RISE-backstepping-based robust control design for induction motor drives

Yosra Rkhissi-Kammoun*, Jawhar Ghommam, Moussa Boukhnifer, Fai Al Mnif

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)


Purpose - This paper aims to address the speed and flux tracking problem of an induction motor (IM) drive that propels an electric vehicle (EV). A new continuous control law is developed for an IM drive by using the backstepping design associated with the Robust Integral Sign of the Error (RISE) technique. Design/methodology/approach - First, the rotor field-oriented IM dynamic model is derived. Then, a RISE-backstepping approach is proposed to compensate for the load torque disturbance under the assumptions that the disturbances are C2 class functions with bounded time derivatives. Findings - The numerical validation results have presented good control performances in terms of speed and flux reference tracking. It is also robust against load disturbances rejection and IM parameters variation compared to the conventional Field-Oriented Control design. Besides, the asymptotic stability and the boundedness of the closed-loop signals is guaranteed in the context of Lyapunov. Originality/value - A very relevant strategy based on a conjunction of the backstepping design with the RISE technique is proposed for an IM drive. The approach remains simple and can be scaled to different applications.

Original languageEnglish
Pages (from-to)906-930
Number of pages25
JournalCOMPEL - The International Journal for Computation and Mathematics in Electrical and Electronic Engineering
Issue number4
Publication statusPublished - 2017


  • Asymptotic stability
  • Backstepping
  • Control systems
  • Control theory
  • Electrical vehicle
  • Induction motor
  • Lyapunov theory
  • Non-linear control systems
  • Numerical simulation
  • RISE control

ASJC Scopus subject areas

  • Applied Mathematics
  • Electrical and Electronic Engineering
  • Computer Science Applications
  • Computational Theory and Mathematics


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