UKF在永磁直线同步电动机无位置传感器控制中的应用

Unscented卡尔曼滤波器(UKF)在许多非线性估计问题中是一种估计性能优于扩展卡尔曼滤波器(EKF)的非线性滤波方法。然而在永磁直线同步电动机无位置传感器控制中,UKF是否能提高永磁直线电动机位置与速度的估计性能却尚未见研究。针对永磁直线同步电动机进给系统的特点,建立用于位置与速度估计器的永磁直线同步电动机进给系统模型,提出永磁直线同步电动机无位置传感器控制系统。通过仿真和试验对UKF的估计性能进行评估,并与EKF进行了比较。仿真及试验结果表明,UKF在估计性能与EKF相当, 然而UKF的计算量却比EKF大,使得在高速永磁直线同步电动机无位置传感器控制这一特定问题上,EKF比UKF更有效。     

MODEL-BASED FAULT DIAGNOSIS OF INDUCTION MOTORS USING NON-STATIONARY SIGNAL SEGMENTATION

Effective detection and diagnosis of incipient faults is desirable for on-line condition assessment, product quality assurance and improved operational efficiency of induction motors running off the power supply mains. In this paper, an empirical model-based fault diagnosis system is developed for induction motors using recurrent dynamic neural networks and multiresolution signal processing methods. In addition to nameplate information required for the initial set-up, the proposed diagnosis system uses measured motor terminal currents and voltages, and motor speed. The effectiveness of the diagnosis system is demonstrated through staged motor faults of electrical and mechanical origin. The developed system is scalable to different power ratings and it has been successfully demonstrated with data from 2.2, 373 and 597 kW induction motors. Incremental tuning is used to adapt the diagnosis system during commissioning on an new motor, significantly reducing the system development time.     

Fast Fourier and discrete wavelet transforms applied to sensorless vector control induction motor for rotor bar faults diagnosis

This paper presents new techniques to evaluate faults in case of broken rotor bars of induction motors. Procedures are applied with closed-loop control. Electrical and mechanical variables are treated using fast Fourier transform (FFT), and discrete wavelet transform (DWT) at start-up and steady state. The wavelet transform has proven to be an excellent mathematical tool for the detection of the faults particularly broken rotor bars type. As a performance, DWT can provide a local representation of the non-stationary current signals for the healthy machine and with fault. For sensorless control, a Luenberger observer is applied; the estimation rotor speed is analyzed; the effect of the faults in the speed pulsation is compensated; a quadratic current appears and used for fault detection.     

基于模糊神经网络系统的三相感应电机矢量控制

为实现三相感应电机稳定控制,提出了一种基于自适应模糊神经网络推理系统（ANFIS）的感应电机矢量控制方法。ANFIS结合了模糊逻辑的调节能力与神经网络的自适应能力,被广泛的应用到电机的参数估计、转速、转矩和磁链控制中。在分析感应电机工作原理的基础上,推导出其数学模型,在Matlab/Simulink上采用基于ANFIS的矢量控制对三相感应电机进行系统仿真,仿真结果表明,该控制策略转矩波动小,转速响应快,具有良好的动态和静态性能。     

MRAS state estimator for speed sensorless ISFOC induction motor drives with Luenberger load torque estimation

This paper presents a novel method for estimating the load torque of a sensorless indirect stator flux oriented controlled (ISFOC) induction motor drive based on the model reference adaptive system (MRAS) scheme. As a matter of fact, this method is meant to inter-connect a speed estimator with the load torque observer. For this purpose, a MRAS has been applied to estimate the rotor speed with tuned load torque in order to obtain a high performance ISFOC induction motor drive. The reference and adjustable models, developed in the stationary stator reference frame, are used in the MRAS scheme in an attempt to estimate the speed of the measured terminal voltages and currents. The load torque is estimated by means of a Luenberger observer defined throughout the mechanical equation. Every observer state matrix depends on the mechanical characteristics of the machine taking into account the vicious friction coefficient and inertia moment. Accordingly, some simulation results are presented to validate the proposed method and to highlight the influence of the variation of the inertia moment and the friction coefficient on the speed and the estimated load torque. The experimental results, concerning to the sensorless speed with a load torque estimation, are elaborated in order to validate the effectiveness of the proposed method. The complete sensorless ISFOC with load torque estimation is successfully implemented in real time using a digital signal processor board DSpace DS1104 for a laboratory 3 kW induction motor.     

Detection of broken rotor bars in induction motors using nonlinear Kalman filters

This paper presents a model-based fault detection approach for induction motors. A new filtering technique using Unscented Kalman Filter (UKF) and Extended Kalman Filter (EKF) is utilized as a state estimation tool for on-line detection of broken bars in induction motors based on rotor parameter value estimation from stator current and voltage processing. The hypothesis on which the detection is based is that the failure events are detected by jumps in the estimated parameter values of the model. Both UKF and EKF are used to estimate the value of rotor resistance. Upon breaking a bar the estimated rotor resistance is increased instantly, thus providing two values of resistance after and before bar breakage. In order to compare the estimation performance of the EKF and UKF, both observers are designed for the same motor model and run with the same covariance matrices under the same conditions. Computer simulations are carried out for a squirrel cage induction motor. The results show the superiority of UKF over EKF in nonlinear system (such as induction motors) as it provides better estimates for rotor fault detection.     

