Fast Indirect Model Predictive Control for Variable Speed Drives

Wei Tian, Qifan Yang, Xiaonan Gao, Petros Karamanakos, Xingqi Yin, Ralph Kennel, Marcelo Lobo Heldwein

Research output: Contribution to journalArticlepeer-review


This article focuses on indirect model predictive control (MPC) for variable speed drives, such as induction and synchronous machine drives. The optimization problem underlying indirect MPC is typically written as a standard constrained quadratic programming (QP) problem, which requires a QP solver to find the optimal solution. Although many mature QP solvers exist, solving the QP problems in industrial real-time embedded systems in a matter of a few tens of microseconds remains challenging. Instead of using the complex general-purpose QP solvers, this article proposes a geometrical method for isotropic machine drives and an analytical method for anisotropic machine drives to find the optimal output voltage. This is done by examining and subsequently exploiting the geometry of the associated optimization problems. Both methods are simple, and easy to implement on industrial control platforms. The effectiveness of the proposed geometrical and analytical methods is demonstrated by experimental results for an induction machine drive and an interior permanent-magnet synchronous machine drive, respectively.

Original languageEnglish
Pages (from-to)14475-14491
Number of pages17
JournalIEEE Transactions on Power Electronics
Issue number11
StatePublished - 1 Nov 2023


  • Induction machine (IM)
  • interior permanent-magnet synchronous machine (IPMSM)
  • model predictive control (MPC)
  • quadratic programming (QP)


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