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: In this work, we present and investigate a new framework for the data-driven simulation of electrical circuits based on discrete-continuous optimization. For such an end, we provide a formal ...
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