Online adaptive optimal tracking control for model-free nonlinear systems via a dynamic neural network
This paper presents an online adaptive approximate solution for the optimal tracking control problem of model-free nonlinear systems. Firstly, a dynamic neural network identifier with properly designed weights updating laws is developed to identify the unknown dynamics. Then an adaptive optimal trac...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2023-07-01
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| Series: | Automatika |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/00051144.2023.2170058 |