应用互换模型参考自适应的异步机无速度传感器直接转矩控制

本文介绍了一种可互换模型参考自适应方法实现对电机转速和定子电阻的辨识,并将其应用于异步机的无速传感器直接转矩控制中。仿真结果表明了方案的有效性。     

异步电机混合型滑模磁链观测器分析与验证

在异步电机直接转矩控制中,磁链的观测是精确控制电机的一个重要环节。针对两类无速度传感器滑模观测器,从收敛性和参数敏感性两方面进行了深入的分析,并比较各自的优缺点。结合工程实际需要提出了一种混合型滑模磁链观测器算法。所提出的磁链观测器在控制中能消除初始磁链误差,又具有较好的鲁棒性。MATLAB仿真和实验结果论证了该方法的正确性和有效性。     

基于全速域混合控制的同步磁阻电机无传感器矢量控制系统

针织大圆机的特殊运动状态要求其驱动电机具有较大的启动和带载能力以及较高的稳态运行精度,同步磁阻电机是一种应用于针织大圆机的理想电机,但现有同步磁阻电机无传感器控制,存在转子位置估计误差大、速度切换不平滑等问题。对此,提出一种基于全速域混合控制的同步磁阻电机无传感器矢量控制系统,零速和低速时采用脉振高频电流注入法,通过在估计坐标系的d轴注入一个幅值恰当的高频电流信号,使用估计q轴的高频电压信号估计转子位置;中速和高速时采用模型参考自适应法,通过建立数学模型并对其进行稳定性分析来估计转子位置;为了实现零速和低速到中高速的速度切换,提出一种改进的过渡区域融合观测方案,采用正弦型饱和函数代替传统的线性切换函数进行位置融合。为了验证方案的有效性,搭建了平台进行测试。由结果表明,该方案启动过程带载能力强,切换过程平滑且稳定,稳态运行过程波动小,是一种较适合大圆机电机驱动的无传感器矢量控制方法。     

六相串联三相双 PMSM 驱动系统低速区转子位置角高精度解耦观测研究

静止坐标系下通过控制不同平面的电压矢量可以实现六相串联三相PMSM系统中两台电机的独立解耦控制。基于此，在静止坐标系下六相平面和三相平面同时注入旋转高频电压，通过解调对应平面高频电流的负序分量，解耦获得两台电机的转子位置角初步观测值。为了补偿定子电阻、转速和滤波器对观测带来的误差，利用高频电流正序分量中误差角信息与转速前馈相结合的补偿方法，对转子位置角观测值进行补偿。实验结果表明，六相和三相电机稳态转子位置角观测误差绝对值的平均值为0.146和0.106 rad,动态下最大误差为0.2 rad;基于观测的转子位置角构建的无位置传感器直接转矩控制系统低速各种运行工况性能优越。     

Design and performance analysis of an iterative flux sliding-mode observer for the sensorless control of PMSM drives

To improve the performance of permanent magnet synchronous motor (PMSM) drives, a sensorless control scheme based on a novel iterative flux sliding-mode observer (IFSMO) is proposed in this paper. Two major drawbacks of the conventional sliding-mode observer (SMO), namely, chattering phenomena and high-order harmonics, are discussed. These drawbacks affect the estimation accuracy of the SMO and reduce the control reliability of the system. To eliminate high-order harmonics, a flux SMO is designed by expanding the PMSM state equations with the PM flux. The flux SMO estimates the rotor speed and position using the flux linkage instead of back-EMF information. Moreover, to reduce the chattering in the estimation results, the proposed flux SMO is iteratively used in one current sampling period to adaptively adjust the observer gain. An overall PMSM sensorless control system based on the proposed IFSMO is designed, and an experimental platform using the TMS320F28335 digital signal processor (DSP) controller is built. The superior chattering reduction and harmonic suppression characteristics of the proposed IFSMO are experimentally validated, and the experimental results verify the feasibility of using the proposed IFSMO-based PMSM sensorless scheme in practical applications.     

基于FIR优化滤波的旋转高频信号注入法及其应用

针对传统旋转高频信号注入法中信号处理精度低、延时时间长及过程复杂等缺陷,提出一种基于有限冲激响应(finite impulse response,FIR)优化滤波的改进旋转高频信号注入法.该方法采用等纹波最佳逼近FIR滤波器提取高频电流信号,实现高频电流信号提取误差最小.通过对高频电流作外差处理,提取转子位置误差信号,省去旋转高频信号注入法中的同步轴系滤波单元,降低系统的复杂性.通过线性相位补偿,实现转子速度与位置估计最小延迟.构建无轴承永磁同步电机无速度传感器矢量控制平台,验证算法的有效性.仿真实验结果表明:通过离线优化设计FIR滤波器及线性相位补偿,该方法在全速范围内能够准确估计转子的位置与速度,与卡尔曼滤波相比,其估计精度更高,鲁棒性更强.     

