Browsing by Author "Yaramasu, Venkata"

Finite Control Set Model Predictive Control (FCS-MPC), thanks to its simple and powerful concept, has been applied widely to control the multilevel converters. FCS-MPC allows the control of several objectives and can incorporate restrictions, even nonlinear, into the mathematical model of the system under consideration. However, FCS-MPC needs to evaluate all the switching states of the multilevel converter to find the best switching state to be applied in the next sampling time. For higher-level multilevel converters, this iterative action requires computational capacity that is far beyond the digital controller’s capacity in the current market. This paper proposes a new predictive geometric pre-filtering strategy to reduce the iterations and computational burden without affecting the dynamic performance of FCS-MPC. This method consists of a novel pre-filtering stage that uses the predictive model of the system and geometrical properties to find the sector where the reference vector is located and evaluates few vectors that constitute the optimal sector. The proposed method is experimentally validated using a four-level three-cell flying capacitor converter with 512 voltage vectors, obtaining a 64% reduction in the computational burden, while achieving excellent electrical performance indices and maintains the high dynamic performance of the standard FCS-MPC.

This article presents the use of model predictive control (MPC) in multilevel inverters for some applications, such as, first, wind generation and, second, photovoltaics, showing that the particular restrictions of each of them can be very easily included in the control algorithm, which is an important advantage of this technique. Another application is in modular multilevel cascaded converters, where it is demonstrated that MPC can operate with very few calculations and fixed switching frequency. The second part of this article is dedicated to comparing MPC with linear control and pulsewidth modulation for multilevel inverters. The main comparison criteria are the switching losses, the distortion in the load current, and the number of commutations. The main conclusion is that MPC is a competitive alternative to linear control for application in multilevel inverters.

This article presents the use of model predictive control (MPC) in multilevel inverters for some applications, such as, first, wind generation and, second, photovoltaics, showing that the particular restrictions of each of them can be very easily included in the control algorithm, which is an important advantage of this technique. Another application is in modular multilevel cascaded converters, where it is demonstrated that MPC can operate with very few calculations and fixed switching frequency. The second part of this article is dedicated to comparing MPC with linear control and pulsewidth modulation for multilevel inverters. The main comparison criteria are the switching losses, the distortion in the load current, and the number of commutations. The main conclusion is that MPC is a competitive alternative to linear control for application in multilevel inverters.