摘要
针对永磁同步电机伺服系统对转动惯量辨识的高精度、收敛的快速性以及系统对扰动影响的鲁棒性要求,提出一种永磁同步电机转动惯量的自适应辨识方法.采用梯度校正参数辨识算法在线辨识惯量值,并设计卡尔曼滤波器实时观测负载转矩状态,将辨识到的惯量值对卡尔曼滤波器的系数矩阵进行实时更新,观测到的转矩值反馈到转矩电流端形成负载扰动的前馈补偿.仿真和实验结果表明,转动惯量在线辨识结果具有较快的收敛速度和较高的辨识精度,同时系统对惯量和负载转矩的变化有较强的抗扰性.
For small inertia permanent magnet synchronous motor speed control system,it requires inertia identification to be of high precision and fast convergence and has strong robustness to disturbance.A adaptive identification method for the moment of inertia was proposed.The gradient correction parameter identification algorithm was applied to identify the inertia online and Kalman filter was designed to observe the load torque.The coefficient matrix of Kalman filter was updated in real time according to the identified value of inertia.The observed value of load torque was feedback to the terminal of torque current to form feedfoward compensation of load disturbance.Simulation and experimental results show that the online identification results of inertia has faster convergence speed and higher precision,and meanwhile the system has strong disturbance resistance to the changes of inertia and load torque.
出处
《华中科技大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2015年第S1期122-126,共5页
Journal of Huazhong University of Science and Technology(Natural Science Edition)
基金
国家高技术研究发展计划资助项目(2011AA04A105)
山东省自然科学基金资助项目(ZR2014EL032)
关键词
电机
梯度校正参数辨识算法
惯量辨识
卡尔曼滤波器
负载转矩估计
实验
motor
gradient correction parameter identification algorithm
inertia identification
Kal-man filter
load torque observation
experiment
