NDLI: Fuzzy Model based Predictive control of a Hammerstein model with constraints handling

Content Provider	IEEE Xplore Digital Library
Author	Raees, A. Kadri, M.B.
Copyright Year	2012
Description	Author affiliation: PNEC, NUST (National University of Science and Technology) in the Department of Power Electronics and Electrical Engineering (Kadri, M.B.) \|\| Control Designing in Masters Degree Program from Pakistan (Raees, A.)
Abstract	Controlling complex systems, containing nonlinearities and constraints, is always a domain of interest for researchers. Different schemes such as Nonlinear Model Predictive Control (NMPC) have been proposed but these are usually computationally demanding and complex by themselves. Nowadays two powerful techniques, Fuzzy Modeling and Model Predictive control, are being blended together in different ways to attain the advantages of controlling delayed, non-minimum phase, nonlinear and constrained systems efficiently. The paper discusses this novel technique to control a class of nonlinear systems, the Hammerstein models. In order to control the Hammerstein model containing static nonlinearity with linear GPC algorithm a $0^{th}$ order TS adaptive fuzzy inverse model controller is used with feedback. This strategy makes the scheme powerful enough to be used with different Hammerstein models containing different types of static nonlinearities and different linear dynamics. Furthermore the GPC algorithm is developed by using Toeplitz/Hankel matrices rather than Diophantine equation to reduce computational complexity. The scheme has been tested in MATLAB/Simulink for different kinds of nonlinearities and different parameters of system dynamics, and has produced good control results. Simulation results show that in any case, the optimization remains convex and single layer of optimization is sufficient to optimize the cost function.
Starting Page	1
Ending Page	6
File Size	468641
Page Count	6
File Format	PDF
ISBN	9781467346870
e-ISBN	9781467346887
e-ISBN	9781467346863
DOI	10.1109/ESTEL.2012.6400119
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-10-02
Publisher Place	Italy
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Adaptation models TS fuzzy model Generalized Predictive control Hammerstein model Computational modeling Predictive models Prediction algorithms Constrained recursive least squares estimation Mathematical model Optimization Predictive control
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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