Model predictive control of double‑input buck converters


Vol. 21, No. 6, pp. 941-950, Jun. 2021
10.1007/s43236-021-00240-w




 Abstract

The control system of a multiple-input dc–dc converter should ensure the stability of output voltage and reasonably distribute the power of multiple-input voltage sources. In addition, there is mutual coupling between multiple closed control loops, which makes the design of the control system difficult. Based on the ability of model predictive control (MPC) to deal with constraints explicitly, a model predictive control algorithm based on the state-space averaging method is proposed for a double-input buck converter. First, a state-space averaging model of a double-input buck converter is established. Then, considering the power management of two input power supplies, a model predictive controller is designed based on the model by combining the input constraints with the objective function. Both simulation and experimental results show that the system has good steady-state accuracy and fast dynamic response characteristics under the action of model predictive controller.


 Statistics
Show / Hide Statistics

Cumulative Counts from September 30th, 2019
Multiple requests among the same browser session are counted as one view. If you mouse over a chart, the values of data points will be shown.



Cite this article

[IEEE Style]

Y. Chen, Y. Lu, W. Luo, "Model predictive control of double‑input buck converters," Journal of Power Electronics, vol. 21, no. 6, pp. 941-950, 2021. DOI: 10.1007/s43236-021-00240-w.

[ACM Style]

Yunzhu Chen, Yimin Lu, and Wei Luo. 2021. Model predictive control of double‑input buck converters. Journal of Power Electronics, 21, 6, (2021), 941-950. DOI: 10.1007/s43236-021-00240-w.