Data‐driven‐based event‐triggered tracking control for non‐linear systems with unknown disturbance. Issue 14 (30th July 2019)

• Record Type: Journal Article
• Authors: Li, Hai‐Feng; Wang, Ying‐Chun; Zhang, Hua‐Guang
• Is Part Of: IET control theory & applications. Volume 13:Issue 14(2019)
• Page Start: 2197
• Page End: 2206
• Publication Date: 2019-07-30
• Subjects: closed loop systems -- nonlinear control systems -- control system synthesis -- linear systems -- tracking -- observers -- adaptive control -- learning systems; data‐driven‐based event‐triggered -- nonlinear systems -- unknown disturbance -- event‐triggered model‐free adaptive tracking control problem -- unknown bounded disturbance -- general dynamic linearisation model framework -- disturbance input -- event‐triggered‐based model‐free adaptive control algorithm -- input/output measurement data -- disturbance estimator -- event‐triggering mechanism -- observer‐based controller -- disturbance compensation -- tracking error -- system output; Control theory -- Periodicals; Automatic control -- Periodicals; 629.8312
• DOI: 10.1049/iet-cta.2019.0051
• Languages: English
• ISSNs: 1751-8644

Abstract

Abstract : A novel event‐triggered model‐free adaptive tracking control problem is studied for non‐linear systems with unknown bounded disturbance. A general dynamic linearisation model framework with disturbance input is developed and event‐triggered‐based model‐free adaptive control algorithm is designed by using pseudo‐partial derivatives method and input/output measurement data. Owing to the existence of unknown disturbance, a disturbance estimator is designed based on the optimisation criterion technique. Then, a new event‐triggering mechanism with dead‐zone operator is designed to improve the utility of network communication resources without Zeno phenomenon. Then, an observer‐based controller with disturbance compensation is developed, such that the tracking error between the system output and desired output signal converges to a small residual set around the origin. Finally, two simulation examples are provided to show the effectiveness and practicability of the proposed approach.