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In this paper, the continuous-time input-constrained nonlinear H∞ state feedback control under event-based environment is investigated with adaptive critic designs and neural network implementation. The nonlinear H∞ control issue is regarded as a two-player zero-sum game that requires solving the Hamilton–Jacobi–Isaacs equation and the adaptive critic learning (ACL) method is adopted toward the event-based...
In this paper, an approximate online equilibrium solution is developed for an ${N}$ -player nonzero-sum (NZS) game systems with completely unknown dynamics. First, a model identifier based on a three-layer neural network (NN) is established to reconstruct the unknown NZS games systems. Moreover, the identifier weight vector is updated based on experience replay technique which can relax the traditional...
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