Fast-Predictive Optimal Control of NPC Multilevel Converters

Abstract

The development of high-processing-capability microprocessors allows the implementation of new digital control methods for neutral-point-clamped (NPC) multilevel converter in power-electronic applications. This paper presents a new predictive digital control method for multilevel converters, called “fast predictive.” This method computes the optimal vector using the NPC three-phase multilevel dynamic model equations just once in each control cycle, while current predictive methods need 27 calculations. The closest vector to the optimal vector is found by minimizing the distance between each one of the 27 available vectors to the optimal vector. Space vector modulation could be also used. The obtained performance is similar to the predictive optimal control that uses the converter model to find all the 27 responses of the multilevel and then searches for the vector that minimizes control errors. Relative to predictive optimal control, the fast predictive improves digital processing speed by at least 150% in multilevel converters with 27 vectors. This speed improvement would allow multilevel converters with five or higher number of levels (125 instead of 27 vectors) to be controlled using the same sampling frequency of the three-level inverter. The fast-predictive controller is used in a multilevel rectifier with near-unity power factor to enforce the ac currents. Fast predictive control is also used in the rectifier dc voltage to reduce sensitivity of the dc voltage to dc load disturbances. The simulation and experimental results show that the fast-predictive controller is able to control the ac currents of a three-phase multilevel rectifier, achieving nearly 1.5% total harmonic distortion while balancing the capacitors' dc voltages. The use of predictive control to regulate the dc voltage shows an improvement of approximately 7% compared to a proportional-integral controller.