Design and stability analysis of a robust model predictive control method for voltage regulation in DC-DC buck converters subject to the input and load uncertainties

In controlling DC-DC buck converters, the issue of input uncertainties as well as load uncertainties is one of the important challenges in controller design. This paper addresses this issue as well as presents a new robust control method according to the model predictive control method for regulating the output voltage of the converter. More specifically, this paper presents an H-Infinity MPC controller in which uncertainty in the converter input voltage is also considered during design, as is uncertainty in the load connected to the converter. Based on these assumptions, this controller is designed to have sufficient resistance to the aforementioned uncertainties. Since this controller solves an optimization problem at each time step, it has an optimal response and minimizes a cost function. Therefore, optimization has been made in the generation of the control law and consequently in energy consumption, which is very important in power electronics applications. In addition, unlike other articles on MPC design for this type of converter, this article examines the stability of the desired control method and theoretically ensures the controller’s asymptotic stability by applying the Lyapunov approach. It should be noted that a saturation constraint is included in the control law generated by this controller to ensure the feasibility of the control signal generation. Ultimately, this problem is transformed into an LMI problem, and by solving this problem, the controller design parameters are optimally extracted. Finally, the performance of the suggested method was investigated through a series of practical experiments on a DC-DC buck converter in the laboratory, and the results confirm the effectiveness of this method in regulating the output voltage.