电励磁同步电机全速域自适应模型预测控制

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摘要针对传统模型预测控制（MPC）单一权值系数存在的局部最优问题,提出一种全速域自适应模型预测控制（FSA-MPC）方法。该方法采取离线初选和在线优化两个步骤完成权值系数配置,保证了MPC中滚动优化的控制品质。首先,建立电励磁同步电机的离散预测模型,并以加权求和的形式配置价值函数;其次,分析不同权值系数对各项优化目标的影响,统计得出了一个理想最优权值系数覆盖区域;最后,考虑到离线穷举法配置权值系数的不完备性,引入在线自适应机制进行在线修正。基于55kW样机验证了全速区域范围内FSA-MPC的可行性,并与传统MPC进行了对比分析,结果表明FSA-MPC可在全速域范围内保持优异的控制效果。

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	刘向昕
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	殷实

关键词 ：模型预测控制, 全速域自适应, 权值系数, 自适应优化

Abstract：The complicated multi-objective optimization problem exists when traditional model predictive control (MPC) is applied to the electrical excitation synchronous motor speed regulating system. Therefore, this paper proposes a full speed adaptive MPC (FSA-MPC) method. This method includes two primary steps of offline and online optimization, which ensures the quality of the rolling optimization. First of all, this paper establishes a discrete prediction model of electrical excitation synchronous motor, and designs the cost function weighted sum. Then the effects of different weighting coefficients on the optimization objects are analyzed. An ideal optimal weighting coefficient of coverage area by statistics is obtained. Finally, due to the incomplete configuration of weighting coefficients by offline exhaustive method, the online adaptive mechanism for online correction is introduced. The feasibility of FSA-MPC at full speed area is verified based on a 55kW prototype. Compared with the traditional MPC, the results show that the FSA-MPC achieves excellent control effects at full speed range.

Key words： Model predictive control full speed adaptive weighting coefficient adaptive optimization

出版日期: 2017-03-01

PACS:

TM461

基金资助:中央高校基本科研业务费专项资金资助项目（2012LWB73）

通讯作者: 刘向昕男,1955年生,博士研究生,研究方向为电子与电力传动。E-mail: cumt_wxq@126mcom

作者简介: 曹晓冬男,1990年生,博士研究生,研究方向为电力电子系统模型预测控制。E-mail: cumtcxd@126.com

引用本文:

刘向昕, 曹晓冬, 谭国俊, 吴轩钦, 殷实. 电励磁同步电机全速域自适应模型预测控制[J]. 电工技术学报, 2017, 32(4): 112-122. Liu Xiangxin, Cao Xiaodong, Tan Guojun, Wu Xuanqin, Yin Shi. Full Speed Adaptive Model Predictive Control for Electrical Excitation Synchronous Motor. Transactions of China Electrotechnical Society, 2017, 32(4): 112-122.

链接本文:

https://dgjsxb.ces-transaction.com/CN/Y2017/V32/I4/112

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