Speed Identification of Speed Sensorless Linear Induction Motor Based on MRAS

In the linear induction motor control system,the optical grating speed transducer is susceptible to strong magnetic field interference.What's more,it may reduce motor integration and raise device costs.Therefore a speed identification method to replace grating speed transducer is studied in this article.This speed identification method for linear induction motor mainly adopts Model Reference Adaptive Method(Abbreviated as MRAS)and Popov Hyperstability Theory.The research content of this paper can be divided into four parts.First,the mathematical model of the motor based on the model reference adaptive system structure is deduced.Second,the adaptive law of the estimated speed is solved by Popov hyper-stability theory,which ensures the stability of the system.Third,the simulation model of the linear induction motor speed identification control system based on model reference adaptation is built in the MATLAB environment.Finally,the simulation test and analysis are carried out.The simulation results show that the speed identification control system can track the actual speed of the linear induction motor well in the no-load operation and the load operation,and the stability of the system is guaranteed in the full speed range.

LOW COST IMPLEMENTATION OF SPEED SENSORLESS INDUCTION MOTOR CONTROL USING STATOR FLUX ORIENTATION

The control platform of the induction motor （IM） with low costs is developed by using DSP MC56F8013 with a good performance/price rtaio. The control algorithm for the speed sensorless IM is studied based on the stator flux orientation （SFO）. The algorithm structure is simple to be implemented and cannot be influenced by motor parameters, The improved stator flux estimation is used to compensate errors caused by the low pass filter （LPF）. A new speed regulator is designed to ensure the system working with the maximal torque in the transient state. The system simulation and the prototype experiment are made. Results show that the con- trol system has good dynamic and static performance.

Speed Sensorless Vector Control of Induction Motor Based on Reduced Order Extended Kalman Filter

A speed sensorless vector control system of induction motor with estimated rotor speed and rotor flux using a new reduced order extended Kalman filter is proposed. With this method, two rotor flux components are selected as the state variables, and the rotor speed as an estimated parameter is regarded as an augmented state variable. The algorithm with reduced order decreases the computational complexity and makes the proposed estimator feasible to be implemented in real time. The simulation results show high accuracy of the estimation algorithm and good performance of speed control, and verify the usefulness of the proposed algorithm.

Compensation of Dead-Time Effect of Speed Sensorless Vector Control System

The key of speed sensorless vector control system lies in the accurate orientation of magnetic field. In some field-oriented algorithms, the integrator of observers and the dead-time effect bring in system errors during the estimation of field position. In this paper, a saturated feedback integrator is used, and the dead-time effect is compen- sated by current positive feedback. Experiments were carried out on the hardware platform of MCK2407, with chip TMS320LF2407 from TI Company. The results show that the prooosed method is simole and effective, and the accuracy of field position is improved.

Speed sensorless FCS-MPTC based on FOSM-MRAS five-phase permanent magnet synchronous motor

For the two-level five-phase permanent magnet synchronous motor(FP-PMSM)drive system,an improved finite-control-set model predictive torque control(MPTC)strategy is adopted to reduce torque ripple and improve the control performance of the system.The mathematical model of model reference adaptive system(MRAS)of FP-PMSM is derived and a method based on fractional order sliding mode(FOSM)is proposed to construct the model reference adaptive system(FOSMMRAS)to improve the motor speed estimation accuracy and eliminate the sliding mode integral saturation effect.The simulation results show that the FP-PMSM speed sensorless FCS-MPTC system based on FOSM-MRAS has strong robustness,good dynamic performance and static performance,and high reliability.

Backstepping Control of Speed Sensorless Permanent Magnet Synchronous Motor Based on Slide Model Observer

This paper presents a backstepping control method for speed sensorless permanent magnet synchronous motor based on slide model observer. First, a comprehensive dynamical model of the permanent magnet synchronous motor(PMSM) in d-q frame and its space-state equation are established. The slide model control method is used to estimate the electromotive force of PMSM under static frame, while the position of rotor and its actual speed are estimated by using phase loop lock(PLL) method. Next,using Lyapunov stability theorem, the asymptotical stability condition of the slide model observer is presented. Furthermore, based on the backstepping control theory, the PMSM rotor speed and current tracking backstepping controllers are designed, because such controllers display excellent speed tracking and anti-disturbance performance. Finally, Matlab simulation results show that the slide model observer can not only estimate the rotor position and speed of the PMSM accurately, but also ensure the asymptotical stability of the system and effective adjustment of rotor speed and current.

