容错逆变器驱动的PMSM双环预测控制的研究

为了提高三相四开关容错逆变器驱动的永磁同步电机调速系统的性能,提出了调速系统双闭环预测控制策略。在转速环中设计了带扰动补偿的模型预测控制方法,通过离散扰动观测器估计负载扰动并进行前馈补偿,与模型预测速度控制相结合得到[q]轴电流环的期望给定值。在电流环中设计了基于离散滑模的有限控制集模型预测控制方法。通过与传统PI、FCS-MPC方法进行仿真对比,验证了该方法在空载启动、给定转速突变以及存在负载扰动、参数变化时,可使容错逆变器驱动的永磁同步电机调速系统具有更好的动态响应能力和鲁棒性。     

基于分数阶滑模观测器的三相八开关容错逆变器驱动 永磁同步电机系统无传感器FCS–MPC

针对三相八开关容错逆变器的永磁同步电机(permanent magnet synchronous motor,PMSM)驱动系统,基于分数阶滑模变结构技术,提出了一种新颖的无速度传感器有限控制集模型预测控制(finite-control-set model predictive control,FCS–MPC)策略.通过驱动系统的运行模式建立三相八开关逆变器和永磁同步电机的数学模型;采用分数阶滑模变结构方法构造PMSM系统转速和反电动势的观测器,以实现对系统转速和反电动势快速准确地实时估计;利用改进型的FCS–MPC策略,以达到减少控制系统计算量和电磁转矩脉动的目的,与此同时,本文中的电流反馈特性的容错控制可有效抑制直流侧母线电容分压不均衡对系统运行产生的不利影响.仿真结果表明,该方法能够保证八开关容错逆变器驱动PMSM系统可靠稳定运行、具有良好的动态性能,并能降低定子电流总谐波失真值.     

基于对数变换的六相永磁容错电机故障预测研究

研究电力作动系统用永磁容错电机故障预测问题,有利于准确监控飞行器健康状态,为飞机维修提供决策支持;TS(2*2永磁容错电机特征信号复杂无序,传统灰色模型故障预测精度不高,基于此,提出一种新的故障预测改进方法;TS(2*2首先对原始故障能量特征序列进行对数变换处理,对序列进行一次累加生成,建立GM(1,1)灰色模型,最后将得到的拟合还原成模拟值,得到预测数据;TS(2*2结果表明,故障原始序列经过对数函数变换处理后,预测误差相比于未经处理的基本灰色模型降低了4.63%,预测精度提高到96.5%以上,有效提高了永磁容错电机的故障预测精度。     

电牵引采煤机五相逆变器驱动双电动机容错控制

考虑到电牵引采煤机多机协调运行的工况特点,提出了一种电牵引采煤机五相逆变器驱动双电动机容错控制方法。建立了两相静止坐标系下的采煤机五桥臂双电动机驱动系统数学模型,并阐明了限制双电动机最高转速的本质原因;在分析三相、五相逆变系统内在联系的基础上,进行了五桥臂逆变器零序信号注入PWM调制的详细推导。实验结果表明,该方法采取零序信号注入PWM调制的方式,仅需五相桥臂即可实现采煤机双三相电动机高性能独立控制。     

基于扩张状态观测器的无速度传感器容错逆变器驱动永磁同步电机系统自抗扰模型预测转矩控制

针对三相四开关逆变器驱动永磁同步电机(PMSM)系统,基于扩张状态观测器(ESO)技术,提出了无速度传感器的自抗扰模型预测转矩控制(ADRMPTC)策略.建立了三相四开关逆变器驱动PMSM系统的数学模型;采用ESO技术构造了PMSM系统转速观测器,以实现对转速快速准确地实时估计;用自抗扰控制器(ADRC)作为系统的转速调节器,以提高系统的鲁棒性;利用模型预测转矩控制(MPTC)方法,以达到减小转矩和磁链脉动的目的.所设计基于ESO的无速度传感器ADRMPTC策略能够使三相四开关逆变器驱动的PMSM系统可靠稳定运行,达到满意的转矩和转速控制效果.与基于PI的MPTC策略相比,本文控制策略使PMSM系统不仅具有良好的动态性能,而且具有较强的抗负载干扰能力.仿真结果验证了所提方法的正确性和有效性.     

