Disturbance Preview Approach Based on Enhanced Reduced-Order GPI Observer for DC-DC Buck Converters

This paper investigates performance issues of DC-DC buck converters based on discrete-time model predictive control (MPC) under the conditions of multiple-source interference. It aims to enhance prediction accuracy by employing an active disturbance rejection strategy. Firstly, a Reduced-Order generalized proportional integral observer (ROGPIO) is used to estimate unmeasurable aggregate disturbances within the system. To address the issue of increased output voltage ripple caused by rapid convergence with high gains in ROGPIO, a self-enhancing topology is proposed by combining a Kalman filter (KF) with ROGPIO. This improvement enables the system to effectively filter noise, provide accurate signals, and overcome the potential increase in voltage ripple associated with traditional ROGPIO. Finally, disturbance estimation and prediction are integrated into output prediction, and a disturbance preview enhanced robust control law is obtained by solving a receding horizon optimization problem. Experimental results demonstrate the feasibility of the proposed approach.