Hybrid modeling and control of switching DC-DC converters via MLD systems

Abstract

Modeling and control of DC-DC converters is a non trivial problem in power electronics. Such converters exhibit both autonomous and non-autonomous switching phenomena which are commonly modeled by general classes of hybrid systems. This paper addresses the modeling and control of a DC-DC buck converter via Mixed Logical Dynamical (MLD) systems and hybrid predictive control based on Mixed Integer Quadratic Programming. The main contribution of the paper is the novel concept of Forward MLD as opposed to the classical modeling approach that we call Backward MLD. The advantage of the proposed method is to introduce a prediction of the continuous behavior at a the switching instant. This results in a more accurate model and allowing to reduce by one step the prediction horizon necessary to compute the optimal control. The proposed technique reduces the complexity of the resulting MIQP program. The transient and steady state performances of the closed-loop control system over a wide range of operating points show satisfactory operation of the proposed modeling and control scheme.