基于改进蚁群算法的永磁同步电动机参数辨识策略研究  

Research on parameter identification strategy of permanent magnet synchronous motor based on improved ant colony optimization

作　　者：陶涛 林荣文[1] Tao Tao;Lin Rongwen(College of Electrical Engineering and Automation,Fuzhou University,Fuzhou 350108)

机构地区：[1]福州大学电气工程与自动化学院,福州350108

出　　处：《电气技术》2020年第6期13-18,共6页Electrical Engineering

摘　　要：永磁同步电动机是一个非线性、高耦合的动态系统,其转动惯量对于以其为主要执行元件的交流伺服系统控制器参数自整定有直接影响,转动惯量的准确辨识对伺服系统的快速稳定运行有重要作用。针对传统的惯量辨识策略存在的辨识精度低、时效性差的缺点,本文将模型参考自适应辨识策略和改进蚁群算法相结合,提出了一种新的惯量辨识方法,利用蚁群算法较强的全局搜索能力和快速收敛性,使得参考模型逼近可调模型,惯量估计值得以逼近真实值,仿真结果表明,相比于传统方法,该方法惯量辨识精度高,辨识速度快,能满足伺服系统较高的调速性能要求。Permanent magnet synchronous motor is a nonlinear,highly coupled dynamic system.Its moment of inertia has a direct impact on the parameter self-tuning of the AC servo system with PMSM as the main actuator.The accurate identification of moment of inertia plays an important role in the fast and stable operation of the servo system.In view of the shortcomings of traditional inertia identification strategy,such as low identification accuracy and poor timeliness,this paper combines model reference adaptive identification strategy with improved ant colony algorithm,and proposes a new inertia identification method.Using the strong global search ability and fast convergence of ant colony algorithm,the reference model approaches the adjustable model,and the inertia estimation approaches the real value.The simulation results show that compared with the traditional method,this method has high inertia identification accuracy,fast identification speed and can meet the high speed regulation performance requirements of the servo system.

关 键 词：伺服系统 转动惯量 参数辨识 改进蚁群算法 

分 类 号：TM341[电气工程—电机]