Online actor‐critic learning control with self‐triggered mechanism for nonlinear regulation problems
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Wiley Open Access
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| Format: | Artículo Open Access |
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2024
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| _version_ | 1867018368540737536 |
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| author | Guilong Liu Yongliang Yang Qing Li Hamidreza Modares |
| author_facet | Guilong Liu Yongliang Yang Qing Li Hamidreza Modares Guilong Liu Yongliang Yang Qing Li Hamidreza Modares |
| collection | Wiley Open Access |
| contents | Online actor‐critic learning control with self‐triggered mechanism for nonlinear regulation problems Guilong Liu Yongliang Yang Qing Li Hamidreza Modares International Journal of Robust and Nonlinear Control AbstractIn this article, a novel self‐triggered mechanism is developed to reduce the computation burden and communication bandwidth for the optimal regulation problem of nonlinear dynamical systems. Compared with existing results, this article can avoid continuous measurement of online signals while achieving the performance optimization with closed‐loop system stability guarantee. The self‐triggered mechanism is combined with the actor‐critic structure for performance optimization, where the critic is trained to provide a guideline to improve the actor. The actor‐critic learning is implemented as a hybrid system, where the critic weights update as a continuous flow, and the actor weights are adapted intermittently. The simulation study is conducted to verify the effectiveness of the proposed self‐triggered actor‐critic learning. 10.1002/rnc.7608 http://onlinelibrary.wiley.com/termsAndConditions#vor |
| doi_str_mv | 10.1002/rnc.7608 |
| format | Artículo Open Access |
| id | wiley_oa_10_1002_rnc_7608 |
| institution | Wiley Open Access |
| license_str_mv | http://onlinelibrary.wiley.com/termsAndConditions#vor |
| publishDate | 2024 |
| publisher | Wiley |
| record_format | wiley_oa |
| spellingShingle | Online actor‐critic learning control with self‐triggered mechanism for nonlinear regulation problems Guilong Liu Yongliang Yang Qing Li Hamidreza Modares International Journal of Robust and Nonlinear Control Online actor‐critic learning control with self‐triggered mechanism for nonlinear regulation problems Guilong Liu Yongliang Yang Qing Li Hamidreza Modares International Journal of Robust and Nonlinear Control AbstractIn this article, a novel self‐triggered mechanism is developed to reduce the computation burden and communication bandwidth for the optimal regulation problem of nonlinear dynamical systems. Compared with existing results, this article can avoid continuous measurement of online signals while achieving the performance optimization with closed‐loop system stability guarantee. The self‐triggered mechanism is combined with the actor‐critic structure for performance optimization, where the critic is trained to provide a guideline to improve the actor. The actor‐critic learning is implemented as a hybrid system, where the critic weights update as a continuous flow, and the actor weights are adapted intermittently. The simulation study is conducted to verify the effectiveness of the proposed self‐triggered actor‐critic learning. 10.1002/rnc.7608 http://onlinelibrary.wiley.com/termsAndConditions#vor |
| title | Online actor‐critic learning control with self‐triggered mechanism for nonlinear regulation problems |
| topic | International Journal of Robust and Nonlinear Control |
| url | https://onlinelibrary.wiley.com/doi/10.1002/rnc.7608 |