基于布谷鸟搜索算法的交错并联双向DC-DC变换器模型预测控制

Wenwen Sun, Qihong Chen, Liyan Zhang
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引用次数: 5

摘要

为了提高交错并联双向DC-DC变换器的响应速度和可靠性,提出了一种基于布谷鸟搜索算法的约束模型预测控制(MPC)。首先,以降压模式为例,根据变换器在不同两种开关状态下的等效电路模型,建立预测模型。然后建立代价函数来评价变换器的性能。引入布谷鸟搜索优化算法求解模型预测控制优化问题,提高了求解速度。最后,利用MATLAB/Simulink进行仿真,并对模型预测控制、PI控制的结果进行了分析和比较。仿真结果表明,CS-MPC变换器具有较好的动态响应性能和稳态性能,证明了该算法的可行性和有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Model Predictive Control Based On Cuckoo Search Algorithm of Interleaved Parallel Bi-directional DC-DC Converter
In order to improve the response speed and reliability of the interleaved parallel bi-directional DC-DC converter, a constrained model predictive control(MPC) based on cuckoo search algorithm is proposed. Firstly, take the buck mode for example, the predictive model is established according to the equivalent circuit model of the converter under different two switch states. Then the cost function is built to evaluate the performance of the converter. Otherwise, the cuckoo search optimization algorithm is introduced and used to solve model predictive control optimization problem so that the speed solution was improved. Finally, the simulation was carried out by MATLAB/Simulink and the results of the model predictive control, PI control was analyzed and compared. The simulation result show that the CS-MPC converter has better dynamic response performance and steady state performance, and the algorithm is feasible and effective.
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