Dynamic Event Triggering Control for Matching Uncertain Systems

In this paper, a new dynamic event-triggering (DET) adaptive dynamic programming (ADP) is developed to deal with the robust control problem of an uncertain system with the matching condition. First, this paper transforms the robust control problem of a nonlinear robust system into the optimal control problem of a nominal system by designing a suitable cost function. In order to improve resource utilization, the DET scheme has been developed. A single critic network approximates the unknown optimal cost function. Moreover, it is proven that the neural networks (NNs) weight estimation error and network weight are bounded. Finally, an experiment demonstrates that the DET algorithm has the best resource-saving effect while guaranteeing learning performance.