感应电机全阶磁链观测器设计及其控制性能对比分析

针对以往在感应电机无速度传感器矢量控制中,全阶磁链观测器均是以静止坐标系下状态变量进行设计的,其基于欧拉法的离散化过程估算误差大,若采用梯形法、双线性法或龙格-库塔法,估算误差有所减小,但计算过程复杂,不适宜工程应用。提出以同步旋转坐标系下的定子电流和转子磁链作为状态变量来设计全阶磁链状态观测器,其离散化过程采用工程上常用的欧拉法,计算量小。同时给出了基于两种坐标系下全阶磁链观测器转速估算自适应律设计方法。仿真分析和实验结果对比表明,在低速和高速状态下,同步旋转坐标系下设计的状态观测器电流和转速估算准确快速,可以明显提高系统控制的精确性和实用性。     

感应电机全阶观测器的一种新型离散方法

针对感应电机全阶自适应观测器的离散化问题,通过将欧拉法和双线性变换法相结合,提出了一种新型离散化方法,用于实现感应电机精确的无速度传感器数字控制。自适应全阶磁链观测器的状态变量由定子电流和转子磁链构成。该方法对定子电流采用欧拉法离散,对转子磁链采用双线性法离散。通过合理近似,使得求解磁链的方程组实现解耦,其运算复杂度比传统的双线性法显著降低。该方法的运算量只比欧拉法有略微增加,但精度却比欧拉法有明显改进。实验结果表明,所提出的方法能取得较小的离散误差,从而提高了感应电机无速度传感器控制的准确度。     

基于无差拍控制的无轴承异步电机DTC系统

针对无轴承异步电机多变量、非线性、强耦合等特点,提出一种基于离散时间无差拍的SVM - DTC控制方法.在定子磁场定向的同步旋转坐标系下,通过离散时间无差拍( DTDB)算法得到转矩和磁链的控制电压分量,实现转矩与磁链控制的动态解耦,解决了转矩环与磁链环的干扰.由定子磁链减去定子漏磁得到悬浮绕组控制所需气隙磁链,简化了...     

三相异步电机矢量控制的研究

在异步电动机数学模型的基础上,讨论了矢量控制理论及其解耦性质.将异步电动机三相静止坐标系下的电压方程、磁链方程、转矩方程分别变换到两相同步旋转坐标系下.通过转子磁场定向技术,使定子绕组电流的转矩分量和磁场分量得到解耦,使得异步电机类似于直流电机的控制方法得以实现,从而,异步电机的调速性能大大提高.根据异步电机的磁链开环矢量的控制原理,采用Simulink自带的小模块自行搭建了矢量控制系统的仿真模型.     

异步电动机间接转矩控制系统的效率优化设计

针对异步电动机间接转矩控制系统,提出了一种效率优化方法.首先,在计及铁损的情况下推导了异步电动机的损失模型;然后,在旋转坐标系下,计算出最优的转差率,根据转差率与转子磁链及电磁转矩的函数关系,推导出最优的转子磁链,根据定子磁链与转子磁链、电磁转矩之间的函数关系,得到定子磁链的最优给定值;最后,将所得到的最优定子磁链给定量用于异步电动机间接转矩控制系统中.实验验证了方法的有效性.     

一种基于MRAS的异步电机速度辨识方法

本文提出了一种在静止坐标系下实现的模型参考自适应系统,以辨识异步电机的转速.该方法的参考模型和可调模型分别由电机定子侧和转子侧的方程构成.参考模型中不含定子电阻,并且避免了纯积分运算,因而在宽速度范围内具有较好的鲁棒性.可调模型包含电机转速的信息和一个电流模型转子磁链观测器.当电机转速的估计值收敛于转速的真实值时,观测的转子磁链也收敛于其真实值,可将其用于直接磁场定向控制中.另外,为避免对定子电流的纯微分,本文应用微分跟踪器以提取高质量的微分信号.数值仿真和实验结果验证了该方法的有效性.     

一种IPMSM无位置传感器系统设计的新方法

针对内置式永磁同步电机IPMSM(interior permanent-magnet synchronous motor),本文给出一种新的无位置传感器系统设计方案.由转子永磁磁链角的估计值和同步坐标系下定子磁链的代数模型得到定子磁链的估计值,经旋转变换后与静止坐标系下由定子电压、电流积分模型得到的定子磁链进行比较形成反馈闭环来抑制积分漂移,并利用两者的叉积经锁相环得到IPMSM转子转速和位置的估计值.与已有的EEMF状态观测器方法相比较,本文所提方法简单且有更好的动态和静态估计性能.最后通过仿真和实验验证了所提算法的可行性和有效性,试验中为提高系统在低速下的性能,对逆变器的非线性进行了补偿.     

