A Computationally Efficient FCS-MPC Method Without Weighting Factors for NNPCs With Optimal Duty Cycle Control

In this paper, a computationally efficient finite control-set model predictive control (FCS-MPC) method without weighting factors is proposed for nested neutral point-clamped converters (NNPCs) with optimal duty cycle control. The aim of this paper is to design a modification of the FCS-MPC scheme that improves the steady-state performance, as well as to avoid the weighting factors selection while remaining computationally feasible. First, in order to improve the calculation efficiency, a simplified computational method is proposed by introducing the Lyapunov principle into the design of sector distribution method based on space vector modulation technique, and eliminates unwanted switching states. Second, aiming at improving the steady-state control performance, an optimal duty cycle control technique is incorporated into the proposed FCS-MPC strategy to determine the time duration of the selected voltage vector. In that sense, a new FCS of candidate voltage vectors with different duty cycles are synthesized without sacrificing the simplicity of the control structure. Besides, in order to avoid the selection of weighting factors, the proposed method replaces the single cost function with simplified multiobjective optimization strategy based on a fuzzy-decision-making method. Finally, the performance of the proposed strategy for NNPCs is evaluated by simulation studies in various operating conditions.

[1]  Ralph Kennel,et al.  A Computationally Efficient Quasi-Centralized DMPC for Back-to-Back Converter PMSG Wind Turbine Systems Without DC-Link Tracking Errors , 2016, IEEE Transactions on Industrial Electronics.

[2]  Bin Wu,et al.  Finite Control-Set Model Predictive Control (FCS-MPC) of Nested Neutral Point-Clamped (NNPC) Converter , 2015, IEEE Transactions on Power Electronics.

[3]  Marco Rivera,et al.  Model Predictive Control for Power Converters and Drives: Advances and Trends , 2017, IEEE Transactions on Industrial Electronics.

[4]  Wei Xie,et al.  Deadbeat Model-Predictive Torque Control With Discrete Space-Vector Modulation for PMSM Drives , 2017, IEEE Transactions on Industrial Electronics.

[5]  Srinivasa Rao Sandepudi,et al.  Enhanced weighting factor selection for predictive torque control of induction motor drive based on VIKOR method , 2016 .

[6]  Enrico Santi,et al.  FPGA-Based Model Predictive Controller for Direct Matrix Converter , 2016, IEEE Transactions on Industrial Electronics.

[7]  Marian P. Kazmierkowski,et al.  State of the Art of Finite Control Set Model Predictive Control in Power Electronics , 2013, IEEE Transactions on Industrial Informatics.

[8]  Jan Fredrik Hansen,et al.  History and State of the Art in Commercial Electric Ship Propulsion, Integrated Power Systems, and Future Trends , 2015, Proceedings of the IEEE.

[9]  Fateh Krim,et al.  Fuzzy-Logic-Based Switching State Selection for Direct Power Control of Three-Phase PWM Rectifier , 2009, IEEE Transactions on Industrial Electronics.

[10]  Marco Rivera,et al.  A Computationally Efficient Lookup Table Based FCS-MPC for PMSM Drives Fed by Matrix Converters , 2017, IEEE Transactions on Industrial Electronics.

[11]  Heng Nian,et al.  Flexible grid connection technique of voltage source inverter under unbalanced grid conditions based on direct power control , 2014, 2014 IEEE Energy Conversion Congress and Exposition (ECCE).

[12]  Srinivasa Rao Sandepudi,et al.  Finite control set predictive torque control for induction motor drive with simplified weighting factor selection using TOPSIS method , 2017 .

[13]  Jiangchao Qin,et al.  Predictive Control of a Modular Multilevel Converter for a Back-to-Back HVDC System , 2013, IEEE Transactions on Power Delivery.

[14]  José R. Espinoza,et al.  Predictive Torque and Flux Control Without Weighting Factors , 2013, IEEE Transactions on Industrial Electronics.

[15]  Zhanfeng Song,et al.  A Simplified Finite-Control-Set Model-Predictive Control for Power Converters , 2014, IEEE Transactions on Industrial Informatics.

[16]  Yongchang Zhang,et al.  Model Predictive Control and Direct Power Control for PWM Rectifiers With Active Power Ripple Minimization , 2016 .

[17]  Fang Zheng Peng,et al.  Reactive power and harmonic compensation based on the generalized instantaneous reactive power theory for three-phase power systems , 1996 .

[18]  Changliang Xia,et al.  Torque Ripple Minimization of Predictive Torque Control for PMSM With Extended Control Set , 2017, IEEE Transactions on Industrial Electronics.

[19]  Dan Wang,et al.  Cascade-Free Fuzzy Finite-Control-Set Model Predictive Control for Nested Neutral Point-Clamped Converters With Low Switching Frequency , 2019, IEEE Transactions on Control Systems Technology.

[20]  Wei Xu,et al.  Finite-Control-Set Model Predictive Torque Control With a Deadbeat Solution for PMSM Drives , 2015, IEEE Transactions on Industrial Electronics.

[21]  Leopoldo G. Franquelo,et al.  Guidelines for weighting factors design in Model Predictive Control of power converters and drives , 2009, 2009 IEEE International Conference on Industrial Technology.

[22]  M. P. Kazmierkowski,et al.  High-Performance Motor Drives , 2011, IEEE Industrial Electronics Magazine.

[23]  Bin Wu,et al.  A New Power Conversion System for Megawatt PMSG Wind Turbines Using Four-Level Converters and a Simple Control Scheme Based on Two-Step Model Predictive Strategy—Part I: Modeling and Theoretical Analysis , 2014, IEEE Journal of Emerging and Selected Topics in Power Electronics.

[24]  Dylan Dah-Chuan Lu,et al.  Finite-State Predictive Torque Control of Induction Motor Supplied From a Three-Level NPC Voltage Source Inverter , 2017, IEEE Transactions on Power Electronics.

[25]  Dylan Dah-Chuan Lu,et al.  A Simplified Finite-State Predictive Direct Torque Control for Induction Motor Drive , 2016, IEEE Transactions on Industrial Electronics.

[26]  Dan Wang,et al.  Improved finite-control-set model predictive control for active front-end rectifiers with simplified computational approach and on-line parameter identification. , 2017, ISA transactions.

[27]  Josep M. Guerrero,et al.  General Unified Integral Controller With Zero Steady-State Error for Single-Phase Grid-Connected Inverters , 2016, IEEE Transactions on Smart Grid.