Gradient-Based Predictive Pulse Pattern Control

Abstract

This paper presents a control scheme that combines the optimal steady-state performance of optimized pulse patterns (OPPs) with the fast dynamics of direct model predictive control (MPC). Due to inherent challenges that relate to the utilization of OPPs in a closed-loop setting, OPPs are traditionally used in slow control loops. As a result, the associated dynamic performance of the drive system is considerably poor. To overcome this, in this work, a direct MPC algorithm is employed to manipulate the OPPs in a fast, yet optimal, manner. Specifically, the MPC algorithm takes advantage of the knowledge of the stator current evolution—as described by its gradient—within the prediction horizon. Subsequently, a constrained optimization problem with a receding horizon is solved to compute the optimal modification of the offline-computed OPP such that superior steady-state and dynamic performance is achieved. The effectiveness of the proposed method is verified based on a variable speed drive system, which consists of a two-level inverter and a low-voltage induction machine.