电网对称故障下无刷双馈电机低压穿越分析

通过控制电机转子磁场定向得到同步坐标系下的仿射非线性状态空间模型,针对无刷双馈发电机组机侧控制器应用反馈线性化解耦控制方法。在电网电压三相对称跌落下,分析控制电机定子电流和控制电机定子反电动势的暂态响应。推导得出BDFM稳定运行时,控制电机转子磁链与功率电机定子电压满足线性比例关系,在低压穿越模式下来改善系统控制性能和稳定性,提高机组低压穿越能力。仿真结果证明了理论分析的正确性和有效性。     

基于MRAS的感应电机无速度传感器矢量控制

在两相静止坐标系下的模型参考自适应系统(MRAS)中,由于转子磁链在α与β轴的两个分量之间存在交叉反馈关系,离散计算时收敛性能较差.采用了一种在两相旋转坐标系下实现的模型参考自适应系统,来辨识感应电机的转速.该方法的参考模型和可调模型分别由改进的电压模型和两相旋转坐标系下转子磁链的电流模型构成.在以TMS320C32为核心的实验平台上进行了实验研究.实验结果表明,该系统能较好地估计电机的磁链及转速,具有良好的稳态辨识特性.     

转子磁链误差对感应电机观测器稳定性影响

利用转子磁链电压模型研究转子磁链误差对感应电动机全阶转速自适应转子磁链观测器稳定性影响.通过研究观测器等效误差系统前向通道传递函数正实性,得到观测器在ω1-ωs平面中稳定区域边界方程.提出不舍纯积分器的新型转子磁链误差模型,通过分析该模型对线性化等效转速控制系统开环零点分布影响,研究不同工况下观测器稳定区域分布.研究结果表明增大转子磁链误差能够扩大稳定区域,所提出的模型解决了低速再生发电工况时观测器稳定问题,但在低速电动工况时观测器不稳定.仿真结果表明组合应用不同转速自适应律观测器在所有工况下均能稳定.     

Robust direct torque and flux control of adjustable speed sensorless induction machine drive based on space vector modulation using a PI predictive controller

A Direct torque and flux control design for a sensorless induction motor, following a Lyapunov-based stator flux observer is presented. In this control scheme, the torque error signal and the amplitude of the stator flux reference vector are delivered to a PI predictive controller. The predictive controller also uses information on the amplitude and position of the actual stator flux vector and measured stator currents to determine the voltage command vector for space vector modulation inverter. In addition, a conventional PI speed controller is used to generate the torque reference signal. Using the fifth order model of the three-phase induction machines in a stationary two axes reference frame, a nonlinear stator flux observer is developed in order to estimate the rotor speed, rotor and stator resistances simultaneously. The stability of this observer is proved by Lyapunov theory. It is shown that if the persistancy of excitation condition is satisfied, the estimated quantities converge to their real values. The effectiveness of the proposed control scheme is verified by computer simulation and experimental results.     

Nonlinear adaptive state-feedback speed control of a voltage-fed induction motor with varying parameters

An adaptive nonlinear-state-feedback speed control scheme of a voltage-fed induction motor has been developed in which the control of torque and flux is decoupled. The inputs to the control algorithm are the reference speed, the reference flux, the measured stator currents, the measured rotor speed, the estimated rotor flux, and estimates of the rotor resistance, stator resistance, and load torque, which may vary during operation. The controller outputs are the reference stator voltages in rotor-flux rotating reference frame. An accurate knowledge of the rotor flux and machine parameters is the key factor in obtaining a high-performance and high-efficiency induction-motor drive. The rotor flux is estimated using the induction-motor rotor-circuit model. Although the estimated rotor flux is insensitive to the stator-resistance variation, it does depend on the rotor resistance. A stable model reference adaptive system (MRAS) rotor-resistance estimator insensitive to stator-resistance variation has been designed. Stable stator-resistance and load-torque MRAS estimators have also been developed. These estimators have been developed to constitute a multi-input-multi-output (MIMO) decoupled-cascade structure control system. This simplifies the design problem of the estimators for a stable operation from a MIMO design problem to a single-input-single-output (SISO) design problem. The continuous adaptive update of the machine parameters and load torque ensures accurate flux estimation and high-performance operation. Simulation and experimental results are presented to verify the stability of the induction-motor drive in various operating modes.     

