Parallel Multistep Evaluation With Efficient Data Utilization for Safe Neural Critic Control and Its Application to Orbital Maneuver Systems

Data-driven methods have significantly advanced optimal learning control, but some approaches overlook systematic considerations of data utilization, including safety, efficiency, and error accumulation. To address the neglects in safe neural critic control, this article introduces a parallel multis...

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Vydáno v:	IEEE transaction on neural networks and learning systems Ročník 36; číslo 9; s. 17114 - 17127
Hlavní autoři:	Wang, Jiangyu, Wang, Ding, Ren, Jin, Liu, Derong, Qiao, Junfei
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	United States IEEE 01.09.2025
Témata:	Adaptation models Adaptive dynamic programming (ADP) Aerospace electronics approximate errors Artificial neural networks Cost function Costs Data models data-driven Heuristic algorithms learning systems neural networks (NNs) Optimal control Q-learning safe optimal control Safety
ISSN:	2162-237X, 2162-2388, 2162-2388
On-line přístup:	Získat plný text
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