An Efficient Model Predictive Control for Three-Level Converters With the Function of Parameter Identification

doi:10.11985/2018.04.001

Abstract

Abstract:

Three-level PWM converters have been widely used in the industrial field especially in the high voltage and high power applications. In practical applications, the parameters of the system may change due to the variation of working environment and temperature, which will deteriorate the control performance. Model predictive control (MPC) has the merits of multivariable control and flexibility to handle various constraints, which receives wide study and attention in the area of three-level converter control. The existing MPC for three-level PWM converters requires many calculations and accurate inductance value to select the optimal voltage vector, which has the problems of huge computation and poor robustness. To solve these problems, an efficient MPC method is proposed in the paper, which greatly reduces the computational burden when selecting the optimal voltage vector. By further introducing the online inductance identification technique, the system robustness is improved. Both simulation and experimental results confirm the effectiveness of the proposed methods in terms of steady-state performance, dynamic response and robustness against parameter variation.

Key words: Three-level PWM converters, model predictive control, inductance parameters identification, recursive least-squares algorithm

CLC Number:

TM351

Zhang Yongchang,Cai Qian,Peng Yubin,Yang Haitao. An Efficient Model Predictive Control for Three-Level Converters With the Function of Parameter Identification[J]. Journal of Electrical Engineering, 2018, 13(4): 1-10.

Figures/Tables 11

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参数	数值
电感电阻R/Ω	0.3
电感L/mH	10
直流母线电容C/μF	470
负载R_L/Ω	97
线电压U_N /V	150
电网频率f /Hz	50
采样频率f_s /kHz	20
直流母线电压U_dc /V	300
权重系数K_r	100
增益常数K	0.395 2