无轴承异步电机转子磁场定向MRAS转速辨识

为了准确辨识无轴承异步电机的转速,提出一种改进转子磁链估算电压模型。以改进转子磁链估计模型为基础,构建了无轴承异步电机的转子磁场定向模型参考自适应(MRAS)无速度传感器矢量控制系统,并通过Matlab/Simulink进行了系统仿真分析。仿真结果表明:基于所提出的转子磁链改进模型,可有效避免纯积分环节初值和累计误差等影响,获得较高的转速辨识精度。所提出的转子磁链辨识模型和MRAS无速度传感器矢量控制系统是有效和可行的。     

改进的MRAS无速度传感器VC控制系统仿真研究

针对交流传动系统中异步电机的精确控制和速度辨识等问题,在Simulink软件环境中,对基于模型参考自适应系统(MRAS)无速度传感器的异步电机的矢量控制(VC)系统进行了研究。系统采用按转子磁场定向的VC对异步电机进行控制,通过MRAS辨识算法估算电机转速,由Popov超稳定定理对磁链偏差进行收敛。由于速度辨识算法中电压模型的纯积分环节会引起误差积累和漂移问题,故采用改进积分型转子磁链估算模型来解决这一问题。仿真结果表明,速度辨识方法能够准确推算出电机转速,控制系统动态响应快、稳态静差小、抗负载扰动能力强,具有良好的动静态控制性能。     

基于MRAS无速度传感器的DTC系统Simulink仿真研究

异步电机的精确控制和速度辨识是交流传动系统中重要问题;文中在Simulink软件环境中构建了基于MRAS无速度传感器的异步电机DTC系统;该系统中采用DTC对异步电机进行控制,定子磁链采用在全速范围内有效的u-n模型观测器来估计,电机转速采用MRAS辨识算法来估算;由于速度辨识算法中电压模型的纯积分环节会引起的误差积累和漂移问题,采用改进积分型转子磁链估算模型来解决;仿真结果表明了文中转速辨识方法能准确推算出电机转速,所设计的控制系统动态响应快、稳态静差小、抗负载扰动能力强,具有良好的静、动态控制性能.     

基于DSP的无速度传感器交流异步电机矢量控制系统设计

为提高交流异步电机控制系统的可靠性和适应性,本文设计了基于DSP的无速度传感器异步电机矢量控制系统。根据异步电机转子磁场定向控制的基本方程式建立了改进电压型转子磁链估算模型,并且采用PI自适应速度估算法来估计转速,同时采用电压空间矢量法实现对异步电机的控制。     

定子电流串联模型无速度传感器异步电机控制

针对基于传统电压电流模型并联结构模型参考自适应的无速度传感器异步电机矢量控制系统中,电压模型因存在纯积分环节而带来的积分初始误差和直流偏移问题,提出一种基于定子电流的串联模型无速度传感器矢量控制方案.方案对传统电压模型和电流模型进行改造,消除了纯积分环节及其带来的不利影响.同时对该串联模型的结构进行了说明,并详细推导了其自适应律.采用全阶磁链观测器估计定子磁链并用于定子磁链定向下的矢量控制,全阶磁链观测器由于含有反馈矩阵鲁棒性和灵活性更强.最后,基于MATLAB搭建了完整的系统仿真模型.仿真结果表明,所提出的控制方案在全速范围内均有良好的动、静态性能.     

基于MRAS的交流异步电机变频调速系统研究

依据矢量控制的基本原理和方法,在基于转子磁场定向的旋转坐标系下,采用Madab／Simulink模块构建了一个具有转矩、磁链闭环的交流异步电机矢量控制系统仿真模型。在此基础上,应用模型参考自适应方法,对无速度传感器矢量控制系统的转速估计进行研究,并针对常规速度辨识器中的基准模型易受积分初值和漂移影响的问题,对传统的MRAS方法进行改进,并对其进行建模仿真。仿真结果表明,该设计具有较强的可行性,且其推算转速能够很好地跟踪实测转速。     

异步电机调速系统转速辨识的研究

针对异步电机转速辨识过程存在积分初始值误差和直流偏置问题,为提高无速度传感器异步电机调速系统中转速观测值的准确性,采用一种以反电动势为电机输出量的模型参考自适应系统(MRAS)法.基于MATLAB/SIMULINK平台,对以转子磁链和反电动势作为电机输出量的MRAS法进行建模与仿真研究.仿真结果表明,基于反电动势的MRAS法比基于转子磁链的MBAS法能准确有效地辨识电机的实际速度,更能满足现代电机调速系统的性能要求.     

