Model Predictive Direct Power Control for PWM Rectifiers Based on Online Parameter Identification

Abstract

Model predictive control guarantees superior control performance with accurate model parameters. However, the prediction accuracy may be deteriorated due to the parameter uncertainties and parameter mismatches. In this paper, an improved model predictive direct power control (MPDPC) based on online parameter identification is proposed for pulse width modulation (PWM) rectifiers with fully unknown parameters. In this paper, an adaptive Parameter estimation update law is proposed to identify the unknown parameters. Two-stage filters are applied to ensure the convergence of estimation errors. In the control part, an MPDPC based on the identified parameters is proposed to realize the desired power control objectives. Simulation results under various parameter conditions are simulated to show the effectiveness of the proposed method.