Precise tracking of highly nonlinear phase-shift full-bridge series resonant inverter via iterative learning control

Abstract

This paper presents iterative learning control of the phase-shift full-bridge series-resonant inverter (PSFB-SRI). It has the merits of high conversion efficiency, medium-to-high power capacity, compact size, and low current–voltage stress on components, but the demerits of highly nonlinear dynamics that varies in a wide range depending on the operating points. The PSFB-SRI also suffers from a grid-voltage disturbance when it operates in grid-connected environment. To overcome these control problems, an iterative learning controller (ILC) supplemented with a proportional controller is developed and applied to the PSFB-SRI. Conventional proportional controller is used to improve the output current tracking performance. The ILC makes use of both previous-cycle and current-cycle learning terms which help the system output to converge to the reference trajectory. It is also simple in structure and easy to implement in practical applications. First-harmonic approximation of the PSFB-SRI model has been conducted and the resulting nonlinear large-signal model was used to construct the developed ILC. A detailed design guideline of the control parameters is provided. Numerical simulations validate the proposed control scheme, and experiments using a 500-W prototype demonstrate its feasibility.