Hybrid fuzzy predictive control based on genetic algorithms for the temperature control of a batch reactor

Javier Causa, Gorazd Karer, Alfredo Núñez, Doris Sáez, Igor Škrjanc, Borut Zupančič

Research output: Contribution to journalArticleScientificpeer-review

63 Citations (Scopus)

Abstract

In this paper we describe the design of hybrid fuzzy predictive control based on a genetic algorithm (GA). We also present a simulation test of the proposed algorithm and a comparison with two hybrid predictive control methods: Explicit Enumeration and Branch and Bound (BB). The experiments involved controlling the temperature of a batch reactor by using two on/off input valves and a discrete-position mixing valve. The GA-hybrid predictive control strategy proved to be a suitable method for the control of hybrid systems, giving similar performance to that of typical hybrid predictive control strategies and a significant saving with respect to the computation time.

Original languageEnglish
Pages (from-to)3254-3263
Number of pages10
JournalComputers and Chemical Engineering
Volume32
Issue number12
DOIs
Publication statusPublished - 22 Dec 2008
Externally publishedYes

Keywords

  • Fuzzy systems
  • Hybrid systems
  • Model predictive control
  • Process control

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