Control of non-linear time-varying systems using fuzzy relational models

Craig Edgar, Bruce Postlethwaite

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

The majority of chemical processes are non-linear in nature. Increasingly, non-linear models are being used as key parts of chemical plant control schemes. A problem with any model is that it can become inaccurate over time and consequently for good control of time-varying processes some sort of model adaptation is required. In this paper a Fuzzy Relational Model (FRM) is incorporated into a multi-variable Fuzzy Internal Model Controller (FIMC). A mechanism for on-line adaptation of the model is described and implemented. Results are presented for a simulated MIMO system.
Original languageEnglish
Title of host publicationUKACC International Conference on Control '98.
PublisherIEEE
Pages60-65
Number of pages5
Volume1
ISBN (Print)0-85296-708-X
Publication statusPublished - Sep 1998

Keywords

  • FIMC
  • FRM
  • fuzzy relational model
  • model adaptation
  • multivariable fuzzy internal model controller
  • nonlinear chemical processes
  • nonlinear time-varying system control
  • online adaptation
  • simulated MIMO system

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  • Cite this

    Edgar, C., & Postlethwaite, B. (1998). Control of non-linear time-varying systems using fuzzy relational models. In UKACC International Conference on Control '98. (Vol. 1, pp. 60-65). IEEE.