Robust model predictive control for discrete T-S fuzzy systems with nonlinear local models

This paper presents a robust model predictive control method for discrete nonlinear systems. Instead of conventional T-S fuzzy system where linear local models are used, T-S fuzzy system with nonlinear local models is adopted that the number of fuzzy rules is decreased and the computational burden i...

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Bibliographic Details
Main Authors: Teng, Long, Wang, Youyi, Cai, Wenjian, Li, Hua
Other Authors: School of Electrical and Electronic Engineering
Format: Conference or Workshop Item
Language:English
Published: 2020
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Online Access:https://hdl.handle.net/10356/143561
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Institution: Nanyang Technological University
Language: English
Description
Summary:This paper presents a robust model predictive control method for discrete nonlinear systems. Instead of conventional T-S fuzzy system where linear local models are used, T-S fuzzy system with nonlinear local models is adopted that the number of fuzzy rules is decreased and the computational burden is reduced. Meanwhile, persistent external disturbances are also considered in the T-S fuzzy systems that input-to-state stability is realized. Based on the concept of robust positively invariant set, the terminal constraint set for T-S fuzzy systems with nonlinear local models is built. The advantages of the developed method is demonstrated in simulation by comparison with an existing fuzzy model predictive control method with linear local models.