Parameter Optimization of Model Predictive Control by PSO

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...

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Veröffentlicht in:Denki Gakkai ronbunshi. C, Erekutoronikusu, joho kogaku, shisutemu Information and Systems, 2009/03/01, Vol.129(3), pp.432-440
Hauptverfasser: Suzuki, Ryohei, Kawai, Fukiko, Nakazawa, Chikashi, Matsui, Tetsuro, Aiyoshi, Eitaro
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Sprache:eng
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Zusammenfassung: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.
ISSN:0385-4221
1348-8155
DOI:10.1541/ieejeiss.129.432