Double-Vector Model-Free Predictive Control Method for Voltage Source Inverter With Visualization Analysis
Nan Jin, Mo Chen, Leilei Guo, Yanyan Li, Yafei Chen
Abstract
Strong parameter dependence and large current ripple are two shortcomings that obstruct the development of model predictive control for voltage source inverters (VSIs). To solve these problems, in this article,a double-vector model-free predictive control (MFPC) method for VSI with visualization analysis is proposed. First, the ultralocal model of the VSI is established and a full-order sliding model observer is designed to estimate the lumped disturbance. MFPC is achieved with enhanced parameter robustness. Then, a double-vector MFPC method is further proposed. By applying two vectors per control period, the current ripple is reduced significantly. A detailed visualization analysis method is proposed, which verifies the effectiveness of the proposed double-vector MFPC method in theory. Besides, the proposed visualization analysis method has the potential to be used to analyze the effectiveness of other types of multivector model predictive control method with different cost functions. Detailed comparative experimental studies verify the effectiveness of the proposed double-vector MFPC method.