基于一阶线性自抗扰控制器的同步磁阻电机无速度传感器控制

同步磁阻电机在实现无速度传感器控制时出现交叉耦合效应,导致dq轴电感随着电流发生非线性变化,转速环使用传统PI控制器已无法满足系统较强的抗扰性能和较高的转子位置估计精度。为了改善此问题,该文提出一阶线性自抗扰控制器的同步磁阻电机无速度传感器控制策略,利用其机械运动状态方程,将同步磁阻电机的交叉耦合效应及负载扰动变化视为扰动。首先通过扩张状态观测器对负载扰动快速观测并进行前馈补偿,以此来提高系统抗扰性;其次利用静止实验法,得到dq轴磁链与电流的非线性函数模型,将该模型运用至磁链观测器中,以减小交叉耦合效应,提高转子位置估计精度;最后在1.5 kW的同步磁阻电机对拖加载实验平台上进行实验,验证了该控制方案的有效性。

A New Sensorless Technique for the Speed Detection of an Induction Motor

This paper presents a new sensorless method, the so-called harmonic impedance / admittance, for detecting speed of induction motors, which is based on the impedance measurement, harmonic analysis and digital signal processing. The method improves theperformance of conventional voltage-based and current-based techniques, because the impedance or admittance harmonics is independent of input or output of motor system due to the system-inherent nature of impedance. It has been used successfully in detecting the rotor speed of three-phase induction motors. A comparison between the proposed method and the conventionalcurrent-based method is also demonstrated.

A Sensor-less Surface Mounted PMSM for Electronic Speed Control in Multilevel Inverter

Recent advancements in power electronics technology evolves inverter fed electric motors.Speed signals and rotor position are essential for controlling an electric motor accurately.In this paper,the sensorless speed control of surface-mounted permanent magnet synchronous motor(SPMSM)has been attempted.SPMSM wants a digital inverter for its precise working.Hence,this study incor-poratesfifteen level inverter to the SPMSM.A sliding mode observer(SMO)based sensorless speed control scheme is projected to determine rotor spot and speed of the multilevel inverter(MLI)fed SPMSM.MLI has been operated using a multi carrier pulse width modulation(MCPWM)strategy for generation offif-teen level voltages.The simulation works are executed with MATLAB/SIMU-LINK software.The steadiness and the heftiness of the projected model have been investigated under no loaded and loaded situations of SPMSM.Furthermore,the projected method can be adapted for electric vehicles.

一种自适应扩展卡尔曼滤波的永磁同步电机无位置传感器矢量控制

在粗差干扰或噪声统计偏差情况下,扩展卡尔曼滤波(EKF)对永磁同步电机(PMSM)的速度和转子位置估计存在精度下降问题,为此提出一种基于新息序列的自适应扩展卡尔曼滤波算法(AEKF)。首先,将粗差干扰加入系统观测方程中,分析粗差干扰对系统观测精度的影响。其次,为增强算法的抗扰性能,在新息协方差计算中设置加权系数,通过调整临近时刻的新息协方差阵权重,计算出新息协方差值,并更新到卡尔曼增益的计算。最后,建立AEKF数学模型,并对比粗差干扰与噪声统计出现偏差情况下,AEKF与EKF两种策略的观测性能。仿真和实验结果表明,在粗差干扰或噪声统计信息出现偏差情况下,AEKF算法对永磁同步电机转速的观测具备更强的鲁棒性及更高的预测精度。

真空泵用屏蔽电机无传感器残压重投控制策略

针对真空干泵机组故障、生产工艺需要等原因影响真空设备产线在线运行时间的问题,研究真空干泵用屏蔽式感应电机带速重投策略,寻求重投的有利时刻以保证带速重投的成功,对电机断电后的转速和定子失电残压特性展开研究。为此,根据屏蔽感应电机空间向量模型,建立基于电压电流混合磁链观测的无速度传感器估算模型、推导电机断电期间的转速估算方法以及定子失电残压解析式。通过重点研究定子残压和虚拟重投电压间幅值特性和相角特性,确定控制系统的首次重投点和其次重投点。以4 kW真空干泵用屏蔽感应电机机组为例,通过模型仿真和失电残压实验验证了该控制方法在泵类工程中有较好的适用性和准确性,重投阶段的转速稳定时间为0.5 s以内,重投阶段的冲击电流平均减小59.18%。

