Model predictive control using fuzzy decision functions

U. Kaymak, J.M. Costa Sousa, da

Research output: Contribution to journalArticleAcademicpeer-review

78 Citations (Scopus)

Abstract

Fuzzy predictive control integrates conventional model predictive control with techniques from fuzzy multicriteria decision making, translating the goals and the constraints to predictive control in a transparent way. The information regarding the (fuzzy) goals and the (fuzzy) constraints of the control problem is combined by using a decision function from the theory of fuzzy sets. This paper investigates the use of fuzzy decision making (FDM) in model predictive control (MPG), and compares the results to those obtained from conventional MPG. Attention is also paid to the choice of aggregation operators for fuzzy decision making in control. Experiments on a nonminimum phase, unstable linear system, and on an air-conditioning system with nonlinear dynamics are studied. It is shown that the performance of the model predictive controller can be improved by the use of fuzzy criteria in a fuzzy decision making framework.
Original languageEnglish
Pages (from-to)54-65
Number of pages12
JournalIEEE Transactions on Systems, Man and Cybernetics. Part B, Cybernetics
Volume31
Issue number1
DOIs
Publication statusPublished - 2001

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