Fuzzy model-based predictive control by instantaneous linearization

Research output: Contribution to journalArticle

38 Citations (Scopus)

Abstract

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
Volume120
Issue number1
DOIs
Publication statusPublished - May 16 2001

Fingerprint

Linearization Techniques
Model-based Control
Predictive Control
Fuzzy Model
Linearization
Instantaneous
Model-based
Controller
PI Controller
Nonlinear Process
Fuzzy Controller
Controllers
Reactor
Process Model
Control Algorithm
Control Strategy
System Performance
Linear Model
Range of data
Demonstrations

Keywords

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

ASJC Scopus subject areas

  • Statistics and Probability
  • Electrical and Electronic Engineering
  • Statistics, Probability and Uncertainty
  • Information Systems and Management
  • Computer Vision and Pattern Recognition
  • Computer Science Applications
  • Artificial Intelligence

Cite this

Fuzzy model-based predictive control by instantaneous linearization. / Abonyi, János; Nagy, Lajos; Szeifert, Ferenc.

In: Fuzzy Sets and Systems, Vol. 120, No. 1, 16.05.2001, p. 109-122.

Research output: Contribution to journalArticle

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