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带恒功率负载Buck变换器的模型预测控制 被引量:6

A Model Predictive Control for Buck Converter with Constant Power Load
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摘要 针对含恒功率负载(Constant Power Load,CPL)的Buck DC-DC变换器稳定性和负荷不确定性问题,提出一种含高阶滑模观测器的模型预测(Model Predictive Control,MPC)控制策略.首先,根据MPC理论,构建Buck变换器的目标函数,建立滚动优化跟踪方程并求解最优控制律.其次,构建高阶滑模观测器,提高电压的控制精度并消除抖振及相对阶问题.最后,对其进行小扰动的稳定性分析,建立源、负载侧的等效模型.在CPL与阻性负载投切较为频繁时,与传统双闭环PI调节和MPC控制进行比较,仿真结果表明:在负载变化时,基于高阶滑模观测器的MPC控制具有良好的动态性和鲁棒性且能对母线电压进行精确跟踪与控制. To solve the problems of stability and load uncertainty of Buck DC-DC converters with constant power load(CPL),a model predictive control(MPC)strategy with high-order sliding mode observers is proposed.Firstly,the objective function of the Buck converter is constructed according to MPC theory,and the rolling optimization tracking equation is established to solve the optimal control rate.Secondly,a high-order sliding mode observer is constructed to improve the voltage control accuracy and eliminate chattering and the relative order problem.Finally,the stability analysis of small disturbance is carried out to establish the equivalent model of source and load side.When CPL and resistive load are switched frequently,the simulation results show that the MPC control based on high-order sliding mode observer has good dynamics and robustness,compared with the traditional double closed-loop PI adjustment and MPC control.In addition,it can control and track the bus voltage when the load changes.
作者 陶彩霞 王伟斌 祝曦 高锋阳 王冉冉 杨乔礼 TAO Caixia;WANG Weibin;ZHU Xi;GAO Fengyang;WANG Ranran;YANG Qiaoli(College of Automation and Electrical Engineering,Lanzhou Jiaotong University,Lanzhou 730070,China;Equipment Technology Center of National Railway Administration,Beijing 100891,China)
出处 《湖南大学学报(自然科学版)》 EI CAS CSCD 北大核心 2021年第8期96-102,共7页 Journal of Hunan University:Natural Sciences
基金 国家自然科学基金资助项目(61863022) 兰州市人才创新项目(2017-RC-95) 国家重点研发计划资助项目(2018YFB1201602-06) 兰州交通大学-天津大学联合创新基金资助项目(2020056)。
关键词 BUCK变换器 恒功率负载 模型预测控制 高阶滑模观测器 小信号分析 Buck converter constant power load model predictive control high-order sliding mode observer small signal analysis
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