Data-driven event-triggered control for discrete-time T-S fuzzy systems subject to actuator saturation

• Published in: Fuzzy sets and systems Vol. 501; p. 109204
• Main Authors: Wang, Zhen, Chen, Yanbo, Ni, Yanyan, Huang, Xia, Shen, Hao
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.02.2025
• Subjects: Actuator saturation; Data-driven control; Event-triggered control; T-S fuzzy systems; Event-triggered control; Data-driven control; Actuator saturation; T-S fuzzy systems
• ISSN: 0165-0114
• DOI: 10.1016/j.fss.2024.109204

This paper is concerned with data-driven event-triggered control for a class of discrete-time Takagi-Sugeno (T-S) fuzzy systems subject to actuator saturation. Based on the proposed event-triggered mechanism (ETM) and the discrete-time Lyapunov stability theory, a model-based stability criterion for the known T-S fuzzy system is derived first. Subsequently, by leveraging the input-state data collected from each local subsystem, a data-based system representation of unknown T-S fuzzy system is established and a pure data-based stability criterion in the form of linear matrix inequalities (LMIs) is obtained to guarantee that the T-S fuzzy system with unknown system matrices is locally stabilized. Meanwhile, a joint design algorithm for the data-driven fuzzy controllers and the ETM is accomplished. Compared with the other data-driven control methods, the proposed method has the advantages of simplicity and flexibility for some control problems whose stability results satisfy a certain LMI form. At last, the effectiveness of the model-based and data-based results is verified through a numerical example, and the influence of some key factors, such as the number of samples and the noise on control performance is investigated by estimating the inner-approximation of the basin of attraction (BoA) and the outer-approximation of the attractor.