Search - kalman induction motor

Search - kalman induction motor - List

[Other] IEEE DL : 0: Speed estimation of an induction motor drive using an optimized extended Kalman filter
Update : 2025-03-07 Size : 1.03mb Publisher : Tuong Quang
[matlab] kalman DL : 0: it describes the vector control of induction motor with Kalman filter
Update : 2025-03-07 Size : 19kb Publisher : Shashank
[matlab] UKF-and-EKF-filter DL : 3: Matlab交互式多模型UKF和EKF滤波程序（附说明文档） -Matlab interacting multiple model UKF and EKF filtering procedures (with documentation)
Update : 2025-03-07 Size : 302kb Publisher : wangyu
[Embeded-SCM Develop] Simulation DL : 1: 扩展卡尔曼滤波算法(EKF)在电机方面的应用-Extended Kalman filter algorithm (EKF) the application of the motor
Update : 2025-03-07 Size : 135kb Publisher : 冯尧径
[Program doc] Kalman DL : 0: The Extended kalman filter (EKF) has been found wide application in the sensorless control of induction motor (IM) because of its good steady and dynamic behaviour,disturbance resistance, and fast convergence. This paper presents a novel speed sensorless field-oriented control scheme of Induction motor using extended kalman filter.
Update : 2025-03-07 Size : 492kb Publisher : lakhdar
[matlab] AnExtendedKalmanFilterApproachtoRotor DL : 0: An Extended Kalman Filter Approach to Rotor Time Constant Measurement in PWM Induction Motor Drives.rar
Update : 2025-03-07 Size : 654kb Publisher : chadi
[matlab] Kalmanfilterwithinductionmotor DL : 0: this theses of kalman filter using induction motor
Update : 2025-03-07 Size : 1.73mb Publisher : bontha
[ToolBar] KALMAN DL : 0: This file includes kalman filter and induction motor model
Update : 2025-03-07 Size : 55kb Publisher : hakn
[Industry research] estimation-extended-Kalman-filter DL : 0: 针对感应电机扩展卡尔曼滤波器转速估计中难以取得卡尔曼滤波器系统噪声矩阵和测量噪声矩阵最优值的问题，提出了一种基于改进粒子群算法优化的扩展卡尔曼滤波器转速估计方法。算法通过融合遗传算法和粒子群算法的优点，采用可调整的算法模型对粒子群算法进行改进，将改进的粒子群算法对扩展卡尔曼滤波器中的系统噪声矩阵和测量噪声矩阵进行优化处理，将优化后的卡尔曼滤波器应用于感应电机转速估计。- Extended Kalman Filter for induction motor speed estimation problem is difficult to obtain a Kalman filter system noise matrix and the measurement noise matrix optimal value proposed speed estimation method based on improved particle swarm optimization of the extended Kalman filter. By virtue of the genetic algorithm and particle swarm optimization algorithm fusion algorithm using the adjustable model PSO improvements that will improve the PSO extended Kalman filter system noise matrix and the measurement noise matrix optimization process, the optimized Kalman filter is applied to the induction motor speed estimate.
Update : 2025-03-07 Size : 1.15mb Publisher : 周
[Driver Develop] 779890831Kalmanfilterw DL : 0: kalman filter using induction motor
Update : 2025-03-07 Size : 1.73mb Publisher : semko
[File Format] Nouveau WinRAR ZIP archive DL : 0: The paper deals with the application of the Extended Kalman Filter and the Extended Luenberger Observer algorithms for the stator and rotor fault detection of the induction motor fed by PWM inverter. The induction motor conditions are analyzed using estimated rotor and stator-winding resistance.
Update : 2025-03-07 Size : 1.06mb Publisher : marwan_123
[Industry research] Particle Swarm Optimization of an Extended Kalman Filter for speed and rotor flux estimation of an induction motor drive DL : 0: A novel method based on a combination of the Extended Kalman Filter (EKF) with Particle Swarm Optimization (PSO) to estimate the speed and rotor flux of an induction motor driveis presented. The proposed method will be performed in two steps. As a first step, the covariance matrices of state noise and measurement noise will be optimized in an off-line manner by the PSO algorithm. As a second step, the optimal values of the above covariance matrices are injected in our speed-rotor flux estimation loop (on-line).Computer simulations of the speed and rotor-flux estimation have been performed in order to investigate the effectiveness of the proposed method. Simulations and comparison with genetic algorithms (GAs) show that the results are very encouraging and achieve good performances.
Update : 2019-01-08 Size : 650.15kb Publisher : pudn0507@yahoo.fr