Adaptive super-twisting sliding mode control for maximum power point tracking of PMSG-based wind energy conversion systems

Darkhan Zholtayev, Matteo Rubagotti, Ton Duc Do

Research output: Contribution to journalArticlepeer-review

24 Citations (Scopus)


This paper proposes a super-twisting adaptive sliding mode control law for maximum power point tracking of wind energy conversion systems based on permanent magnet synchronous generators (PMSGs). The employed sliding mode control algorithm can be considered an effective solution, as it retains the robustness properties of classical sliding mode control methods in the presence of disturbances and parameter uncertainties; at the same time, it provides chattering reduction via gain adaptation and generation of second-order sliding modes. In our work, a nonlinear multi-input multi-output tracking control problem is solved to maximize the captured power. Simulation results are presented using real wind speed data, and discussed for the proposed controller and four other sliding mode control solutions for the same problem, in the presence of variations of stator resistance, stator inductance and magnetic flux linkage. The proposed controller achieves the best trade-off between tracking performance and chattering reduction among the five considered solutions: compared to a standard sliding mode control algorithm, it reduces the amount of chattering from two to five orders of magnitude, and the steady-state error on PMSG rotor velocity of one order of magnitude. Also, it reduces the above-mentioned steady-state error of four orders of magnitude with respect to a previously-proposed linear quadratic regulator based integral sliding mode control law for the same system.

Original languageEnglish
Pages (from-to)877-889
Number of pages13
JournalRenewable Energy
Publication statusPublished - Jan 2022


  • Permanent magnet synchronous generators
  • Sliding mode control
  • Wind energy conversion systems

ASJC Scopus subject areas

  • Renewable Energy, Sustainability and the Environment


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