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In fixed time interval, event-triggered tracking control for nonlinear systems with unknown coexistence uncertainties has been investigated in this paper. The control scheme can handle unknown virtual control gains, external disturbances and nonsymmetric input dead zone. The unknown nonlinearities are identified by using neural networks. In the traditional backstepping design process, a bound estimation strategy is developed to design the adaptive parameters. Based on the adaptive estimation tactic, the severe coexistence uncertainties caused by the unknown virtual control gains, external disturbances, nonsymmetric input dead zone and identify errors can be estimated online, such that the robust performance of the system can be effectively elevated. Note that, the priori knowledge of the boundary are not required for the proposed bound estimation mechanism, and the control gains and the slope of dead zone have been relaxed to be completely unknown. In view of fixed time stability design scheme, the singularity phenomenon for the differential of virtual control signal has been conquered by employing the piecewise functions method. Furthermore, to decrease the resource consumption, a dynamic event triggered rule is used to cut down the data sampling and communication. And two practical examples are used to verify the effectiveness.
Zhai et al. (Tue,) studied this question.