非正弦供电感应电动机传动系统稳态仿真方法

为克服谐波分析法的近似性,提出利用三相交流电路的波形对称条件,通过坐标变换得到感应电动机的常因数状态方程,根据基于对称因数矩阵的状态方程解析求解方法,确定状态变量的初值,直接求得非正弦变频电源供电时感应电动机传动系统稳态运行的时域解.以方波电压源供电感应电动机传动系统为例,分别进行稳态仿真和动态仿真.仿真结果的对比表明,该方法正确、有效,可为其他电力传动系统的稳态分析提供参考.     

感应电动机传动系统建模及仿真的一般方法

感应电动机传动系统是目前应用最广泛的交流传动系统,对其性能的计算机模拟和仿真具有重要的实际指导意义。结合MATLAB语言和环境,介绍在任息速参考坐标系下,基于感应电动机传动系统不同的控制策略和运行状态,导出其由状态变量方程描述的统一时域建模方法,详述仿真工具和方法的选择、逆变器的处理、及其完整的流程。对三相异步电动机的直接转矩控制（DTC）系统的仿真结果表明,该文所提出的仿真方法是有效和可行的。     

变频器非正弦供电对异步电机的影响

介绍变频器非正弦供电对异步电机的影响,分析谐波电压和电流对电机磁路、定子和转子功率因数、电机损耗与效率、谐波转矩、电应力、轴电流产生的危害和如何防止。     

基于Simulink仿真工具的感应电动机仿真模型研究

在分析感应电动机数学模型的基础之上,利用Ｍａｔｌａｂ软件提供的Ｓｉｍｕｌｉｎｋ仿真工具,构造了感应电动机的通用仿真模型。并设计了人机交互式界面,使得利用Ｍａｔｌａｂ进行交流调速诉仿真过程大大简化。该模型结构简单。可测量多,研究结果表明,能满足一般系统的要求,因而有较强的实用性。     

单相感应电动机瞬态过程的SIMULINK仿真

根据单相感应电动机在d-q静止坐标系下的动态数学模型,用MATLAB软件中的动态仿真工具SIMULINK构造出电容单相感应电动机的仿真模型。通过实例对电容起动单相感应电动机和电容起动、电容运行单相感应电动机的瞬态特性进行仿真计算,并对仿真结果进行分析。     

单相电源供电时三相感应电动机瞬态仿真研究

对三相感应电动机由单相电源供电和用电容器作为相平衡器的瞬态行为进行仿真分析。为了得到瞬态特性，根据三相感应电动机在A、B、C相坐标系下的动态数学模型和推导出三相定子绕组端电压约束条件，编写计算机仿真程序，通过实例对Y接法的三相感应电动机由单相电源供电和用电容器作为相平衡器时的瞬态过程进行仿真计算，对仿真结果进行分析；用对称分量法分析了电动机对称运行时需要满足的条件，并由此初步计算电容的数值，然后通过计算机仿真较准确地加以确定。     

基于Magnet的六相感应电动机建模及仿真研究

在Magnet环境中建立六相感应电动机模型,并采用梯形波相电流对其驱动;分析了转矩电流和转子电流的关系,表明梯形波相电流实现了励磁电流和转矩电流的分立控制;对电磁场进行2D瞬态磁场仿真,分析了等磁势分布情况、磁感应强度波形、稳态电磁转矩和转矩电流的关系;添加Motion单元,对电动机的启动性能进行2D动态仿真。仿真结果表明,电动机空载和负载运行时电磁转矩响应速度快,无明显电磁转矩脉动和转速脉动,说明采用梯形波相电流驱动电动机的方法切实可行,仿真参数设置合理,为最终实现电动机的性能优化提供了参考。     

基于Intel196的感应电动机软起动器

提出了一种以Intel196单片机为控制核心的感应电动机软起动控制与保护系统,通过控制主回路上三对反并联晶闸管的导通角度,实现交流感应电动机的平滑起动和停机。根据电动机拖动负载的不同特点,设计了多种软起动方式。试验结果表明,该软起动器具有优良的性能。     

感应电动机的闭环控制系统设技

本文研究了用电压矢量变频器和感应电动机构成的变频电动机系统。通过对该闭环控制系统数学模型的建立,推导出了它的传递函数。它有着与可控硅直流调速系统极其相似的传递函数,因而可用直流电动机的闭环控制对该系统加以控制。通过实际的测试,得到比较满意的结果。     

感应电动机一种节能控制策略的仿真研究

本文提出了在恒转矩条件下,使电动机的功率因数和效率的乘积最大的方法,并将该方法应用于非线性解耦控制的感应电动机调速系统。仿真结果表明该方法切实可行并具有节能效果。     

Three-phase induction motor impulse drive method

A three-phase induction motor is successfully driven in a stepwise motion, that is, one small rotating angle of the motor shaft at a time. This is accomplished by applying a three-phase power source voltage in pulse form through thyristors to the primary winding of the motor. The drive method based on this entirely new principle is dubbed "impulse drive." It is classified into six types with somewhat different characteristics depending on the construction of the thyristor circuit. The torque generated by each type consists of pulsed positive and negative portions in a pair for each cycle. Theoretical as well as experimental investigations of the torque generated are given, together with various characteristics of a positioning machine. This machine makes the most of this drive method which is especially suited for controlling speed in very low-speed regions below several r/min.     

