• DocumentCode
    1290813
  • Title

    Intelligent double integral sliding-mode control for five-degree-of-freedom active magnetic bearing system

  • Author

    Lin, Faa-Jeng ; Chen, Shih-Yuan ; Huang, Ming-Shi

  • Author_Institution
    Dept. of Electr. Eng., Nat. Central Univ., Chungli, Taiwan
  • Volume
    5
  • Issue
    11
  • fYear
    2011
  • Firstpage
    1287
  • Lastpage
    1303
  • Abstract
    This study presents a decentralised intelligent double integral sliding-mode control (IDISMC) system, which consists of five IDISMCs, to regulate and stabilise a fully suspended five-degree-of-freedom (DOF) active magnetic bearing (AMB) system. The system structure and drive system with differential driving mode (DDM) are introduced first. Then, the decoupled dynamic model of the five-DOF AMB is analysed for the design of the decentralised control. Moreover, a decentralised integral sliding-mode control (ISMC) system is designed based on the decoupled dynamic model to control the five-DOF AMB considering the existences of the uncertainties. Furthermore, since the control characteristics of the five-DOF AMB are highly non-linear and time varying, the decentralised IDISMC system is proposed to further improve the control performance of the five-DOF AMB. In each IDISMC, the adopted double integral sliding surface reinforces the control law with the integral (I) control feature. In addition, the control gains of the IDISMC can be adjusted on-line and the system uncertainty can also be observed simultaneously by using of a modified proportional-integral-derivative neural network (MPIDNN) observer. Thus, the proposed IDISMC combines the merits of the ISMC, adaptive control and neural network (NN). Finally, the experimental results illustrate the validities of the proposed control systems using various operating conditions.
  • Keywords
    adaptive control; decentralised control; electric drives; machine control; magnetic bearings; neurocontrollers; three-term control; uncertain systems; variable structure systems; MPIDNN observer; adaptive control; control characteristics; control law; control performance; decentralised IDISMC system; decentralised intelligent double integral sliding-mode control; decoupled dynamic model; differential driving mode; drive system; five-DOF AMB system; five-degree-of-freedom active magnetic bearing system; modified proportional-integral-derivative neural network; system structure; system uncertainty;
  • fLanguage
    English
  • Journal_Title
    Control Theory & Applications, IET
  • Publisher
    iet
  • ISSN
    1751-8644
  • Type

    jour

  • DOI
    10.1049/iet-cta.2010.0237
  • Filename
    5975317