直接转矩控制全阶磁链观测器的设计及离散仿真

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。     

基于改进滑模策略永磁同步电机SVM-DTC控制

传统的永磁同步电机直接转矩控制采用双滞环结构,因而电机转矩和磁链脉动较大。SVM控制方法通过合成最合理的电压矢量对转矩和磁链作精确补偿,能够一定程度上降低二者的脉动,但传统SVM控制方法包含了转速和转矩两个PI调节器,两个调节器的参数设计比较复杂,且直接影响了电机性能。提出用快速终端滑模（FTSM）控制器来代替传统PI转速调节器,为了克服滑模带来的抖振,设计负载转矩观测器,并将观测值反馈至滑模控制器。仿真和实验结果表明所提控制方法改善了系统的动静态性能,抗干扰能力增强,同时SMC固有抖振现象得到有效抑制。     

一种基于二阶广义积分器的永磁同步电机定子磁链观测方法

永磁同步电机的定子磁链观测技术是实现直接转矩控制的基础。传统的电压模型定子磁链观测器中存在着直流偏置、积分饱和等问题,因此本文采用改进的二阶广义积分器(improved second-order generalized integrator, ISOGI)代替电压模型中的纯积分器,进而得到一种改进的基于ISOGI的定子磁链观测器。与传统的电压模型定子磁链观测器相比,该观测器有效提高了定子磁链的观测精度。仿真和实验结果表明基于ISOGI的定子磁链观测器是可行的。本文网络版地址：http：//www.eepw.com.cn/article/276359.htm     

基于全维状态观测器的永磁同步电机无差拍直接转矩控制

永磁同步电机传统的直接转矩控制存在磁链幅值和转矩脉动大的缺点。文中研究了基于状态观测器的无差拍直接转矩控制方案,通过构造全维状态观测器的方法来观测定子磁链幅值,消除了初始磁链误差以及电机参数对传统的观测方法影响的问题。此外针对传统控制系统产生的时滞现象,文中的研究提前一个周期计算出所需的电压矢量,实现了转矩和磁链无差拍控制。仿真结果表明,所提出的基于全维状态观测器的无差拍控制能较好地抑制磁链和转矩脉动,具有良好的控制性能。     

基于空间矢量调制的PMSM直接转矩控制研究

针对传统的直接转矩控制（DTC）出现的开关频率不恒定,磁链和转矩脉动大的问题,提出一种基于空间矢量调制的直接转矩控制（SVM-DTC）方法。该方法集合了直接转矩控制响应快、矢量控制连续平滑的优点,以永磁同步电机（PMSM）数学模型为基础,建立转矩、磁链双闭环PI控制回路。采用空间电压矢量调制策略,将转矩和磁链作为控制量。仿真结果表明,相对于传统的直接转矩控制,基于空间矢量调制的直接转矩控制方案的开关频率恒定,转矩、磁链脉动小,系统具有良好的动、静态性能,验证了该方法的可行性和有效性。     

检测感应电机磁链的闭环方法

要实现电磁转矩和磁链的解耦控制,必须得到足够精确的磁链检测值。计算磁链不可避免地受到电机参数不准确以及测量干扰的影响。磁链的开环检测方法缺少对各种干扰的抑制,通过引入反馈来抑制干扰和变参数的影响是简单而有效的,称为检测磁链的闭环方法。介绍四种检测磁链的闭环方法:(1)使用电流反馈的改进的电压模型法;(2)现代控制理论的观测器法;(3)滑模观测器法;(4)人工神经网络法。     

异步电机全阶自适应磁链观测和速度辨识

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。     

基于BP网络的开关磁阻电机变磁链DTC方法研究

文章针对传统定磁链双闭环DTC调速系统稳态时定子电流幅值较大、电机铜耗增加的问题,提出了变磁链给定的解决方案,建立了变磁链三闭环DTC调速系统。仿真结果证明,此调速系统动、静态性能良好,既能充分抑制SRM的转矩脉动,又能在稳态时降低定子电流的幅值,解决了电机高速时铜耗较大的问题。另外,针对变磁链三闭环DTC调速系统控制参数复杂,实时性要求高的特点,文章将BP神经网络PID控制器与传统PI控制器复合,构成了BP-PI控制器。仿真表明,BP-PI控制器有效克服了单一神经网络DTC控制器存在的缺陷,动、静态性能明显优于传统PI调节器,显著提高了调速系统的自适应性和鲁棒性。     

基于ESO磁链观测器的直接转矩控制的研究

讨论直接转矩控制方法在永磁同步电机中的应用问题,利用MATLAB仿真工具对永磁同步电机直接转矩控制系统仿真。针对直接转矩控制低速时存在较大转矩脉动的问题,采用观测器方法克服传统磁链模型中参数的不确定性对磁链观测精度的影响,保证全速范围内磁链的准确估计,提高控制性能。仿真表明观测磁链具有较高的精度,对电阻的不确定变化具有较强的鲁棒性,并可准确估计无速度传感器的速度及位置。     

基于自适应状态观测器的异步电机无速度传感器矢量控制系统

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。     

A hybrid computed torque controller using fuzzy neural network formotor-quick-return servo mechanism