感应电动机调速系统的自适应逆控制

针对电压源型逆变器供电的感应电动机调速系统,提出了一种自适应逆控制方法,实现了电磁转矩和定子磁链的解耦控制．应用得到的逆系统将多变量、非线性、强耦合的感应电动机调速系统解耦为电磁转矩和定子磁链两个一阶线性子系统,从而简化了各个闭环线性调节器的设计难度．为了提高系统的鲁棒性,利用递推最小二乘算法实时辨识电动机参数,降低了参数变化对系统性能的影响．使用MATLAB软件进行了仿真实验,实验结果验证了理论分析的正确性和控制方案的可行性．     

A new instantaneous reactive power based MRAS for sensorless induction motor drive

A model reference adaptive system (MRAS) based speed estimator for sensorless induction motor (IM) drive is proposed in this paper. The MRAS is formed with instantaneous reactive power and the estimated stator current vector. Current, being a vector quantity, is configured in terms of reactive power, which is a scalar quantity. The advantage is that we need not equate either or both the in-phase and quadrature components of the current vector. The performance of the estimator under regeneration is an important aspect, which is studied in this paper through the small signal analysis. Graphical representation in the speed–torque domain gives a clear idea about the stable and unstable zones of operation in the regenerating mode. Sensorless IM drive along with the proposed MRAS is verified through computer simulation.     

Hybrid control for speed sensorless induction motor drive

The dynamic response of a hybrid-controlled speed sensorless induction motor (IM) drive is introduced. First, an adaptive observation system, which comprises speed and flux observers, is derived on the basis of model reference adaptive system (MRAS) theory. The speed observation system is implemented using a digital signal processor (DSP) with a high sampling rate to make it possible to achieve good dynamics. Next, based on the principle of computed torque control, a computed torque controller using the estimated speed signal is developed. Moreover, to relax the requirement of the lumped uncertainty in the design of a computed torque controller, a recurrent fuzzy neural network (RFNN) uncertainty observer is utilized to adapt the lumped uncertainty online. Furthermore, based on Lyapunov stability a hybrid control system, which combines the computed torque controller, the RFNN uncertainty observer and a compensated controller, is proposed to control the rotor speed of the sensorless IM drive. The computed torque controller with RFNN uncertainty observer is the main tracking controller and the compensated controller is designed to compensate the minimum approximation error of the uncertainty observer instead of increasing the rules of the RFNN. Finally, the effectiveness of the proposed observation and control systems is verified by simulated and experimental results     

Parameter identification for induction motor simulation

The simulation of squirrel-cage induction motors is very useful to design frequency-controlled a.c. drives. For this purpose the parameters of the induction motor must assume suitable values.Parameter obtained by the open and short circuit tests give generally unsatisfactory results. In this paper it is therefore proposed to apply a suitable identification technique.By assuming the two axes equations as the model of the motor, the parameters are worked out by a curve fitting procedure of the steady state torque and current characteristics.Due to the nonlinearities in the model equations an iterative procedure is proposed which attains the absolute minimum.The parameter can be therefore worked out with a satisfactory accuracy as confirmed by the test presented in this paper.     

Adaptive sliding-mode-observer for sensorless induction motor drive using two-time-scale approach

This paper, presents a new sliding-mode-observer design for sensorless vector control of induction motors with rotor resistance estimation using two-time-scale approach. This approach, based on the singular perturbation theory, decomposes the observer error dynamics on two parts; fast part, associated to the stator-current observer, and slow part, associated to the rotor-flux observer. Using this decomposition, the rotor-flux-observer accuracy is guaranteed through the stator-current observer. Consequently, adaptive laws for rotor speed and rotor resistance estimations are easily derived using only measured and estimated stator currents and estimated rotor fluxes. The effectiveness of this new approach has been successfully verified through computer simulations, where the control algorithm is based on the indirect field oriented sliding-mode control.     

三相异步电机的Z-SOURCE驱动性能分析

通过SIMULINK/MATLAB对Z-SOURCE驱动系统进行仿真,研究电机在满负荷和空载两种情况下的电流、转速和电磁转矩,得到了一个满意的控制结果。     

A PC-based architecture for parameter analysis of vector-controlled induction motor drive

In this article a methodology for constructing a user interface for system control and data acquisition of a drive which is suitable for three-phase induction motors (3?IM) is presented. The entire hardware implementation is shown, including power and digital stages. Communication between the computer and the controller is engaged in order to enhance an analysis of power quality, adjust the controller parameters for tuning the flux and speed loops, and performance of the embedded algorithm. USB and Ethernet protocols have been put into operation in the user front-end because a high speed sample frequency is required in order to guarantee the real-time operation of the whole system. A software interface is developed using LabVIEW environment enabling features not only as filtering signals of phase voltage and current but also power spectrum measurements. Vector-controlled drive is programmed on a digital signal processor (DSP) in order to ensure efficient use of energy in the power stage and proper tracking of the reference at low and high speeds.     

Backstepping wavelet neural network control for indirect field-oriented induction motor drive

This study address a newly designed decoupling system and a backstepping wavelet neural network (WNN) control system for achieving high-precision position-tracking performance of an indirect field-oriented induction motor (IM) drive. First, a decoupling mechanism with an online inverse time-constant estimation algorithm is derived on the basis of model reference adaptive system theory to preserve the decoupling control characteristic of an indirect field-oriented IM drive. Moreover, based on the backstepping design methodology, a desired feedback control law is developed for ensuring the favorable control performance. However, the uncertainties, such as mechanical parameter uncertainty, external load disturbance, unstructured uncertainty due to nonideal field orientation in transient state, and unmodeled dynamics in practical applications, are difficult to know in advance. Thus, the stability of the desired feedback control may be destroyed. Due to the powerful approximation ability of WNN, a backstepping WNN control scheme is designed in this study to control the rotor position of an indirect field-oriented IM drive for periodic motion. This control scheme contains two parts: one is a WNN control that is utilized to mimic the desired feedback control law, and the other is a robust control that is designed to recover the residual part of approximation for ensuring the stable control characteristic. In addition, numerical simulation and experimental results due to periodic commands are provided to verify the effectiveness of the proposed control strategy.