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In this paper, we study the adaptive-critic-based event-driven robust state feedback stabilization for a class of uncertain nonlinear systems. The novel idea lies in bringing adaptive dynamic programming, a self-learning optimization approach, into nonlinear robust control area under uncertain environment and event-triggering framework. Through theoretical analysis, the nonlinear robust stabilization...
In this paper, we investigate the self-learning optimal guaranteed cost control problem of input-affine continuous-time nonlinear systems possessing dynamical uncertainty. The cost function related to the original uncertain system is discussed sufficiently, with the purpose of developing the optimal guaranteed cost and the corresponding feedback control input. Through theoretical analysis, the optimal...
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