A Model Predictive Control Considering Parameters and System Uncertainties for Suppressing Low-Frequency Oscillations of Traction Dual Rectifiers

Abstract

Low-frequency oscillation (LFO) overvoltage problems often occur in vehicle-grid coupled systems of high-speed railways. In order to suppress LFO and make up for the problem of weak control effect caused by the large deviation between the model predictive control (MPC) model and the actual system, the uncertainties in parameters and system are enough considered, and a combination of MPC and deviation error correction (DEC) is proposed in this article. First, the error caused by the parameter mismatch, discretization, and sampling process from system noise is analyzed, and then the DEC is designed to compensate for the calculated predicted current in real-time. The control performance between dq decoupling control, MPC, and the new algorithm is compared. Besides, the influence of circuit parameters on the robustness of the system is discussed in detail. Finally, to further verify the effectiveness of the proposed method, a hardware-in-the-loop simulation platform is constructed to test the proposed method. The results show that the algorithm can not only suppress LFO but also effectively reduce the harmonic distortion of the current and overcome the shortcomings of more interference caused by the weak decoupling effect of dq-axis current of MPC in a traction line-side converter.