Disturbance observer-based integral fuzzy sliding-mode control and its application to wind turbine system

Sounghwan Hwang, Jin Bae Park, Young Hoon Joo

Research output: Contribution to journalArticlepeer-review

34 Citations (Scopus)


In this study, a disturbance observer-based integral fuzzy sliding-mode control methodology for a wind turbine system with a non-linear permanent magnet synchronous generator (PMSG) is proposed using the Takagi–Sugeno fuzzy model. To reduce the hardware cost of the fuzzy controller membership function, an imperfect premise matching condition is considered. Considering the matched disturbance, and an external disturbance acting on the system, a novel integral fuzzy sliding surface is proposed based on a fuzzy disturbance observer (FDOB). Therefore, various forms of external disturbances can be estimated using the FDOB. In addition, a sufficient condition for guaranteeing the asymptotic stability of the sliding motion with H performance is proposed using a Lyapunov function and derived using a linear matrix inequality format. Furthermore, a reachability problem of the system states over the proposed sliding surface is derived through an appropriate Lyapunov function. Finally, the simulations for a wind turbine system using a PMSG are implemented to verify the effectiveness of the proposed method as compared with previous studies.

Original languageEnglish
Pages (from-to)1891-1900
Number of pages10
JournalIET Control Theory and Applications
Issue number12
Publication statusPublished - 2019 Aug 13

Bibliographical note

Funding Information:
This work was partially supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2016R1A6A1A03013567) and by Korea Electric Power Corporation (grant no. R17XA05-17).

Publisher Copyright:
© The Institution of Engineering and Technology 2019

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Human-Computer Interaction
  • Computer Science Applications
  • Control and Optimization
  • Electrical and Electronic Engineering


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