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1.
在交流异步机数学模型的基础上,建立异步电机直接转矩控制系统。对电机状态值和测量值之间偏差进行反馈校正,并把反馈校正项与估计磁链的电机数学模型结合起来,建立含有闭环状态估计的误差补偿器的全阶磁链观测器;利用Matlab/Simulink构建全阶磁链观测器,对构建的模型进行离散仿真,得到定子磁链的仿真波形,验证了全阶磁链观测器的正确性。  相似文献   

2.
程国栋 《变频器世界》2014,(4):65-68,83
异步电机无速度传感器矢量控制系统是目前研究的热点,本文采用一种闭环磁链观测器,即自适应状态观测器对转子磁链进行观测,与传统开环电压、电流模型相比,观测效果更好。在转子磁链观测的基础上,采用PI型自适应律,对转速进行了辨识。最后,通过Matlab仿真验证了本文给出的异步电机无速度传感器矢量控制系统的可行性,仿真结果表明该系统具有较好的动、静态性能,并具有一定的抗干扰能力。  相似文献   

3.
《信息技术》2017,(9):143-146
针对当前无速度传感器的控制方法中,存在低频时无法稳定运行、转速估算不精准、计算量偏大等问题,利用鲁棒性控制理论、线性矩阵不等式(LMI)来选择观测器的增益,推导了符合稳定性与收敛性要求的自适应律。并在此基础上,优化设计了转子速度和定子电阻能同时观测的自适应全阶磁链观测器,以此来对转子速度进行准确估算,确保电机在全速范围内稳定运行。用MATLAB对自适应全阶磁链观测器进行模型仿真,最后以实时ADI半实物仿真试验系统验证了在实际运用中自适应全阶磁链观测器的设计在全速范围内准确估算转速的可行性,且有良好的抗负载扰动能力。  相似文献   

4.
本文依据异步电机矢量控制的基本原理,构建了无速度传感器的矢量控制系统。该系统中采用了转子磁链观测器方法,并运用模型参考自适应法进行了转子速度的估计。文中通过了Matlab/Simulink构建系统仿真模型,结果表明了系统的正确性与可行性。  相似文献   

5.
本文介绍了异步电动机直接转矩控制的基本原理,提出了基于自适应全阶磁链观测器的速度估算方法,实现了无速度传感器的速度辨识.并应用Matlab/SimulinK软件对该系统进行了建模和仿真,仿真结果表明,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.  相似文献   

6.
本文介绍了异步电动机直接转矩控制的基本原理,提出了基于自适应全阶磁链观测器的速度估算方法,实现了无速度传感器的速度辨识。并应用Matlab/Simulink软件对该系统进行了建模和仿真,仿真结果表明,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。  相似文献   

7.
由于电机定转子参数的变化,利用一般的转子磁链对转速进行估算,将导致不能得到准确的结果。这里采用积分型转子磁链的参考和可调模型构建出一个基于MRAS的异步电机无速度传感器的矢量控制模型。该模型提高了矢量控制系统的动态性能并利用MATLAB,sIMULINK进行了异步电机无速度传感器矢量控制系统的仿真,验证了文中所采用的模型参考自适应的速度估算方法的可行性以及对参数误差的鲁棒性。  相似文献   

8.
为提高异步电机直接转矩控制系统的低速性能,本文中提出了一种模糊控制和PI闭环校正磁链观测器相结合的控制方法。该方法采用PI闭环校正磁链观测器代替传统U-I模型,给磁链和转矩误差分级,用模糊控制代替传统滞环控制选择合适的电压矢量.为减少模糊控制规则和加快模糊推理,定义了定子磁链角映射。仿真结果表明,此方法能够提高磁链的观...  相似文献   

9.
针对传统的直接转矩控制系统采用纯积分的电压模型作为磁链观测器,存在着误差积累以及直流偏移,导致电流和转矩的波动问题,提出了一种基于定子磁链的自适应全阶观测器的直接转矩控制系统,并实现了速度辨识。仿真实验表明:采用自适应磁链观测器具有较高的观测精度和较好的鲁棒性。  相似文献   

10.
建立了一种滑模速度观测器,用于电机转速的精确观测。该观测器充分利用电机状态方程具有的结构特点,设计出简单有效的速度估算方法,在转子磁链的估算中无须用到转子时间常数和转速等信息,提高了观测器对于参数误差的鲁棒性。将所建立的观测器和空间电压矢量脉宽调制技术(SVPWM)结合对电机进行控制,进一步提高了系统的调速性能。仿真结果验证了基于滑模控制理论的异步电机无速度传感器直接转矩控制系统的可行性以及对参数误差的鲁棒性。  相似文献   

11.
A novel control technique for sensorless vector control operation of a double-inverter-fed wound-rotor induction motor is presented. Two current controllers control the stator-side currents based on a vector control algorithm. Another V/f-type flux and frequency controller controls the rotor-side frequency directly. A novel frequency command profile for the rotor-side controller is suggested to make this sensorless drive operation reliable and reduce dependence on motor parameters at any rotor speed. A complete inverter power flow analysis is presented to show that the drive can deliver full torque from 0- to 2-p.u. speed for either direction of rotation. Thus, double the rated power can be extracted from the induction motor without overloading it. The proposed algorithm allows the drive to start on-the-fly without any rotor transducer. Results from a prototype 50-hp drive are presented.  相似文献   

