Iterative Learning-Based Adaptive Hysteresis Current Control Method for the Power Electronics Converters

Abstract

This paper proposes an iterative learning-based adaptive hysteresis current control (HCC) method. The HCC method is a nonlinear current control method and does not require controller design. This method is preferred because of its fast dynamic response and simplicity. In conventional HCC, the switching states are determined by comparing the measured current with the reference current using a constant hysteresis band. However, conventional HCC has disadvantages such as variable switching frequency and the difficulty of digital implementation.HCC can easily be implemented with analog circuits,but it is difficult to implement with digital circuits. Because continuous comparison of the inductor current is required, the processor load increases. The HCC method is not widely used in industrial applications because of the variable switching frequency. In this paper, a new adaptive HCC method is developed for constant switching frequency. The proposed method is based on iterative learning control (ILC). The ILC is used to compensate for non-ideal effects such as variations in the DC link voltage and the inductance value, the slope of the current reference, the sampling period, and the dead time. Therefore, the problems of the HCC method are removed, and the advantages of the analog-based HCC method are provided with digital control. The proposed control method is implemented on a single-phase voltage source inverter (VSI) prototype. Theoretical analyses and simulations are verified with experimental results.