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The optimal event-triggered control of nonlinear continuous-time systems by using input and output data is a challenging problem due to system uncertainties, non-availability of state vector and event-based sampled outputs between the plant and the controller. Therefore, a novel reinforcement learning-based approach is proposed to solve time-based near optimal event-triggered control of nonlinear...
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