Data-Driven Koopman Based System Identification for Partially Observed Dynamical Systems with Input and Disturbance
The identification of dynamical systems from data is essential in control theory, enabling the creation of mathematical models that accurately represent the behavior of complex systems. However, real-world applications often present challenges such as the unknown dimensionality of the system and lim...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2024-12-01
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| Series: | Sci |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2413-4155/6/4/84 |
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