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Real-Time Measurement-Driven Reinforcement Learning Control Approach for Uncertain Nonlinear Systems
The paper introduces an interactive machine learning mechanism to process the measurements of an uncertain, nonlinear dynamic process and hence advise an actuation strategy in real-time. For concept demonstration, a trajectory-following optimization
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bf928e1ee7b57a04ac17e7d2501bbe88
http://arxiv.org/abs/2303.08745
http://arxiv.org/abs/2303.08745
