Fast Indirect Model Predictive Control for Variable Speed Drives

Abstract

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.