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This paper proposes neural network (NN) approximation-based event-triggered control of multiple-input and multiple output (MIMO) nonlinear discrete-time systems in the context of limited communication over the network. Unlike the traditional NN-based discrete-time control, the weights are updated non-periodically and only at the trigger instants. The Lyapunov direct approach is utilized to arrive...
In this paper, a neural network (NN) based adaptive event-triggered control is developed for a single input and single output (SISO) uncertain nonlinear continuous time system. An explicit design of the event-triggered controller using NN approximation and feedback linearization is presented. The controller dynamics are approximated by using two single layer NNs. In addition, novel weight update laws...
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