Hybrid predictive control of a DC–DC boost converter in both continuous and discontinuous current modes of operation

Developing efficient and appropriate modeling and control techniques for DC–DC converters is of major importance in power electronics area and has attracted much attention from automatic control theory. Since DC–DC converters have a complex hybrid nature, recently several techniques based on hybrid modeling and control have been introduced. These techniques have shown better results as compared with conventional averaging-based schemes with limited modeling and control abilities. But the current works in this field have not considered all possible dynamics of the converters in both continuous and discontinuous current modes (CCM, DCM) of operations. These dynamics are results of controlled and uncontrolled switching phenomena in DC–DC converters. This paper proposes a new switching scheme for modeling and controlling a DC–DC boost converter. The converter is represented as a hybrid automaton by considering the all three possible modes. The hybrid automaton is translated into the mixed logical dynamical (MLD) mathematical framework. The switching among these modes is generated by hybrid predictive control method which is calculated by Mixed Integer Quadratic Programming (MIQP). Using the exact model of the converter, the proposed switching algorithm can globally control the converter in all operation regimes, including CCM and DCM operations, considering all constraints in the physical plant, such as maximum inductor current and capacitor voltage limits. The switching algorithm is applied to a real converter circuit, modeled with various parasitic components. Simulation results are provided to show the advantages of the proposed control scheme.