一种可倾斜六旋翼无人机容错控制方法

常规六旋翼无人机在单个旋翼完全失效后, 存在姿态与高度不完全可控的情况, 此时采取降级控制策略会 使无人机失去静态悬停能力. 针对此问题, 本文提出了一种可倾斜旋翼的容错控制方法, 在经典旋翼结构布局的基 础之上, 将其中一个旋翼设计成可倾斜结构, 通过倾斜角度的改变与控制分配重构, 无人机在任意单个旋翼完全失 效后均能保持力与力矩的平衡. 利用线性规划方法得到无人机的可达力矩集, 同时对电机饱和度进行分析, 确定了 不同旋翼失效后的最优倾斜角. 搭建飞行测试平台进行对比验证, 实验结果表明, 本文提出的方法具有良好的容错 效果与鲁棒性, 能够保证六旋翼无人机在故障后的稳定飞行与平稳降落.     

开关磁阻电机功率变换器容错控制方法

功率变换器是开关磁阻电机驱动系统易出现故障机构之一,为提高该驱动系统可靠性与容错性,本文以不对称半桥型功率变换器为研究对象,针对功率管短路与开路故障分别提出不同在线容错控制方法.通过对调故障相两功率管工作状态实现斩波功率管短路故障容错控制,基于细菌觅食算法(bacterial foraging algorithm)优化的PI速度控制器来降低转矩脉动以消除常闭功率管短路故障造成的恶性影响,并通过实时在线调整非故障相的导通角与关断角实现功率管开路故障容错控制.仿真与实验结果表明,所提方法能够根据故障诊断详情及时进行在线容错控制,且容错效果良好,无需增加任何硬件结构,操作简单易行,可避免故障运行造成的恶性影响.     

空间矢量调制矩阵变换器驱动的异步电机直接转矩控制系统

矩阵变换器较传统的变换器具有一系列优点而成为研究热点, 随着其理论研究的接近成熟, 逐渐转向应用研究.提出了一种新颖控制策略. 通过磁链和转矩的PI调节, 把矩阵变换器的空间矢量调制与异步电机的直接转矩控制有机地结合起来, 改进了系统的控制性能, 尤其是电磁转矩的低速性能. 这种PI调节器相对简单和具有较强的鲁棒性, 比较无差拍空间矢量调制而言. 本文首先阐述了传统的直接转矩控制原理和矩阵变换器的空间矢量调制,接着利用磁链和转矩的PI调节, 详细论述了两者的结合和实现过程, 并且在此基础上, 建立这种新型交流调速系统的仿真模型, 最后按照3种负载情况进行了仿真研究. 仿真结果验证了这种新颖控制策略的可行性和较强的鲁棒性.     

基于传感器故障的网络化系统鲁棒容错设计

针对一类具有参数不确定的非线性网络化控制系统,基于T-S模糊模型建模,推证出了确保非线性网络化控制系统在传感器发生失效故障时具有鲁棒完整性的时滞依赖充分条件,并以求解矩阵不等式给出了容错控制器的设计方法.最后以一个仿真算例验证了文中所述方法的可行性和有效性.     

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.     

Adaptive control of ac motor drives with inverter non-linearities

An ac motor drive consists of a dc-ac inverter, an ac motor and some mechanical load. The inverter supplies electrical power in an appropriate form to the motor, which in turn provides the conversion to mechanical power needed to drive the load. All three components of the system are characterized by models which are non-linear and contain unknown parameters. Improved motion control performance may thus be attempted by using non-linear adaptive control methods. In this paper, a linearizing adaptive motion controller is derived for a representative ac motor drive, under the assumption that the parameters describing the inverter, the motor, and its load, are all unknown. The controller guarantees global stability and asymptotic tracking.     

Adaptive fuzzy control for field-oriented induction motor drives

With the field-oriented method, the dynamic behavior of the induction motor is rather similar to that of a separately excited DC motor. However, the control performance of the induction motor is still influenced by the unmodelled dynamics or external disturbances, and to compensate for these uncertainties, adaptive fuzzy control is proposed. The overall control signal consists of two elements, (1) the equivalent control which is used for linearization of the induction motor’s model through feedback of the state vector. The equivalent control includes neurofuzzy approximators of the unknown parts of the induction motor model (2) the supervisory control which consists of an H_￥H_{\infty} term and compensates for parametric uncertainties of the induction motor model and external disturbances. The performance of the proposed adaptive fuzzy H_￥H_{\infty} controller is compared to backstepping nonlinear control through simulation tests.     

