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Model predictive control using fuzzy decision functions

da Costa Sousa, JM and Kaymak, U 2001, 'Model predictive control using fuzzy decision functions' , IEEE Transactions on Systems, Man and Cybernetics - Part B: Cybernetics, 31 (1) , pp. 54-65.

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Abstract

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 (MPC), and compares the results to those obtained from conventional MPC. 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.

Item Type: Article
Uncontrolled Keywords: Fuzzy criteria, fuzzy decision making (FDM), fuzzy predictive control, model predictive control (MPC)
Themes: Subjects / Themes > T Technology > TK Electrical engineering. Electronics Nuclear engineering
Subjects / Themes > Q Science > QA Mathematics > QA075 Electronic computers. Computer science
Subjects outside of the University Themes
Schools: Colleges and Schools > College of Science & Technology
Colleges and Schools > College of Science & Technology > School of Computing, Science and Engineering
Journal or Publication Title: IEEE Transactions on Systems, Man and Cybernetics - Part B: Cybernetics
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Refereed: Yes
ISSN: 10834419
Related URLs:
Depositing User: Institutional Repository
Date Deposited: 12 Mar 2009 15:24
Last Modified: 20 Aug 2013 15:56
URI: http://usir.salford.ac.uk/id/eprint/1818

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