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This paper develops a novel neural network (NN) based finite-horizon approximate optimal control of nonlinear continuous-time systems in affine form when the system dynamics are complete unknown. First an online NN identifier is proposed to learn the dynamics of the nonlinear continuous-time system. Subsequently, a second NN is utilized to learn the time-varying solution, or referred to as value function,...
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