Performance based linear control system design by genetic evolution with simulated annealing

Yun Li*, Chen Tan, Kim Chwee Ng, David J. Murray-Smith

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

8 Citations (Scopus)

Abstract

This paper develops a genetic algorithm based design automation method for linear control systems. It unifies the design and avoids the need for pre-selection of control schemes. Using this method, best performance is obtained for controllers described by a transfer function. The genetic algorithm encoded in decimal numerals is fine tuned by incorporating a simulated annealing technique for a more accurate search. It is shown that the design can be applied to both linear and nonlinear plants without manual calculations and can include practical constraints imposed upon the performance requirement. This method also allows the step of linearising nonlinear plants to be bypassed.

Original languageEnglish
Pages (from-to)731-736
Number of pages6
JournalProceedings of the IEEE Conference on Decision and Control
Volume1
Publication statusPublished - 1 Dec 1995

Keywords

  • linear systems
  • nonlinear systems
  • control system synthesis
  • genetic algorithms
  • simulated annealing
  • search problems
  • transfer functions

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