Adaptive Model Predictive Control of an Interleaved Boost Converter Using Real-Time Updated Model

Abstract

To optimize the voltage regulation performance and enhance the robustness, an adaptive model predictive controller is proposed in this article for an interleaved dc–dc boost converter. The predictive model is constructed by linearizing the nonlinear equations of the converter at the current operating point. A novel parameter update mechanism is developed based on the static model, which enables fast and accurate identification of the model parameters, thus the control law can guarantee the desired control performance in the wide operating range. Based on the adaptive model, a disturbance observer is constructed to correct the model predictions and mitigate parameter uncertainties. Then an explicit control law is derived by solving the optimization problem offline, and the stability analysis is carried out using the linear control theory. Finally, the effectiveness of the proposed method is verified by both simulation and experimental results.