Optimal Control for Constrained Discrete-Time Nonlinear Systems Based on Safe Reinforcement Learning
Abstract: The state and input constraints of nonlinear systems could greatly impede the realization of their optimal control when using reinforcement learning (RL)-based approaches since the commonly ...
Abstract: Recently Koopman operator has become a promising data-driven tool to facilitate real-time control for unknown nonlinear systems. It maps nonlinear systems into equivalent linear systems in ...
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