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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| Published in: | Neurocomputing (Amsterdam) Vol. 626; p. 129579 |
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| Main Authors: | , , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Elsevier B.V
14.04.2025
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| Subjects: | |
| ISSN: | 0925-2312 |
| Online Access: | Get full text |
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