基于粒子群优化的感应电机模糊扩展卡尔曼滤波器转速估计方法

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摘要为了减弱固定的先验噪声模型对扩展卡尔曼滤波器（EKF）状态估计的影响,提出一种基于粒子群优化的感应电机模糊EKF（PFEKF）转速估计方法。通过将粒子群优化（PSO）算法引入模糊控制器,监视实际残差与理论残差的偏离程度,自适应选择模糊调整因子,在线递推修正测量噪声协方差矩阵的加权值,使其逐渐逼近真实噪声水平,从而使滤波器进行优化估计,并减小外部干扰和时变测量噪声对系统性能的影响。仿真和实验结果验证了基于PSO的感应电机模糊EKF转速估计方法的正确性与有效性。

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	尹忠刚
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关键词 ：粒子群优化, 模糊, 扩展卡尔曼滤波, 感应电机, 转速估计

Abstract：This paper presents a speed estimation method of particle swarm optimization fuzzy extended Kalman filter (PFEKF) for induction motors, to weaken the impacts of priori measurement noise model on the estimation accuracy of extended Kalman filter (EKF). The proposed algorithm modifies the measurement noise covariance of EKF recursively and chooses a fuzzy factor to make its noise model close to real noise model adaptively, based on PSO fuzzy controller which monitors the degree of divergence (DOD) parameters. Accordingly the optimal estimation is realized, and the impacts of system performance under gross external error and unknown measurement noises are weakened. Simulation and experimental results verify the proposed method for induction motors.

Key words： Particle swarm optimization fuzzy extended Kalman filter induction motor speed estimation

收稿日期: 2014-04-07 出版日期: 2016-04-01

PACS:

TM343

基金资助:国家自然科学基金资助项目（51307139）

通讯作者: 尹忠刚男,1982年生,博士,副教授,主要研究方向为高性能交流调速系统与电力电子变换器数字化控制。E-mail: smart860@163.com

作者简介: 肖鹭男,1989年生,硕士研究生,主要研究方向为高性能变频调速系统控制策略。E-mail: zephyrxiao@126.com

引用本文:

尹忠刚, 肖鹭, 孙向东, 刘静, 钟彦儒. 基于粒子群优化的感应电机模糊扩展卡尔曼滤波器转速估计方法[J]. 电工技术学报, 2016, 31(6): 55-65. Yin Zhonggang, Xiao Lu, Sun Xiangdong, Liu Jing, Zhong Yanru. A Speed Estimation Method of Fuzzy Extended Kalman Filter for Induction Motors Based on Particle Swarm Optimization. Transactions of China Electrotechnical Society, 2016, 31(6): 55-65.

链接本文:

https://dgjsxb.ces-transaction.com/CN/Y2016/V31/I6/55

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