Premium
Parameter optimization of model predictive control by PSO
Author(s) -
Suzuki Ryohei,
Kawai Fukiko,
Nakazawa Chikashi,
Matsui Tetsuro,
Aiyoshi Eitaro
Publication year - 2011
Publication title -
electrical engineering in japan
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.136
H-Index - 28
eISSN - 1520-6416
pISSN - 0424-7760
DOI - 10.1002/eej.21188
Subject(s) - particle swarm optimization , model predictive control , metaheuristic , computer science , mathematical optimization , control theory (sociology) , simple (philosophy) , control (management) , mathematics , artificial intelligence , philosophy , epistemology
Among various control methods, model predictive control (MPC) is one of the major control strategies and has many successful applications. This paper presents an automatic tuning method for MPC using particle swarm optimization (PSO). One of the challenges in MPC is how control parameters can be tuned for various target plants, and the use of PSO for automatic tuning is one of the solutions. The MPC tuning problem is formulated as an optimization problem and PSO is applied as the optimization technique. PSO is one of the metaheuristic methods which are known to seek 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. © 2011 Wiley Periodicals, Inc. Electr Eng Jpn, 178(1): 40–49, 2012; Published online in Wiley Online Library ( wileyonlinelibrary.com ). DOI 10.1002/eej.21188