【摘要】 针对感应电机转速估计过程中,采集数据易受到外界干扰,导致的转速估计值出现较大偏差的问题,提出采用基于模糊自适应卡尔曼滤波的感应电动机无速度传感器控制策略。通过监视理论残差与实际残差的比值,对量测噪声协方差阵进行递推在线修正,使其逐渐逼近真实噪声水平,从而使滤波器执行最优估计,提高转速估计精度。仿真及实验结果表明,提出的改进模糊卡尔曼估计器,对随机的测量噪声具有较强的抑制能力。能够准确估计电机转速,抗差能力较好,满足工程实际需求。更多还原

【Abstract】 In the process of induction motor speed estimation,the data collection is vulnerable to the outside interference easily,which leads to large deviations. The induction motor speed estimation strategy was based on improved self-adaptive fuzzy kalman filter without speed sensor. Online recurrence correction was applied to the measurement noise covariance matrix by monitoring the ratio of the theoretical and actual residual so that it gradually approached the real noise level. After that,the filter can implement the optimal estimation precisely. The simulation and experimental results show that,the improved fuzzy kalman filter suppresses the random measurement noise evidently. The speed of the motor can be estimated precisely. The robustness is good and meets the needs of engineering.更多还原