Practical Tracking Via Adaptive Event-Triggered Feedback for Uncertain Nonlinear Systems

• Published in: IEEE transactions on automatic control Vol. 64; no. 9; pp. 3920 - 3927
• Main Authors: Huang, Yaxin, Liu, Yungang
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.09.2019; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Actuators; Adaptive systems; Adaptive technique; Computer architecture; Control systems design; Controllers; event-triggered control; global tracking; Nonlinear systems; parametric uncertainties; Sampling; Sampling error; Tracking; Uncertainty; Upper bound
• ISSN: 0018-9286; 1558-2523
• DOI: 10.1109/TAC.2019.2891411

This paper addresses the event-triggered tracking for a class of uncertain nonlinear systems. Essentially different from the related works, the nonlinear systems allow serious (parametric) uncertainties, while no further a priori information, excepting some coarse information, is required on the reference signal to be tracked. This makes event-triggered control more challenging, partially because the sampling error cannot be precisely bounded any more. As main contributions of this paper, new adaptive event-triggered tracking schemes are proposed for the systems in two event-triggering architectures with different roles of the event-triggering mechanism on the information transmitting and control computing/updating. Much importantly, a dynamic gain is incorporated in either scheme not only to counteract the serious uncertainties, but also to overcome the bad influence of the sampling error. Based on the dynamic gain, two adaptive event-triggered controllers are designed with distinct event-triggering mechanisms, respectively. Particularly, to ensure application flexibility, one of the triggering mechanisms is rendered relatively independent of the controller signal. The designed event-triggered controllers are shown to achieve the practical tracking for the systems, that is, the prespecified arbitrary tracking accuracy can be guaranteed (a comparable objective to that via continuous-time control), while avoiding infinitely fast sampling/execution.