Abstract
Finite control set model predictive control (FCS-MPC) offers many advantages over more traditional control techniques, such as the ability to avoid cascaded control loops, easy inclusion of constraint, and fast transient response of the control system. This control scheme has been recently applied to several power conversion systems, such as two, three, or more level converters, matrix converters, etc. Unfortunately, because of the lack of the presence of a modulation strategy, this approach produces spread spectrum harmonics which are difficult to filter effectively. This may result in a degraded power quality when compared to more traditional control schemes. Furthermore, high switching frequencies may be needed, considering the limited number of switching states in the converter. This paper presents a novel multiobjective modulated predictive control strategy, which preserves the desired characteristics of FCS-MPC but produces superior waveform quality. The proposed method is validated by experimental tests on a seven-level cascaded H-bridge back-to-back converter and compared to a classic MPC scheme.
Highlights
Model Predictive Control (MPC) has been widely proposed as a promising solution for the control of power converters
Several approaches are possible to implement a Model Predictive Control on a modern power electronic converter, such as Continuous Control Set Model Predictive Control (CCS-MPC), which iteratively calculate the minimum value of the selected cost function [5], or Explicit MPC, which analytically solve the cost function minimization problem [6]–[8]
The converter voltage shows a fixed switching frequency waveform with a THD of approximately 24.5% while the current has a THD of approximately 4.5%, lower than the AC current THD value produced with the standard control approach by Finite Control Set Model Predictive Control (FCS-MPC) (6.3%)
Summary
Model Predictive Control (MPC) has been widely proposed as a promising solution for the control of power converters. Several approaches are possible to implement a Model Predictive Control on a modern power electronic converter, such as Continuous Control Set Model Predictive Control (CCS-MPC), which iteratively calculate the minimum value of the selected cost function [5], or Explicit MPC, which analytically solve the cost function minimization problem [6]–[8]. Both these approaches take advantage of a suitable modulation technique to apply the desired voltage demand to the converter. [20] for the case of multi-objective control, in this paper M2PC is applied and tested for the case of the AC current and DCLink voltage control of a grid connected 7-Level, 3-Phase Cascaded H-Bridge Back-To-Back converter
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