The dynamic response of a hybrid computed torque controlled quick-return mechanism, which is driven by a permanent magnet (PM) synchronous servo motor, is described in this paper. The crank and disk of the quick-return mechanism are assumed to be rigid. First, Hamilton's principle and Lagrange multiplier method are applied to formulate the mathematical model of motion. Then, based on the principle of computed torque control, a position controller is designed to control the position of a slider of the motor-quick-return servo mechanism. In addition, to relax the requirement of the lumped uncertainty in the design of a computed torque controller, a fuzzy neural network (FNN) uncertainty observer is utilized to adapt the lumped uncertainty online. Moreover, a hybrid control system, which combines the computed torque controller, the FNN uncertainty observer, and a compensated controller, is developed based on Lyapunov stability to control the motor-quick-return servo mechanism. The computed torque controller with FNN 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 rule numbers of the FNN. Finally, simulated and experimental results due to periodic step and sinusoidal commands show that the dynamic behaviors of the proposed hybrid computed torque control system are robust with regard to parametric variations and external disturbances     

基于模糊控制的感应电机直接转矩控制系统

根据直接转矩控制理论,在Matlab 6.5/Simulink下构造了一个感应电机直接转矩控制系统的仿真模型。为改善感应电机系统的动、静态品质,设计了模糊自适应PI速度调节器,根据速度偏差与偏差变化率,通过模糊推理在线调整PI参数,提高系统的调速性能。仿真结果表明,这种模糊控制器具有比常规PID控制器更好的控制效果。     

NPC三电平逆变器中点电位观测器设计及控制

针对中点嵌位型（Neutral Point Clamp,NPC）三电平逆变器的中点电压波动会引起输出电压失真的问题,设计了一种观测器对中点电压波动进行观测,并根据观测结果设计了模糊PI控制器对其进行控制。首先建立了NPC三电平逆变器的数学模型,通过对直流侧电容电压的数学模型进行分析,将逆变器的中点电位不平衡问题近似为系统存在扰动下的误差估计;其次,根据模糊逻辑规则定义了新的误差变量,设计了模糊PI控制器,对中点电位波动问题进行控制;最后通过仿真和实验结果表明：设计的观测器可有效完成对中点电位的准确观测,利用模糊PI控制器实现了对中点电压波动的有效控制。     

Vibration Suppression Using Single Neuron-Based PI Fuzzy Controller and Fractional-Order Disturbance Observer

An approach is proposed for vibration suppression in a two-inertia system using an integration of a fractional-order disturbance observer and a single neuron-based PI fuzzy controller. The former is used to obtain disturbance estimate and generate compensation signal, and the latter is utilized to realize outer loop control. Fractional-order disturbance observer has a wider range to select a suitable tradeoff between robustness and vibration suppression, because introduction of fractional calculus makes universe of relative degree of Q-filter is expanded from integer domain to real-number domain. For the single neuron-based PI fuzzy controller, a single neuron makes up a PI controller and such a controller is embedded in each cell of the fuzzy control table. Thus, the fuzzy control table is changed into a controller matrix and it constructs a nonlinear adaptive controller with parameter self-tuning property. Experimental results illustrate that the integration of fractional-order disturbance observer and single neuron-based PI fuzzy controller can improve the performance of disturbance attenuation and system robustness     

Decoupled stator-flux-oriented induction motor drive with fuzzyneural network uncertainty observer

A stator-flux-oriented induction motor drive using online rotor time-constant estimation with a robust speed controller is introduced in this paper. The estimation of the rotor time constant is made on the basis of the model reference adaptive system using an energy function. The estimated rotor time-constant is used in the current-decoupled controller, which is designed to decouple the torque and flux in the stator-flux-field-oriented control. Moreover, a robust speed controller, which is comprised of an integral-proportional speed controller and a fuzzy neural network uncertainty observer, is designed to increase the robustness of the speed control loop. The effectiveness of the proposed control scheme is demonstrated by simulation and experimental results     

基于模糊神经网络的异步电机DTC研究

针对异步电机直接转矩控制在低速时脉动大、开关频率不固定等缺陷,提出了一种基于模糊神经网络的直接转矩控制方案,该方案采用模糊神经网络调节器分别对转矩和磁链进行控制。该控制方法综合了模糊控制和神经网络的优点,原理简单、无需大量专家经验、具有优良的非线性逼近和自适应能力。最后通过仿真实验证明,采用该控制器的异步电机系统动态性能良好、低速脉动小。     

High-performance speed servo system considering Voltage saturation of a vector-controlled induction motor

Generally, a speed servo system of a vector-controlled induction motor has limitations of motor voltage and current. When the speed servo system has a large torque reference, the output of its PI controller is often saturated. In this case, the conventional servo system stops the integral calculation of its PI controller. However, this system often has a large overshoot and/or an oscillated response caused by both a windup phenomenon and phase error on the vector control condition. This paper proposes a new speed servo system considering voltage saturation for the vector-controlled induction motor. The proposed control method compensates the phase error on vector control condition quickly, and always keeps the vector control condition. The experimental results show that the proposed system well regulates the motor speed and the secondary magnetic flux for a large torque reference without a windup phenomenon.