无速度传感器直接转矩控制系统仿真研究

在直接转矩控制系统中,采用传统的纯积分器(U-I模型)作为磁链观测器存在低速时定子磁链难以准确观测的问题,采用速度传感器测量转速存在增加系统的复杂性、降低系统可靠性和鲁棒性并增加系统成本和维护要求的问题。文章提出了利用闭环磁链观测器取代传统的纯积分器来观测定子磁链、依据模型参考自适应理论(MRAS)构造速度观测器来实现速度估计的方法。应用该方法,在Matlab仿真工具中构建了异步电动机无速度传感器直接转矩控制系统的仿真模型,仿真结果证明了该方法的合理性和有效性。     

基于左逆系统的无轴承异步电机无速度传感器运行

为了解决无轴承异步电机运行控制中转速检测的问题,实现对其高性能控制,提出了一种基于左逆系统的无速度传感器控制方法.建立了转速与转矩绕组定子电流的子系统,并证明了该子系统是左可逆的,将左逆系统与该子系统串联,便可实现对转速的观测.应用该方法建立了无轴承异步电机无速度传感器的矢量控制系统,并进行仿真研究.结果表明,该方法能在无轴承异步电机全速范围内准确观测出转速,实现无速度传感器方式的稳定悬浮运行.     

基于DSP的无速度传感器控制系统研究

为了实现快速准确地观测电机转速,在直接转矩控制系统的基础上,采用了基于电机转子磁链的MRAS速度辨识方法对系统进行速度估计,并通过DSP实现无速度传感器的直接转矩控制.利用Matlab对系统进行仿真分析,仿真结果表明,该方案的设计方法正确可行.     

采用MRAS速度观测器的异步电机无电压传感器DTC研究

为提高系统的抗干扰能力,降低运行成本,提出无电压传感器控制策略,通过逆变器的导通状态和直流侧电压估算三相定子电压,采用模型参考自适应系统（ MRAS）方法设计速度观测器,基于异步电机数学模型得到转子磁链的两种模型,根据合适的自适应机构得到精确的实际转速,实时调节模型参数,该控制方法简单,保持较高的控制精度。最后通过实验验证了控制策略的可行性。     

An MRAS method for sensorless control of induction motor over a wide speed range

This paper addresses the problem of wide speed range sensorless control of induction motor.The proposed method is based on model reference adaptive system (MRAS),in which the current model serves as the adjustable model,and a novel hybrid model integrating the modified voltage model (MVM) and high-frequency signal injection method (HFSIM) are established to serve as the reference model.The HFSIM works together with MVM to improve the performance of the rotor speed and rotor flux position estimation at low speed,whereas at high speed,the MVM acts alone.In addition,a rotor resistance online estimation scheme is proposed to update the rotor resistance contained in the adjustable model and to ensure the estimation accuracy further.Experimental results show that the proposed MRAS method is very effective from low to high speed range,including zero speed.     

永磁同步电机系统的无速度传感器研究

为了提高永磁同步电机系统的抗干扰能力,提出一种无速度传感器方法,用于速度辨识.将滑模(SM)变结构控制与模型参考自适应系统(MRAS)方法相结合,选取电机本体作为参考模型,利用逆变器输出的电压和电流,构建基于磁链方程的可调模型,利用两模型误差运用SM变结构方法辨识速度.在Matlab仿真平台对无速度传感器方法进行了分析,研究结果表明:所提出的无速度传感器方法具有较好的动静态性能,可以实现对速度的准确辨识.     

基于滑模模型参考自适应观测器的无速度传感器三相永磁同步电机模型预测转矩控制

针对三相永磁同步电机(PMSM)驱动系统,基于滑模变结构模型参考自适应(MRAS)技术,提出了一种新颖的无速度传感器模型预测转矩控制(MPTC)策略.采用滑模变结构模型参考自适应方法构造电机转速观测器,以改善速度估计精度并提高系统鲁棒性;利用模型预测转矩控制策略,以达到减小转矩和磁链纹波并提高系统控制性能的目的.仿真结果表明:就滑模MRAS观测器与MRAS观测器比较而言,基于前者的PMSM无速度传感器MPTC系统比基于后者的PMSM无速度传感器MPTC系统具有较强的鲁棒性和更好的动态性能;就MPTC与直接转矩控制(DTC)和磁场定向控制(FOC)比较而言,采用前者策略的无速度传感器电机驱动系统能够降低逆变器开关频率、减少相电流总谐波失真(THD),从而提高系统可靠性.     

