A Terminal Constraint Set-Dependent Mixed Time/Event-Triggered Approach to Multistep Fuzzy MPC

In this article, the problem of multistep model predictive control (MPC) under a mixed time/event-triggered mechanism (MTEM) is investigated for fuzzy systems with hard constraints. To improve its flexibility in adjusting releases, this MTEM incorporates the information from the fuzzy membership functions and the terminal constraint set (TCS). In the online control unit, the time-triggered way is first implemented to steer the system state into the TCS quickly, and then in the offline control unit, the involved event-triggered pattern plays its role in conserving resources while ensuring the control performance. Two offline optimization problems (OPs) are presented to design the TCS and the approximate robust one step sets, respectively, and an online OP is given to design the control laws to steer the system state into TCS. Based on these three OPs, we propose an MTEM-based multistep fuzzy MPC algorithm and demonstrate the feasibility of the algorithm together with the input-to-state stability of the closed-loop system. Three examples are given to verify the effectiveness of the proposed method and its superiority in saving communication and computing resources while ensuring control performance.

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Publication Details

Journal
IEEE Transactions on Fuzzy Systems
Published
2024-10-28
DOI
https://doi.org/10.1109/tfuzz.2024.3487005
Citations
3
Primary Topic
Advanced Control Systems Optimization
Type
article
Field-Weighted Citation Impact
0.98

Funders

Controls
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article

A Terminal Constraint Set-Dependent Mixed Time/Event-Triggered Approach to Multistep Fuzzy MPC

Chuan‐Ke Zhang, Xiongbo Wan, Fan Wei, Leimin Wang
3 citations
IEEE Transactions on Fuzzy Systems
Advanced Control Systems Optimization
0.98
article

A Terminal Constraint Set-Dependent Mixed Time/Event-Triggered Approach to Multistep Fuzzy MPC

Chuan‐Ke Zhang, Xiongbo Wan, Fan Wei, Leimin Wang
article en
3 citations

Abstract

In this article, the problem of multistep model predictive control (MPC) under a mixed time/event-triggered mechanism (MTEM) is investigated for fuzzy systems with hard constraints. To improve its flexibility in adjusting releases, this MTEM incorporates the information from the fuzzy membership functions and the terminal constraint set (TCS). In the online control unit, the time-triggered way is first implemented to steer the system state into the TCS quickly, and then in the offline control unit, the involved event-triggered pattern plays its role in conserving resources while ensuring the control performance. Two offline optimization problems (OPs) are presented to design the TCS and the approximate robust one step sets, respectively, and an online OP is given to design the control laws to steer the system state into TCS. Based on these three OPs, we propose an MTEM-based multistep fuzzy MPC algorithm and demonstrate the feasibility of the algorithm together with the input-to-state stability of the closed-loop system. Three examples are given to verify the effectiveness of the proposed method and its superiority in saving communication and computing resources while ensuring control performance.

IEEE Transactions on Fuzzy SystemsVol. 33(2)
China University of Geosciences (CN)
National Natural Science Foundation of China, Higher Education Discipline Innovation Project
Climate action
Openalex Percentile: Top 23%
Advanced Control Systems Optimization
0.98
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A Terminal Constraint Set-Dependent Mixed Time/Event-Triggered Approach to Multistep Fuzzy MPC — Chuan‐Ke Zhang, Xiongbo Wan, et al. · IEEE Transactions on Fuzzy Systems (2024) | TGRS Research Map | TGRS