Event-Triggered Model Reference Adaptive Control for Linear Partially Time-Variant Continuous-Time Systems With Nonlinear Parametric Uncertainty

• 成果类型: Article
• 署名作者: Jiang, Yi; Shi, Dawei; Fan, Jialu; Chai, Tianyou; Chen, Tongwen
• 署名单位: Northeastern University - China; Northeastern University - China; City University of Hong Kong; Beijing Institute of Technology; University of Alberta
• 刊物名称: IEEE TRANSACTIONS ON AUTOMATIC CONTROL
• ISSN/ISSBN: 0018-9286
• DOI: 10.1109/TAC.2022.3169847
• 发表日期: 2023
• 页码: 1878-1885
• 关键词: Adaptation models; uncertainty; Closed loop systems; Adaptive control; Nonlinear systems; automation; computational modeling; Event-triggered adaptive control; linear partially time-variant continuous-time (CT) systems; model reference adaptive control (MRAC); nonlinear state-dependent matched parametric uncertainty

摘要

In this work, we develop an event-triggered adaptive control approach for solving the state tracking problem of linear partially time-variant continuous-time systems with the nonlinear state-dependent matched parametric uncertainty under unknown system dynamics. First, an event-triggered model reference adaptive controller is designed, which is composed of event-triggered adaptive laws based on the event-updated information and an event-triggering condition depending on the state tracking error of the controlled plant and reference model. Then, the state-tracking error and the error between control parameters and ideal ones of the resulting closed-loop system are proven to be uniformly ultimately bounded. Moreover, based on the designed event-triggering condition, the interevent time between two consecutive triggering points is proven to have a positive lower bound. Finally, a simulation example is provided to show the effectiveness of the proposed approach.