Optimal model predictive control for disturbance rejection and stability in buck-boost converter and its comparison with classical technique

Abstract

The Buck-Boost converter with pulse width modulator has a large impact on power industry in energy management, specifically for electronic devices. In this paper the sub-optimal model predictive control algorithm applied to Buck-boost converter, which assured robust stability of system. This algorithm based on simpler optimization problems, which can be solved faster, and still have prior robust stability and discard all disturbances. Lyapunov function was used to ensure the constraints of model predictive cost function. In most of DC-DC converters, simple current control method is used for stability of system. Where as in proposed research Model Predictive Control and classical control algorithm are stimulated to achieve stability and control in the Buck-Boost converter. In the last part comparison of both control algorithms is also tackled. The comparison results show that model predictive control is more steadfast and efficient as compared to conventional PI and other control techniques.