Sensorless Inverter‐Fed Compressor Drive System Using Back‐EMF Estimator with PIDNN Torque Observer

A saliency back‐EMF estimator with a proportional–integral–derivative neural network (PIDNN) torque observer is proposed in this study to improve the speed estimating performance of a sensorless interior permanent magnet synchronous motor (IPMSM) drive system for an inverter‐fed compressor. The PIDNN torque observer is proposed to replace the conventional proportional–integral–derivative (PID) torque observer in a saliency back‐EMF estimator to improve the estimating performance of the rotor flux angle and speed. The proposed sensorless control scheme use square‐wave type voltage injection method as the start‐up strategy to achieve sinusoidal starting. When the motor speed gradually increases to a preset speed, the sensorless drive will switch to the conventional saliency back‐EMF estimator using the PID observer or the proposed saliency back‐EMF estimator using the PIDNN observer for medium and high speed control. The theories of the proposed saliency back‐EMF rotor flux angle and speed estimation method are introduced in detail. Moreover, the network structure, the online learning algorithms and the convergence analyses of the PIDNN are discussed. Furthermore, a DSP‐based control system is developed to implement the sensorless inverter‐fed compressor drive system. Finally, some experimental results are given to verify the feasibility of the proposed estimator.     

Grid-connected vector-controlled slip-ring induction machine drive with out speed sensor

A speed estimation method is presented in this paper for a grid-connected doubly-fed slip-ring induction machine drive. The proposed method is formulated with reactive power based model reference adaptive system (MRAS). The method does not require the estimation of stator/rotor flux. So, the integrator related problems at synchronous speed are overcome. Also, the estimation method is independent of stator and rotor resistance variation. Extensive simulation results are presented to validate the technique.     

基于DSP的自适应速度辨识直接转矩控制系统研究

异步电机直接转矩控制能产生快速且良好的鲁棒性响应,采用自适应磁链观测器,取代传统的积分器,构造了新型的速度估计器,并结合模糊控制器,实现对定子磁链准确观测和系统无速度传感器运行状态。基于DSP(TMS320LF2407A)核心芯片建立数字化控制系统。仿真与实验表明,该系统对电机定子磁链的观测精度高,转速估算准确,尤其在低速下能保持很高的性能。     

Sensorless direct torque control of an induction motor by a TLS-based MRAS observer with adaptive integration

This article presents a new speed and flux estimation algorithm for high-performance direct torque control (DTC) induction motor drives based on model reference adaptive systems (MRAS) observers using linear artificial neural networks (ANNs). Two completely new improvements of MRAS speed and flux observers are presented here: the first is a solution to the open-loop integration problem in the reference model, based on the voltage model of the induction machine, by means of a new adaptive neural integrator, the second is the employment of a new adaptation law in the ANN adaptive model, based on the total least-squares (TLS) technique. In particular, the adaptive neural integrator is based on two adaptive noise filters which completely cancel any DC drift present in the voltage or current signals to be integrated. This neural integrator does not need any a priori training of its two only neurons, adapting itself on-line. With regard to the ANN-based adaptive model, since the most suitable least-square technique to be used for training is the TLS technique, here the neuron is trained on-line by means of a TLS EXIN algorithm which is the only neural network able to solve a TLS problem recursively. Also the TLS EXIN algorithm does not require any a priori training, since it adapts itself recursively on-line. Moreover, to improve the dynamical performances of the speed loop of the drive, the adaptive model has been used as predictor, i.e. without any feed-back between its outputs and its inputs. The sensorless algorithm has been verified experimentally both on the classic DTC technique and on the DTC-SVM (space vector modulation), by adopting a proper test set-up. The speed observer has been tested in the most challenging operating conditions. The experimental results show that the dynamical performances of the sensorless drive are comparable or even better than those obtained with the corresponding DTC drives with encoders as for the medium to high-speed ranges. As for low-speed ranges, the presented sensorless DTC algorithm outcomes the performance presented in the literature for MRAS systems, thus permitting to have an accurate estimation equal or better than that obtainable with more complex observers. Finally, experimental results show that the MRAS speed observer is robust to load torque perturbations and permits zero-speed operation at no-load conditions.