Data-driven sliding mode control for partially unknown nonlinear systems
Fuente:
arXiv
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| Autori principali: | , , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| _version_ | 1866908301880459264 |
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| author | Lan, Jianglin Zhao, Xianxian Sun, Congcong |
| author_facet | Lan, Jianglin Zhao, Xianxian Sun, Congcong |
| contents | This paper presents a new data-driven control for multi-input, multi-output nonlinear systems with partially unknown dynamics and bounded disturbances. Since exact nonlinearity cancellation is not feasible with unknown disturbances, we adapt sliding mode control (SMC) for system stability and robustness. The SMC features a data-driven robust controller to reach the sliding surface and a data-driven nominal controller from a semidefinite program (SDP) to ensure stability. Simulations show the proposed method outperforms existing data-driven approaches with approximate nonlinearity cancellation. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2403_16136 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Data-driven sliding mode control for partially unknown nonlinear systems Lan, Jianglin Zhao, Xianxian Sun, Congcong Systems and Control This paper presents a new data-driven control for multi-input, multi-output nonlinear systems with partially unknown dynamics and bounded disturbances. Since exact nonlinearity cancellation is not feasible with unknown disturbances, we adapt sliding mode control (SMC) for system stability and robustness. The SMC features a data-driven robust controller to reach the sliding surface and a data-driven nominal controller from a semidefinite program (SDP) to ensure stability. Simulations show the proposed method outperforms existing data-driven approaches with approximate nonlinearity cancellation. |
| title | Data-driven sliding mode control for partially unknown nonlinear systems |
| topic | Systems and Control |
| url | https://arxiv.org/abs/2403.16136 |