首页|Hybrid Dynamic Variables-Dependent Event-Triggered Fuzzy Model Predictive Control

Hybrid Dynamic Variables-Dependent Event-Triggered Fuzzy Model Predictive Control

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  • 国家科技期刊平台
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This article focuses on dynamic event-triggered mechanism(DETM)-based model predictive control(MPC)for T-S fuzzy systems.A hybrid dynamic variables-dependent DETM is carefully devised,which includes a multiplicative dynamic vari-able and an additive dynamic variable.The addressed DETM-based fuzzy MPC issue is described as a"min-max"optimization problem(OP).To facilitate the co-design of the MPC controller and the weighting matrix of the DETM,an auxiliary OP is pro-posed based on a new Lyapunov function and a new robust posi-tive invariant(RPI)set that contain the membership functions and the hybrid dynamic variables.A dynamic event-triggered fuzzy MPC algorithm is developed accordingly,whose recursive feasibility is analysed by employing the RPI set.With the designed controller,the involved fuzzy system is ensured to be asymptotically stable.Two examples show that the new DETM and DETM-based MPC algorithm have the advantages of reduc-ing resource consumption while yielding the anticipated perfor-mance.

Dynamic event-triggered mechanism(DETM)hybrid dynamic variablesmodel predictive control(MPC)robust positive invariant(RPI)setT-S fuzzy systems

Xiongbo Wan、Chaoling Zhang、Fan Wei、Chuan-Ke Zhang、Min Wu

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School of Automation,China University of Geosciences,the Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems,and the Engineering Research Center of Intelligent Technology for Geo-Exploration,Ministry of Education,Wuhan 430074,China

National Natural Science Foundation of ChinaNational Natural Science Foundation of ChinaHubei Provincial Natural Science Foundation of China111 Project

62073303616733562015CFA010B17040

2024

10.1109/JAS.2023.123957

自动化学报(英文版)
中国自动化学会,中国科学院自动化研究所,中国科技出版传媒股份有限公司

自动化学报(英文版)

CSTPCDEI
ISSN：2329-9266
年,卷(期)：2024.11(3)
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