Abstract
The Dynamic Matrix Control (DMC) Algorithm is a control method widely applied to industrial processes. Evolutionary Computation (EP) is a vibrant area of investigation, with some of the least widely known approaches being Genetic Algorithm (GA), Ant Colony Optimization (ACO) and Particle Swarm Optimization (PSO) all of which can be used in optimisation problem. This work make a comparative study of the effectiveness of the three methods to optimize the tuning parameters of the Dynamic Matrix Controller for SISO (single-input single-output) and MIMO (multi-input multi-output) linear dynamical systems with constraints.
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de Almeida, G.M., de S.L. Cuadro, M.A., Amaral, R.P.P., Salles, J.L.F. (2015). A Comparative Study of the Dynamic Matrix Controller Tuning by Evolutionary Computation. In: Omatu, S., et al. Distributed Computing and Artificial Intelligence, 12th International Conference. Advances in Intelligent Systems and Computing, vol 373. Springer, Cham. https://doi.org/10.1007/978-3-319-19638-1_24
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DOI: https://doi.org/10.1007/978-3-319-19638-1_24
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