Event-Based Model Reference Adaptive Tracking

In this article, the event-triggered asymptotic tracking problem is considered for an uncertain linear system by using the model reference adaptive control approach. Different from the existing results, the control signal and the parameter estimator are event-triggered simultaneously for transmission, which brings difficulties in achieving the objective of both asymptotic stability and Zeno-free behavior. To overcome the difficulties, a novel dynamic event-triggered scheme is proposed, where the adaptive parameters coupled with a time-varying term are designed. With the proposed event-triggered adaptive controller, the achievement of the objective is ensured theoretically. Then by adding a constant to the novel event-triggered condition, a positive lower bound for all interevent intervals can be obtained. Finally, simulation results are presented to illustrate the effectiveness of the proposed method.