Research on predictive sliding mode control strategy for horizontal vibration of ultra-high-speed elevator car system based on adaptive fuzzy
| Autor: | Hong Wang, Mingqin Zhang, Ruijun Zhang, Lixin Liu |
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| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: | |
| Zdroj: | Measurement + Control, Vol 54 (2021) |
| Druh dokumentu: | article |
| ISSN: | 0020-2940 00202940 |
| DOI: | 10.1177/00202940211003926 |
| Popis: | In order to effectively suppress horizontal vibration of the ultra-high-speed elevator car system. Firstly, considering the nonlinearity of guide shoe, parameter uncertainties, and uncertain external disturbances of the elevator car system, a more practical active control model for horizontal vibration of the 4-DOF ultra-high-speed elevator car system is constructed and the rationality of the established model is verified by real elevator experiment. Secondly, a predictive sliding mode controller based on adaptive fuzzy (PSMC-AF) is proposed to reduce the horizontal vibration of the car system, the predictive sliding mode control law is achieved by optimizing the predictive sliding mode performance index. Simultaneously, in order to decrease the influence of uncertainty of the car system, a fuzzy logic system (FLS) is designed to approximate the compound uncertain disturbance term (CUDT) on-line. Furthermore, the continuous smooth hyperbolic tangent function (HTF) is introduced into the sliding mode switching term to compensate the fuzzy approximation error. The adaptive laws are designed to estimate the error gain and slope parameter, so as to increase the robustness of the system. Finally, numerical simulations are conducted on some representative guide rail excitations and the results are compared to the existing solution and passive system. The analysis has confirmed the effectiveness and robustness of the proposed control method. |
| Databáze: | Directory of Open Access Journals |
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