基于参数辨识的推进电机模型参考自适应控制

Model Reference Adaptive Control of Propulsion Motor Based on Parameter Identification

针对模型参考自适应系统(MRAS)对电机参数依赖性强的问题,采用Adaline神经网络对电机参数进行在线参数辨识,并对MRAS中的模型参数进行修正;以船用永磁同步推进电机作为被控对象,使用Adaline神经网络对控制系统中的模型参数进行修正,结果表明,该方法可有效提高MRAS对电机转速和转子信息的估测精度,提高系统的动态和稳态性能。

In view of the strong dependence of the model reference adaptive system(MRAS)on the motor parameters,the Adaline neural network was used to identify the motor parameters on line,and the model parameters in the MRAS were corrected.Taking the marine asynchronous motor as the controlled object,the analysis using Adaline neural network to correct the model parameters in the control system can effectively improve the estimation accuracy of the motor speed and rotor information by MRAS,and improve the dynamic and steady-state performance of the system.