Ultra-local model Predictive Current Control of phase-shifted full-bridge Based on Kalman Filter

The paper proposes an ultra-local model predictive current control strategy to improve the stability and robustness of the phase-shifted full-bridge(PSFB) converter under parameter mismatch causing by operating conditions changes. Firstly, analysis is conducted to show the effect of circuit parameter mismatch on the anticipated current estimate in the PSFB converter circuit. Secondly, an ultra-local model is built for the PSFB converter by analyzing the total disturbance of the circuit. Ultimately, the unknown nonlinear total disturbance part of the model is estimated using a Kalman filter, which is then integrate in model predictive control algorithm to enhance the control effect. The experiments on a semi-physical simulation platform demonstrate that the proposed strategy effectively suppresses the steady-state error caused by parameter mismatch when compared to the conventional predictive current control scheme. It increases system resilience and anti-disturbance capabilities in the event of parameter disturbances, as well as its capacity to adapt efficiently to changes in working conditions.