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Model predictive control of double-input buck converters

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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.

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Acknowledgements

This work was supported in part by the Key Program of Natural Science Foundation of Guangxi Province of China under Grant 2018GXNSFDA281037 and in part by the National Natural Science Foundation of China under Grant 51667005.

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  1. School of Electrical Engineering, Guangxi University, Nanning, China

    Yunzhu Chen, Yimin Lu & Wei Luo

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  1. Yunzhu Chen
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  2. Yimin Lu
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  3. Wei Luo
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Correspondence to Yimin Lu.

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Chen, Y., Lu, Y. & Luo, W. Model predictive control of double-input buck converters. J. Power Electron. 21, 941–950 (2021). https://doi.org/10.1007/s43236-021-00240-w

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  • DOI: https://doi.org/10.1007/s43236-021-00240-w

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