Identification of Load Inertia Parameters in Permanent Magnet Synchronous Linear Servo Systems Using Extended Kalman Filtering
Addressing the issue of resonance frequency identification in permanent magnet synchronous linear motors with flexible loads, this paper proposes the calculation of the resonance frequency by employing a nonlinear Extended Kalman Filter ( EKF) for load inertia identification. This study initially establishes a dual-mass system model, then implements the EKF algorithm on the system model, with a focus on formulating the state and measurement equations within the dual-mass system model. An EKF dual-mass system simulation model is developed, and simulation experiments are conducted. Finally, the EKF algorithm is applied to the permanent magnet synchronous linear motor system for identification, achieving load inertia identification for permanent mag-net synchronous linear motors with flexible loads. Simulation validation demonstrates the capability to identify a 0.1 kg∗m2 load in-ertia within 0.1 seconds. During inertia transformation, the identification results can be promptly corrected in real-time, with an i-dentification error of less than 1％.
permanent magnet synchronous linear motorextended kalman filteringload inertiaparameter identification
万方数据
维普