无速度传感器矢量控制的速度推算

通过测量定子每相的电压和电流值，推测出速度是实现无速度传感器矢量控制的一条途径，其中磁链的精度是速度推算的重要环节。通过构造全维状态观测器来提高转子电流和磁链的推算精度，同时使用速度自适应辩识和Rs自适应辩识来进一步提高电流和磁链的推算精度，并完成速度推算，从而可以对感应电机实现高性能的矢量控制。     

IGCT在矿井提升机斩波串调系统中的应用

采用转子回路串电阻调速的绕线式异步电机广泛应用于矿井提升机电控系统,提出了将斩波串级调速方案应用于改造该类矿井提升机电控系统。其与常规串级调速系统的不同之处在于转子直流回路中加入了直流斩波器。斩波串调不仅克服了有级调速的缺点,还可以采用闭环控制．使调速性能大大改善,同时与普通串调系统相比,逆变器的容量大为减小;更为重要的是能够大大改善电机拖动系统的功率因数。     

采用神经网络对感应电动机的速度辨识

提出一种采用神经网络辨识感应电动机转速的新方法,采用后传播神经网络技术来提供一种实时自适应速度估计,利用希望的状态变量和实际状态变量的误差来调整神经网络的权重,达到使实际状态变量与希望状态变量一致理论分析和仿真结果都证明了这种方法的有效性。     

Induction machine condition monitoring using notch-filtered motor current

This paper presents a new approach to induction motor condition monitoring using notch-filtered motor current signature analysis (NFMCSA). Unlike most of the previous work utilizing motor current signature analysis (MCSA) using spectral methods to extract required features for detecting motor fault conditions, here NFMCSA is performed in time-domain to extract features of energy, sample extrema, and third and fourth cumulants evaluated from data within sliding time window. Six identical three-phase induction motors were used for the experimental verification of the proposed method. One healthy machine was used as a reference, while other five with different synthetic faults were used for condition detection and classification. Extracted features obtained from NFMCSA of all motors were employed in three different and popular classifiers. The proposed motor current analysis and the performance of the features used for fault detection and classification are examined at various motor load levels and it is shown that a successful induction motor condition monitoring system is developed. Developed system is also able to indicate the load level and the type of a fault in multi-dimensional feature space representation. In order to test the generality and applicability of the developed method to other induction motors, data acquired from another healthy induction motor with different number of poles and rated power is also incorporated into the system. In spite of the above difference, the proposed feature set successfully locates the healthy motor within the classification cluster of “healthy motors” on the feature space.     

Sensorless speed detection of squirrel-cage induction machines using stator neutral point voltage harmonics

In this paper a sensorless speed detection method of induction squirrel-cage machines is presented. This method is based on frequency determination of the stator neutral point voltage primary slot harmonic, which is dependent on rotor speed. In order to prove method in steady state and dynamic conditions the simulation and experimental study was carried out. For theoretical investigation the mathematical model of squirrel cage induction machines, which takes into consideration actual geometry and windings layout, is used. Speed-related harmonics that arise from rotor slotting are analyzed using digital signal processing and DFT algorithm with Hanning window. The performance of the method is demonstrated over a wide range of load conditions.     

无速度传感器转子磁场定向感应电机控制系统研究与开发

介绍了一种采用磁链和开环速度估算器的转子磁场定向的控制系统，系统设计的的关键问题是磁链的观测和速度的准确估算。按照模型参考自适应系统构造出参考模型和可调模型来实现了扩展卡尔曼滤波对磁链和电机转速的估算，并成功应用此算法设计了一套DSP实验控制系统，实现了速度自适应识别。介绍了DSP实验系统的硬件和软件实现方法并对实验结果进行了分析。模型试验应用于1．0kW的感应电机取得了较好的的控制效果。     

Embedded model control: application to web winding

Embedded Model Control (EMC) methodology is applied to web-winding control problems. These require time-varying Embedded Model and adaptive control law, because of a variable winder radius; disturbance estimation and rejection, because of friction and variable web speed and acceleration; sensorless reel radius estimation; and robust stability and performance in the presence of web and gear vibrations. The goal is to solve these key issues in the framework of EMC, which amounts to (i) designing a time-varying Control Law capable of disturbance rejection, (ii) designing Noise Estimators capable of keeping live and accurate disturbance and radius estimates, and (iii) tuning their eigenvalues to guarantee stability and performance. Tuning takes advantage of an 'error loop' formulation, which explicitly relates neglected dynamics to eigenvalues, stability and performance. Simulated runs from a fine winder model are compared to published results.     

基于EKF的异步电机转速和负载转矩估计

合理选择电机的容量具有重要的意义,电机的容量可根据电机的转速和负载转矩确定,将电机的转速和负载转矩同时作为系统的状态,提出了一种基于EKF同时估计异步电机转速和负载转矩的方法,建立了包含异步电机转速和负载转矩状态的系统模型,基于该模型用EKF实现了同时估计异步电机转速和负载转矩,仿真和实验验证了所提方法能以较高的精度同时估计出电机的转速和负载转矩.