2019
DOI: 10.1007/s40815-019-00676-0
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How Effective are Smooth Compositions in Predictive Control of TS Fuzzy Models?

Abstract: In this article, we study the structural properties that smooth compositions bring to predictive control of TS fuzzy models and examine how they affect the uncertainties, parameter variations of the system and environmental noises to die out. We have employed the smoothness structure of compositions to convert the MPC cost function of TS fuzzy model of the nonlinear systems to an incremental iterative algorithm. Hence, the proposed algorithm does not linearize the nonlinear dynamics, neither requires solving a… Show more

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Cited by 11 publications
(2 citation statements)
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“…The fuzzy rules we have just constructed are supposed to have two IF and THEN parts, which can be interpreted to make a mathematical inference based on the fuzzy values employing the compositions of t-norms and s-norms. Different types of t-norms and s-norms have been introduced in the literature [18][19][20], where the min-max composition and product-sum composition are the mostly used compositions and are shown as follows:…”
Section: General Structure Of Fuzzy Systemsmentioning
confidence: 99%
“…The fuzzy rules we have just constructed are supposed to have two IF and THEN parts, which can be interpreted to make a mathematical inference based on the fuzzy values employing the compositions of t-norms and s-norms. Different types of t-norms and s-norms have been introduced in the literature [18][19][20], where the min-max composition and product-sum composition are the mostly used compositions and are shown as follows:…”
Section: General Structure Of Fuzzy Systemsmentioning
confidence: 99%
“…The achievements can be extended for the time varying smooth fuzzy systems [26] in the future works. Also, since the smooth fuzzy model is differentiable and the use of derivative based iterative optimization 648 techniques become possible for better connectivist identi-649 fication-control approaches [27], hence, the other future 650 work can focus on the development of a detailed error 651 mapping of the smooth fuzzy models for characterization 652 of high speed stages used in the noisy environments for 653 precise measurement and manipulation.…”
Section: Future Workmentioning
confidence: 99%