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In this paper, we investigate the event-triggered output tracking problem for a class of nonlinear systems with unknown time-varying parameters. To reduce the communication burden, an event-triggered adaptive control method is proposed by introducing hyperbolic tangent functions in the controller to compensate for the effects of the time-varying parameters. New estimation laws are developed to estimate the bounds of time-varying parameters, where no any prior information about the bounds of unknown time-varying parameters is required. An additional term is introduced in the parameter estimation law to compensate for the effects of unknown time-varying parameters. The proposed control scheme can effectively reduce the communication burden while maintain global stability of the closed-loop system, which means that all the signals are bounded. And the tracking error converges towards an adjustable set, which can be exactly expressed with the user-defined parameters. Simulation results are given to show the performance of the proposed method.

In this paper, we focus on the design of output feedback controller for a class of discrete-time nonlinear systems combined with event-triggered control approach. The designed event-triggered threshold is related to the output signal, which further reduces the tracking error. Besides, by co-designing backstepping control method and the event-triggered strategy, the corresponding assumptions for input-to-state stable (ISS) with respect to the measurement errors can be removed. The stability analysis result shows that all signals in the closed-loop system are bounded and the tracking error is bounded by a small constant depending on event-triggered threshold parameter. Simulation results show the performance and effectiveness of the designed controller.

In practice, modelling errors caused by high-order unmodelled dynamics and external disturbances are unavoidable. How to ensure the robustness of an adaptive controller with respect to such modelling errors is always a critical concern. In this study, the authors consider the design of event-triggered robust adaptive control for a class of discrete-time uncertain systems which involve such modelling errors and also are allowed to be non-minimum phase. Unlike some existing event-triggered control schemes, the developed controllers do not require that the measurement errors meet the corresponding input-to-state stable condition. Global stability of the closed-loop system which means that all the signals are bounded is established in the presence of unmodelled dynamics and disturbances. Besides, in contrast to existing robust adaptive schemes, the designed adaptive controller does not involve parameters related to unmodelled dynamics and disturbances which are difficult to be chosen for ensuring such stability. An example is given to verify the effectiveness of the proposed control strategy.

In this paper, an event-triggered adaptive control approach is proposed to control a class of discrete-time uncertain nonlinear systems, based on the backstepping adaptive control and the fixed threshold strategy. The designed event-triggered adaptive control can guarantee that all the closed-loop signals are globally bounded and the tracking error converges to a compact set. Simulation results are given to illustrate the performance and effectiveness of the proposed method.