Adaptive complementary sliding-mode control for thrust active magnetic bearing system

Faa Jeng Lin*, Syuan Yi Chen, Ming Shi Huang

*此作品的通信作者

研究成果: 雜誌貢獻期刊論文同行評審

27 引文 斯高帕斯(Scopus)

摘要

An adaptive complementary sliding-mode control (ACSMC) system with a multi-input-multi-output (MIMO) recurrent Hermite neural network (RHNN) estimator is proposed to control the position of the rotor in the axial direction of a thrust active magnetic bearing (TAMB) system for the tracking of various reference trajectories in this study. First, the operating principles and dynamic model of the TAMB system using a linearized electromagnetic force model is derived. Then, a conventional sliding-mode control (SMC) system is designed for the tracking of various reference trajectories. Moreover, a complementary sliding-mode control (CSMC) system is adopted to reduce the guaranteed ultimate bound of the tracking error by half while using the saturation function as compared with the SMC. Furthermore, since the system parameters and the external disturbance are highly nonlinear and time-varying, the ACSMC is proposed to further improve the control performance and increase the robustness of the TAMB system. In the ACSMC, the MIMO RHNN estimator with estimation laws is proposed to estimate two complicated dynamic functions of the system on-line. In addition, a robust compensator is proposed to confront the minimum approximated errors and achieve the robustness. Finally, some experimental results for the tracking of various reference trajectories show that the control performance of the ACSMC is significantly improved comparing with the SMC and CSMC.

原文英語
頁(從 - 到)711-722
頁數12
期刊Control Engineering Practice
19
發行號7
DOIs
出版狀態已發佈 - 2011 七月
對外發佈

ASJC Scopus subject areas

  • 控制與系統工程
  • 電腦科學應用
  • 電氣與電子工程
  • 應用數學

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