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

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...

Full description

Saved in:
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
Subjects:
Engineering::Electrical and electronic engineering
Fuzzy Systems
Predictive Control
Online Access:https://hdl.handle.net/10356/143561
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Nanyang Technological University
Language: English
id sg-ntu-dr.10356-143561
record_format dspace
spelling sg-ntu-dr.10356-1435612021-01-14T07:36:24Z Robust model predictive control for discrete T-S fuzzy systems with nonlinear local models Teng, Long Wang, Youyi Cai, Wenjian Li, Hua School of Electrical and Electronic Engineering School of Mechanical and Aerospace Engineering Interdisciplinary Graduate School (IGS) 2016 12th IEEE International Conference on Control and Automation (ICCA) Energy Research Institute @ NTU (ERI@N) Engineering::Electrical and electronic engineering Fuzzy Systems Predictive Control 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. Accepted version 2020-09-09T05:59:40Z 2020-09-09T05:59:40Z 2016 Conference Paper 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 978-1-5090-1738-6 https://hdl.handle.net/10356/143561 10.1109/ICCA.2016.7505255 74 79 en © 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. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Electrical and electronic engineering
Fuzzy Systems
Predictive Control
spellingShingle Engineering::Electrical and electronic engineering
Fuzzy Systems
Predictive Control
Teng, Long
Wang, Youyi
Cai, Wenjian
Li, Hua
Robust model predictive control for discrete T-S fuzzy systems with nonlinear local models
description 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.
author2 School of Electrical and Electronic Engineering
author_facet School of Electrical and Electronic Engineering
Teng, Long
Wang, Youyi
Cai, Wenjian
Li, Hua
format Conference or Workshop Item
author Teng, Long
Wang, Youyi
Cai, Wenjian
Li, Hua
author_sort Teng, Long
title Robust model predictive control for discrete T-S fuzzy systems with nonlinear local models
title_short Robust model predictive control for discrete T-S fuzzy systems with nonlinear local models
title_full Robust model predictive control for discrete T-S fuzzy systems with nonlinear local models
title_fullStr Robust model predictive control for discrete T-S fuzzy systems with nonlinear local models
title_full_unstemmed Robust model predictive control for discrete T-S fuzzy systems with nonlinear local models
title_sort robust model predictive control for discrete t-s fuzzy systems with nonlinear local models
publishDate 2020
url https://hdl.handle.net/10356/143561
_version_ 1690658276144840704

Similar Items