基于矩阵变换器的异步电机容错控制的研究

矩阵变换器(MC)具有输入输出特性好、电力谐波低、体积小等优良特性,但研究学者发现MC在实际应用中并不能稳定、可靠地运行,因而提出了不同的控制策略来提高其运行稳定性。本文提出一种MC的容错控制方法,使MC—电机系统在出现故障的情况下依然能够稳定运行或者安全停车,并对MC的输出进行谐波分析。仿真实验验证了采用容错控制能够提高矩阵变换器的运行稳定性,证明了这一理论的正确性和可行性。     

Slip ring induction motor speed control using a thyristor inverter

A closed-loop speed control scheme for a slip ring induction motor is described in this paper. The speed control is achieved through slip power recovery with the aid of static power devices. The design of the controllers is considered. Experimental results are given and compared with the analytical results.     

电动汽车感应电机驱动系统效率优化控制

针对电动汽车感应电动机变频驱动系统存在的轻载低效问题,考虑电机定转子铜损和铁损,研究了感应电动机变频驱动系统效率优化控制算法．采用减小磁链搜索范围的方法,改进了黄金分割法在线搜索控制器,设计了以数字信号处理器TMS320LF2407为控制电路核心的实验系统,对损耗模型控制算法、黄金分割法和改进的黄金分割法在线搜索控制算法分别进行了对比实验研究．实验结果表明,两类控制策略都能够有效提高感应电动机变频驱动系统的运行效率;基于损耗模型的控制算法具有寻优速度快、磁链和转矩波动小的优点,而改进的黄金分割法搜索控制器算法简单,效率优化效果优于基于损耗模型的控制器;在线搜索控制算法不受电机参数变化及建模精度的影响,具有更为广泛的应用前景．     

Robust output feedback learning control for induction motor servo drives

This paper addresses the output feedback tracking control problem for induction motor servo drives with mechanical uncertainties: rotor angle, rotor speed and stator currents are assumed to be available for feedback. A robust adaptive learning control is designed under the assumption that the reference profile for the rotor angle is periodic with known period: it ‘learns’ the periodic disturbance signal by identifying the Fourier coefficients of any truncated approximation; ??₂ and ??_∞ transient performances are guaranteed in the ‘learning phase’. It is shown that, for any motor initial condition belonging to an arbitrary given compact set, by properly setting the control parameters: (i) the rotor position and flux modulus tracking errors exponentially converge to residual sets, which may be arbitrarily reduced by increasing the number of terms in the truncated Fourier series; (ii) when the unknown periodic disturbance can be represented by a finite Fourier series, the rotor position and flux modulus tracking errors exponentially converge to zero. As in field oriented‐control, the control algorithm generates references for the magnetizing flux component and for the torque component of the stator current leading to significant simplifications for current‐fed motors. Copyright © 2008 John Wiley & Sons, Ltd.     

Learning control for induction motor servo drives with uncertain rotor resistance

The tracking control problem for induction motor servo drives with mechanical and electrical uncertainties is addressed. Under the assumptions that the reference profile for the rotor angle is periodic of known period and the rotor flux modulus reference signal is persistently exciting, a robust adaptive learning control is designed, which is adaptive with respect to the uncertain rotor resistance and is able to ‘learn’ the periodic disturbance signal due to mechanical uncertainties by identifying the Fourier coefficients of its truncated approximation.     

应用于感应电机矢量控制中的逆变器死区补偿

为了减小电压源型逆变器死区时间引起的输出电压畸变,对死区产生的原因进行分析,总结出三点原因,列出误差电压计算公式,最后运用到感应电机矢量控制中,对u_a、u_b、u_c三项输入到逆变器中的电压进行补偿。该补偿策略首先计算控制周期内的误差时间,算出误差时间与电流的对应关系,最后将算出的周期T_S内误差电压补偿到逆变器输入端上。通过补偿误差电压,降低了电流谐波对控制系统的影响,同时电网侧的能量利用率得到了提高。实验结果表明,该策略对电流波形起到了改善作用。     

Application of CMAC neural network to the control of induction motor drives

In this paper, a cerebellar-model-articulation-controller (CMAC) neural network (NN) based control system is developed for a speed-sensorless induction motor that is driven by a space-vector pulse-width modulation (SVPWM) inverter. By analyzing the CMAC NN structure and motor model in the stationary reference frame, the motor speed can be estimated through CMAC NN. The gradient-type learning algorithm is used to train the CMAC NN online in order to provide a real-time adaptive identification of the motor speed. The CMAC NN can be viewed as a speed estimator that produces the estimated speed to the speed control loop to accomplish the speed-sensorless vector control drive. The effectiveness of the proposed CMAC speed estimator is verified by experimental results in various conditions, and the performance of the proposed control system is compared with a new neural algorithm. Accurate tracking response and superior dynamic performance can be obtained due to the powerful online learning capability of the CMAC NN.