基于滑模观测器的高速PMSM无传感器控制

针对基于饱和函数滑模观测器方法存在调节参数多及低通滤波器带来的相位延迟问题,研究一种基于超螺旋算法的滑模观测器无传感器控制策略,通过理论推导及系统稳定性分析,设计了一种滑模系数根据转速变化在线调节的自适应滑模系数算法。通过实验验证了该方法相比于基于饱和函数滑模观测器,能在较宽速度范围内有效地抑制抖振,提高了无传感器控制系统的估计精度,简化了参数调节过程及滤波器设计环节。

永磁同步电机无位置传感器控制技术综述

无位置传感器电机驱动器具有成本低、可靠性高、硬件电路简单以及维护要求少等优势,在学术界和工业应用中受到了越来越多的关注。对适用于零低速域、中高速域以及全速域三种运行范围的多种无位置传感器技术进行了综述。首先,分别对比分析了零低速域和中高速域下各种无位置传感器控制方法的优缺点。其次,梳理和总结了目前全速域运行的切换控制策略。最后,对永磁同步电机无位置控制技术的未来发展趋势进行了展望,并指出了后续研究的关键问题。

基于模糊扩展卡尔曼的直线感应电机无速度传感器控制

直线感应电机(linear induction motor,LIM)可实现无接触、无摩擦的直线运动,具有爬坡强、横断面小、低噪音等优势,在中低速磁悬浮与城市轨道交通中被广泛应用。其中,基于观测器的电机无速度传感器矢量控制方法,是解决速度传感器成本高、可靠性低、维护难等问题的有效途径。针对LIM速度辨识受系统内外扰动影响导致观测精度下降问题,提出基于模糊扩张卡尔曼滤波(Fuzzy Extended Kalman Filter,FEKF)的速度观测方法,提高观测器鲁棒性。首先在αβ坐标系下建立考虑动态边端效应的LIM数学模型,利用LIM的实时电流和电压作为输入信号,以电流、磁链和速度作为状态变量,推导出基于扩展卡尔曼滤波(extended kalman filter,EKF)观测器电机状态空间方程的离散模型,利用EKF对LIM的速度和磁链进行在线观测,并用于实现LIM的矢量控制。其次,为提高EKF的噪声协方差矩阵Q对LIM系统内外扰动的鲁棒性,引入模糊控制方法对矩阵Q进行自适应调整,实现速度与磁链的估计精度。具体通过计算系统理论残差与实际残差的偏离程度得到噪声调节因子,实时调整噪声协方差矩阵Q,并在下一周期更新模糊扩展卡尔曼的反馈增益矩阵,提高对速度与磁链的估计精度。之后对系统的能观性与FEKF的收敛性进行分析,探明矩阵Q中各参数的边界及整定规律。最后通过仿真和硬件在环实验验证所提FEKF优化算法的有效性,结果表明FEKF能有效提高对LIM速度辨识准确性,实现LIM无速度传感器矢量控制。

基于电流误差加权转速自适应律的异步电机无速度传感器设计方法

针对异步电机无速度传感器低速运行不稳定的问题,提出一种基于电流误差加权转速自适应律的异步电机无速度传感器设计方法。首先,采用小信号线性化模型分析方法说明转子磁链误差与励磁电流误差之间的关系,进而得出新的转速自适应律;然后,推导所提转速自适应律的开环传递函数,采用劳斯稳定性判据得出系统稳定运行的条件,借助MATLAB软件确定加权系数的取值;最后,将反馈矩阵引入含有改进转速自适应律的系统中,分析所提方法的极点分布规律。实验分析表明,所提方法具有较好的稳定性和优越性。

