Incremental value iteration for optimal output regulation of linear systems with unknown exosystems

This paper addresses the optimal output regulation problem for discrete-time linear systems with completely unknown dynamics and unmeasurable exosystem states. The primary objective is to design incremental dataset-based value iteration (VI) reinforcement learning algorithms to derive both state fee...

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Vydané v:	Neurocomputing (Amsterdam) Ročník 626; s. 129579
Hlavní autori:	Jing, Chonglin, Wang, Chaoli, Liang, Dong, Xu, Yujing, Hao, Longyan
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier B.V 14.04.2025
Predmet:	Incremental dataset Optimal control Output regulation Value iteration algorithm Output regulation Incremental dataset Value iteration algorithm Optimal control
ISSN:	0925-2312
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