Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/143561
Title: Robust model predictive control for discrete T-S fuzzy systems with nonlinear local models
Authors: Teng, Long
Wang, Youyi
Cai, Wenjian
Li, Hua
Keywords: Engineering::Electrical and electronic engineering
Issue Date: 2016
Source: Teng, L., Wang, Y., Cai, W., & Li, H. (2016). Robust model predictive control for discrete T-S fuzzy systems with nonlinear local models. 2016 12th IEEE International Conference on Control and Automation (ICCA), 74-79. doi:10.1109/icca.2016.7505255
Abstract: 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.
URI: https://hdl.handle.net/10356/143561
ISBN: 978-1-5090-1738-6
DOI: 10.1109/ICCA.2016.7505255
Rights: © 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: https://doi.org/10.1109/ICCA.2016.7505255.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Conference Papers

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