO). One of the challenges in MPC is how control parameters can be turned for various target plants and usage of PSO for automatic tuning is one of the solutions. The tuning problem of MPC is formulated as an optimization problem and PSO is applied as the optimization techniques. PSO is one of meta-heuristic methods which are known to search a global optimum at a relatively high ratio and with no use of a gradient. The numerical results for simple examples show the effectiveness of the proposed PSO-based automatic tuning method.

Original languageEnglish
Pages (from-to)432-440+5
JournalIEEJ Transactions on Electronics, Information and Systems
Issue number3
Publication statusPublished - 2009


  • Metaheuristics
  • Model predictive control
  • Parameter optimization
  • Particle swarm optimization

ASJC Scopus subject areas

  • Electrical and Electronic Engineering


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