Adaptive non-linear speed control of induction motors

In this paper we present two adaptive non-linear speed control algorithms for induction motors. They employ input-output linearization techniques for the motor model in the stator fixed reference frame. The first control algorithm directly tracks speed and rotor flux. The second is designed using torque and rotor flux tracking and is extended for speed control. A key point is that this algorithm ensures exact current limitation in the known parameter case. The adaptation based on Lyapunov design can cope with rotor and stator resistance variations. Significant simulations using sampled controllers are presented emphasizing adaptation and current limitation effects.     

基于磁通观察器的感应电动机无速度传感器矢量控制系统的参数在线辨识

提出了一个基于磁通观察器的感应电动机无速度传感器矢量控制系统的参数在线辨识方案 ,包括利用d轴磁通误差实现定子电阻在线辨识法和利用励磁电流指令上叠加交流信号实现转子电阻在线辨识法。该方案的优点是系统简单 ,解决了电机参数变化对调速精度和系统稳定性影响的问题。数字仿真和实验结果验证了方案的有效性。     

无传感器矢量控制系统及其速度估算的研究

基于同步轴系下的感应电动机电压磁链方程式,提出了一种感应电动机转子磁场定向的矢量控制方法,利用在同步轴系中q轴电流的误差信号实现对电动机速度的估算.在该无传感器矢量控制系统中,由于采用了经典的PI调节器,使得控制系统更为简单.最后利用MATLAB建立仿真模型,通过仿真验证了该控制系统具有良好的动态和静态性能.     

无速度传感器直接转矩控制系统的MATLAB仿真

采用定子磁链u-n模型计算定子磁链,并在此基础上将模型参考自适应应用于直接转矩控制系统中,实现了系统的无速度传感器运行。针对3kW异步电动机,采用MATLAB/SIMULINK软件进行了仿真。仿真结果表明,该系统对电机定子磁链的观测精度高,速度运算较准确,在全速范围内能保持较高的性能。     

Speed sensorless vector control of induction motor using extendedKalman filter

A vector control of an induction motor by an estimated speed using an extended Kalman filter is proposed. With this method, the states are composed of stator current and rotor flux. The rotor speed is regarded as a parameter, and the composite states consist of the original states and the rotor speed. The extended Kalman filter is employed to identify the speed of an induction motor and rotor flux based on the measured quantities such as stator currents and DC link voltage. The estimated speed is used for vector control and overall speed control. Since the current control is performed at a synchronous rotating reference frame, the estimated speed information is also used for the reference frame transformation of the current controller. Computer simulations and experiments of the speed control have been carried out to test the usefulness of the speed estimation algorithm. The experimental results show that the performance of the speed estimation is very good     

Design and implementation of a closed-loop observer and adaptivecontroller for induction motor drives

This paper discusses the implementation and experimental results of a closed-loop rotor flux observer and model reference adaptive system (MRAS) of a direct field-oriented control (FOC) of an induction motor drive. The motor was supplied from a high-frequency (20 kHz) AC resonant link via a MOS-controlled-thyristor (MCT)-based bidirectional converter. Hardware and software implementations of the various motor control functions are presented. The closed-loop observer combines the current and voltage models via a speed-dependent gain (SDG). The current model was formulated to operate in the rotor reference frame and requires only an encoder angle and not the actual rotor speed for implementation. The closed-loop observer permits the use of a pure analog integrator to calculate an adequate stator flux. The use of an AC resonant link further complicated an all-digital calculation of the stator flux. The observer and adaptive controller were tested on a 400-Hz 2-hp induction motor for low and high speeds. The closed-loop observer showed sensitivity at low speeds to the rotor circuit time constant which attributed to the current model rotor flux estimation. At high speed, the closed-loop observer followed the voltage model rotor flux estimation attributes. The MRAS was able to improve the complete speed response by correcting the current model rotor flux observer for errors in estimation of its parameters     

Design of a new adaptive sliding mode observer for sensorless induction motor drive

This paper proposes a new speed and flux estimation method which has the robustness against the variation of the electrical parameters of the motor and the superiority in the dynamic characteristics. In the proposed method, the stator currents and the rotor fluxes are observed on the stationary reference frame using the sliding mode concept. And the rotor speed is estimated using the current estimation errors and the observed rotor fluxes based on the Lyapunov stability theory. Also a design method of the observer gain using H₈ norm is proposed to minimize the effect of the speed estimation error on the rotor flux observation. The experimental results are shown to verify that the proposed method shows the excellent performances under the variations of motor resistance and inductance.