Fuzzy model-based predictive control by instantaneous linearization

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A linearization technique for product-sum crisp-type fuzzy model and a multistep predictive control strategy for the construction of a model-based predictive fuzzy controller is presented in this paper. A model-based predictive controller is based on a local linear model generated by using the proposed linearization technique that linearizes the product-sum crisp-type fuzzy process model around the current operating point. The control of pH in a continuous stirred tank reactor is chosen as a realistic nonlinear case study for the demonstration of the proposed control algorithm. The controller is shown to be capable of controlling the nonlinear processes that operate over a wide range, and of providing better overall system performance than the optimal PI controller.

Original languageEnglish
Pages (from-to)109-122
Number of pages14
JournalFuzzy Sets and Systems
Issue number1
Publication statusPublished - May 16 2001



  • Control theory
  • Fuzzy model linearization
  • Model-based control

ASJC Scopus subject areas

  • Logic
  • Artificial Intelligence

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