Continuous model predictive control of interleaved boost converter with current compensation

An interleaved DC-DC boost converter is widely used in DC power systems such as fuel cell systems or other systems requiring high-power quality for increasing and stabilising the output voltage. The performance of the converter can be affected by the control strategy. In this study, a robustness continuous control set model predictive control (CCS-MPC) for an interleaved DC-DC boost converter is proposed to achieve optimised transient dynamics and steady performance. To deal with unknown load variation and systems uncertainties, an extended Kalman observer is designed to estimate the lumped disturbance, including the load variation and unmodelled part. Based on the disturbance estimation, a dynamic current reference with the disturbance and the integrated voltage error is formulated for the optimal voltage tracking. Also, a prediction-accuracy-enhanced CCS-MPC for a wide range of operation points and multi-parameter disturbance is obtained. The proposed approach could stabilise the output voltage with good robustness under external disturbance and operation point change. Compared with other existing controllers, i.e. a proportional-integral controller, a sliding mode controller, and a finite control set model predictive controller, both the steady and transient performances are validated by a simulation and experimental test bench.