A case study for fuzzy adaptive multiple models predictive control strategy

The purpose of the paper presented here is to deal with the well-known linear generalized predictive control (LGPC) scheme based on multiple models strategy for a tubular heat exchanger system. In this control strategy, the operating environments of the system are first represented by multiple expli...

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Bibliographic Details
Published in2009 IEEE International Symposium on Industrial Electronics pp. 1172 - 1177
Main Authors Mazinan, A.H., Sadati, N., Ahmadi-Noubari, H.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.07.2009
Subjects
Adaptive control
Fuzzy control
Fuzzy systems
Heat transfer
Modeling
Predictive control
Predictive models
Programmable control
Temperature control
Temperature distribution
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Summary:The purpose of the paper presented here is to deal with the well-known linear generalized predictive control (LGPC) scheme based on multiple models strategy for a tubular heat exchanger system. In this control strategy, the operating environments of the system are first represented by multiple explicit linear models. Then the best model of the system is precisely identified by a novel intelligent decision mechanism (IDM), where is organized in association with the fuzzy adaptive Kalman filter and recursive weight generator approaches. As soon as the best model of the system is identified, the corresponding predictive control action is instantly implemented on the system. In order to demonstrate the effectiveness of the proposed strategy, simulations are carried out and the outcomes are compared with those obtained using the nonlinear GPC (NLGPC) approach. The results can verify the validity of the proposed control scheme.
ISBN:9781424443475
1424443474
ISSN:2163-5137
DOI:10.1109/ISIE.2009.5217435