考虑边端效应及参数变化的直线感应电机MRAS速度观测方法

以轨道交通直线感应电机(Linear Induction Motor,LIM)牵引驱动系统速度观测器为研究对象,针对边端效应及电机参数变化导致辨识结果实时性、鲁棒性不足的问题,提出一种基于二阶超螺旋滑模的改进模型参考自适应系统(Model Reference Adaptive System,MRAS)速度观测方法。首先,以计及动态边端效应的初次级电压电流磁链方程为核心,设计直线感应电机标准MRAS速度观测器,降低边端效应对速度辨识性能的影响。然后,进一步分析初级集肤效应和初次级横向错位对标准MRAS速度观测器辨识性能的影响。在此基础上,基于二阶超螺旋算法对MRAS参考模型进行改进,利用主滑模面和辅助滑模面对次级磁链观测的干扰项进行补偿,同时抑制由于滑模算法引入的系统抖振,提高了速度观测器的鲁棒性和动态性能。最后,搭建仿真和硬件在环实验环境进行算法验证。实验结果表明:励磁互感及其他电机参数随边端效应修正因子变化,标准MRAS观测器在突加负载、引入测量误差和电机参数突变的工况下,速度辨识误差明显;改进的MRAS观测器能够实现直线感应电机速度的快速、准确辨识,基于该速度观测器的矢量控制策略,在突加负载、引入测量误差和电机参数突变的工况下,控制性能满足设计要求。研究结果能为轨道交通直线感应电机无速度传感器牵引驱动系统的研究提供一定借鉴。

基于两级滤波的改进滑模观测器PMSM无速度传感器控制

针对永磁同步电动机(permanent magnet synchronous motor,PMSM)伺服系统中由滑模观测器引起的位置估算误差以及抖振问题,提出了一种改进的两级滤波滑模观测器。首先,根据PMSM的数学模型,设计了利用传统滑模观测器估计定子电流和反电动势的估计算法;其次,分析了传统滑模观测器在PMSM伺服系统应用中的不足;再次,提出了一种新的饱和函数以代替传统的符号函数,改进了滑模观测器的控制律;最后,通过变截止频率滤波器和卡尔曼滤波器组成的二级滤波器,得到PMSM转子更精确的位置估计信息。利用Matlab,对使用了传统观测器的系统和使用改进的观测器的系统分别进行了仿真,仿真结果表明:与使用了传统观测器的PMSM伺服系统相比,使用了改进观测器的PMSM伺服系统转速误差更小、估算结果更准确。

复合模型参考自适应无速度矢量控制

磁链模型和无功功率模型由于结构简单、估计性能好,常用于模型参考自适应转速估计。针对磁链模型和无功功率模型各自存在的动稳态问题,通过分析不同模型对磁链精度的需求差异,提出了由无功功率-磁链-切换函数组成的复合模型,该复合模型在动态和稳态过程中都能实现准确的速度估计。经Matlab/Simulink仿真及实物实验,证实复合模型具有良好的动态跟踪性能和优秀的稳态性能。

表贴式永磁同步电机无位置传感器零低速起动方法的比较研究

由于运行在中高速状态下的永磁同步电机无位置传感器控制方式大多是采用反电动势来估算角度位置和转速,这在零低速往往不适用。为了实现表贴式永磁同步电机无位置传感器零低速起动和平滑切换到中高速运行,分析了恒压频比控制、恒流频比控制、脉振电压信号高频注入法三种低速起动控制方法。开环恒压频比控制采用了新的V/F曲线和电压补偿,近似补偿定子阻抗压降防止起动失败;单闭环IF控制和双闭环脉振高频电压注入控制采用加权算法切换至滑模观测器。对某一表贴式永磁同步电机应用Matlab/Simulink进行了永磁同步电机无位置传感器控制系统的仿真分析,仿真结果验证了所提出方法的有效性。

基于SMC与SVPWM的永磁同步电机无速度传感器控制技术研究

针对传统永磁同步电机控制是利用速度传感器获取实时速度信息而导致系统复杂性与成本增加的问题,提出一种基于SMC与SVPWM的永磁同步电机无速度传感器控制技术。在对滑模控制与空间矢量脉冲宽度调制理论分析的基础上建立了电机无速度传感器控制模型,并在MATLAB/Simulink平台下搭建了仿真模型,对电机转速与负载变化下的速度与位置跟踪性能进行仿真,结果表明所提出的控制技术在两种工况下具有良好的性能。对降低系统成本与复杂性,使得永磁同步电机具有更广泛的用途提供了参考。