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A Comparative Study of the Dynamic Matrix Controller Tuning by Evolutionary Computation

  • Gustavo Maia de Almeida
  • Marco Antonio de S.L. Cuadro
  • Rogério Passos Pereira Amaral
  • José Leandro F. Salles
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 373)

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.

Keywords

Evolutionary Computation Genetic Algorithm Ant Colony Optimization Particle Swarm Optimization Dynamic Matrix Controller 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Gustavo Maia de Almeida
    • 1
  • Marco Antonio de S.L. Cuadro
    • 1
  • Rogério Passos Pereira Amaral
    • 1
  • José Leandro F. Salles
    • 2
  1. 1.Instituto Federal do Espírito SantoCoordenadoria de Automação IndustrialSerraBrasil
  2. 2.Departamento de Engenharia ElétricaUniversidade Federal do Espírito SantoVitóriaBrasil

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