12.
基于模型参考自适应系统的感应电机控制   总被引:2,自引:0,他引:2  
采用模型参考自适应法设计了无速度传感器矢量观测器。现以电压模型为参考模型,电流模型为可调模型,推算出速度信息,计算输出控制信号,实现了对感应电机的精确控制;通过Matlab/Simulink对其进行仿真、验证,结果表明,该系统对定子磁链观测精度高,速度估计准确,改善了电机的控制特性。  相似文献   

13.
This paper proposes a programmable low pass filter (LPF) to estimate stator flux for speed sensorless stator flux orientation control of induction motors. The programmable LPF is developed to solve the DC drift problem associated with a pure integrator and a LPF. The pole of the programmable LPF is located far from the origin in order to decrease the time constant with the increasing speed. In addition, the programmable LPF has a phase/gain compensator to estimate exactly stator flux in a wide speed range. Consequently, the drift problem is much improved and the stator flux is exactly estimated in the wide speed range. The validity of the proposed programmable LPF is verified by speed sensorless vector control of a 2.2 kW three-phase induction motor  相似文献   

14.
Various control algorithms have been proposed for the speed-sensorless control of an induction motor. These sensorless algorithms are mainly based on the speed feedback with the flux and speed estimations. This paper proposes a new scheme for the speed-sensorless control of an induction motor. The proposed scheme is based on the current estimation without the flux and speed estimations, in which the controlled stator voltage is applied to the induction motor so that the difference between stator currents of the mathematical model and motor may be forced to decay to zero. The performance of the proposed scheme is verified through simulation and experiment.  相似文献   

15.
崔超群 《电子质量》2010,(7):21-22,33
在高性能的交流异步电机矢量控制系统中,速度传感器的高成本和困难的安装条件限制了交流异步电动机的应用,因此无速度传感器的控制技术成为发展趋势。本文阐述了以数学模型的开环估计转速控制算法为核心,采用ADSP-BF518芯片设计了三相交流异步电动机无速度传感器矢量控制系统,具有一定的实用价值。  相似文献   

16.
This paper presents a sensorless vector control system for general-purpose induction motors, which is based on the observer theory and the adaptive control theories. The proposed system includes a rotor speed estimator using a q-axis flux and stator resistance identifier using the d-axis flux. The advantages of the proposed system are simplicity and avoidance of problems caused by using only a voltage model. Since the mathematical model of this system is constructed in a synchronously rotating reference frame, a linear model is easily derived for analyzing the system stability, including the influence of the observer gain, motor operating state, and parameter variations. In order to obtain stable low-speed operation and speed control accuracy, an algorithm for compensating for the deadtime of the inverter and correcting the nonideal features of an insulated gate bipolar transistor was developed. The effectiveness of the proposed system has been verified by digital simulation and experimentation  相似文献   

17.
本文针对2500kW同步电机交一直一交变频调速系统,提出了一种基于模型参考自适应算法(MRAS)的转速辨识方法,依照MRAS方法把得到的转速自适应结构运用到系统中,替代了电机上的传感器和系统的磁链观测单元,达到了转速和磁链幅值、角度的一同辨识,并在PSIM中构建了仿真模型。结果表明,采用无速度传感器的矢量控制方法具有较好的准确性以及更好的鲁棒性。  相似文献   

18.
This paper presents a new method of online estimation for the stator and rotor resistances of the induction motor for speed sensorless indirect vector controlled drives, using artificial neural networks. The error between the rotor flux linkages based on a neural network model and a voltage model is back propagated to adjust the weights of the neural network model for the rotor resistance estimation. For the stator resistance estimation, the error between the measured stator current and the estimated stator current using neural network is back propagated to adjust the weights of the neural network. The rotor speed is synthesized from the induction motor state equations. The performance of the stator and rotor resistance estimators and torque and flux responses of the drive, together with these estimators, are investigated with the help of simulations for variations in the stator and rotor resistances from their nominal values. Both resistances are estimated experimentally, using the proposed neural network in a vector controlled induction motor drive. Data on tracking performances of these estimators are presented. With this speed sensorless approach, the rotor resistance estimation was made insensitive to the stator resistance variations both in simulation and experiment. The accuracy of the estimated speed achieved experimentally, without the speed sensor clearly demonstrates the reliable and high-performance operation of the drive  相似文献   

19.
感应电机高动态控制的困难性在于感应电机是一个高阶、非线性的复杂系统。异步电动机传统方法采用模型为基础的无速度传感器磁场定向控制,高性能矢量控制系统中需采用速度闭环控制。为了提高异步电机无速度传感器矢量控制的控制性能,将其与矢量控制结合起来,组成一种基于TMS320F2812的无速度传感器矢量控制系统。本文主要介绍了硬件实现其软件实现方法,并且通过MATLAB仿真验证了所提出方法的有效性使系统具有良好的动态性能以及稳定性。  相似文献   

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