Generalized Proportional Integral Observer and Kalman-Filter-Based Composite Control for DC-DC Buck Converters

Abstract

There are uncertainties and disturbances in the DC-DC buck converters system; in terms of actual working conditions, they are often very complex, exhibiting a polynomial form of time series. Therefore, a single controller and an observer that can only estimate slowly varying disturbances will lose their effectiveness. The generalized proportional integral observer can generally be used to estimate the disturbances in the polynomial form of time series, but it is usually necessary to select a high gain to achieve the fast convergence of the observer, which makes it sensitive to measurement noise. Therefore, before designing the controller that needs to estimate information, it is necessary to design a new structure that combines an observer and a Kalman filter. The filter is used for noise filtering, and the observer is used for the online reconstruction of disturbances. This can solve the above problems. Then, the whole control strategy is designed based on backstepping control. Theoretical analysis and experimental verification can effectively illustrate the feasibility and superiority of this strategy.