Model Predictive Pulse Pattern Control

Abstract

Industrial applications of medium-voltage drives impose increasingly stringent performance requirements, particularly with regard to harmonic distortions of the phase currents of the controlled electrical machine. An established method to achieve very low current distortions during steady-state operation is to employ offline calculated optimized pulse patterns (OPP). Achieving high dynamic performance, however, proves to be very difficult in a system operated by OPPs. In this paper, we propose a method that combines the optimal steady-state performance of OPPs with the very fast dynamics of trajectory tracking control. A constrained optimal control problem with a receding horizon policy, i.e., model predictive control (MPC), is formulated and solved. Results show that the combination of MPC with OPPs satisfies both the strict steady-state as well as the dynamic performance requirements imposed by the most demanding industrial applications. The estimation of the fundamental components of the machine variables separately from their respective harmonic components is not required. As a result, complicated structures such as observers can be avoided, contrary to state-of-the-art methods. A further advantage of the MPC method is the use of a receding horizon policy, which provides feedback and a high degree of robustness.