永磁交流伺服系统速度检测与控制研究
|
摘要
目前永磁交流伺服系统常见控制策略有矢量控制,直接转矩控制,无位置传感器控制等,也有很多新控制策略层出不穷,如智能控制、滑模控制等。由于其广泛地应用于航空航天、数控机床、机器人、工业电气自动化等行业,人们对其伺服性能要求越来越高,因此许多科技工作者还在孜孜不倦地研究伺服系统的一些关键环节和细节处理。本文主要针对矢量控制系统速度环进行一些探讨,在速度检测、速度控制器设计、转动惯量辨识等影响速度性能的环节做一些新尝试和研究。
首先,针对M法中根据位置编码器计算输出速度之缺陷,提出单维卡尔曼滤波器计算速度,并在此基础上计算加速度。分析M法测速特点后,建立系统噪声方差自适应的单维卡尔曼滤波器估算电机转速,由于系统误差主要与转速及其变化程度有关系,所以构建一个含转速及其变化程度的多项式关系式近似表示自适应噪声方差。以卡尔曼滤波器输出速度为参考速度,运用软件锁相环估算加速度,避免微分运算就可计算加速度。
然后,为调节基于PI控制的速度环PI系数需要辨识出转动惯量,提出用蚁群矢量移动算法同时辨识永磁交流伺服系统负载运行时的转动惯量和负载转矩,以利于速度环PI参数整定和转矩补偿。运用采样得到的d轴电流和速度序列数据,基于最小方差原理,建立蚂蚁信息素散发模型,使得蚂蚁位置与实际转动惯量和负载转矩越接近,蚂蚁散发的信息素越大。根据蚁群总信息素分布情况,计算蚁群的理想分布期望,与实际蚁群分布比较后,启发蚁群矢量移动,并朝最优方向聚集,收敛点为辨识最优解。另外,分析电机模型后,建立电机输出量的误差函数,使之含有各种待估参数,引入单层神经网络,运用梯度方法动态更新权值,再通过权值估算电机参数。
接着,提出最小拍法设计速度控制器。研究用最小拍无纹波数字化方法设计永磁交流伺服系统速度控制器。把电机传动过程模型的连续域传递函数转换成数字域Z形式传递函数,根据速度指令的Z变换输入形式,事先设定预期误差传递函数,使得在有限拍内就能输出稳定的速度信号,然后依据最小拍无纹波零极点配置原则,反推出数字控制器的形式,并使速度控制器输出的电流指令信号在有限拍内就能稳定。最后,描述柔性连接引起的速度谐振问题,利用IIR和FIR方法设计陷波器,比较两种方法,并做理论仿真。
本文提出的一些思路和方法有一定效果,以后研究中需要坚持不懈地完善这些方法,使之能够满足工程需求且应用于实际产品中。
The permanent magnet synchronous motor (PMSM) AC servo system has employed many perfect control strategies, such as vector control, direct torque control, sensorless control, and even many novel control strategies including intelligent control, sliding mode control,etc., have been applied into the system. However, because of its widely use in aerospace, machine tools, robotics, industrial automation, electrical industry and so on, it needs more and more high performance,and many scientists are still diligently studying some key aspects and detail technologies about the servo system. In this paper,some research about velociy control based on the vector control system such as identification of the moment of inertia, the design of speed controller,etc., which affect the servo sytem's performance, have been done through other new methods.
Firstly, the angular velocity and acceleration through first-order and second-order differential calculation of the position pulses from photoelectric encoder have serious errors. Single-dimension Kalman filter with adaptive system noise variance is proposed to estimate velocity, since the noise variance is associated with velocity and its variations. Combining with virtual error model method presented by Jazwinski, a polynomial expression multiplied by exponential is established to describe the adaptive noise variance approximately. Regarding the velocity out of Kalman filter as the reference input, the software PLL-type regulator is utilized to estimate acceleration, whose integral is another estimated velocity. Regulating the optimal proportional gain and integral gain, the acceleration can be estimated without differential computation when the PLL's estimated velocity can strictly follow the Kalman filter's estimated velocity. The step velocity and sinusoidal velocity signals are used to verify the above algorithm. The results demonstrate that the simplified single-dimension Kalman algorithm becomes succinct, and the filtered speed becomes smooth without jump and obvious ripple phenomenon, and the acceleration has fewer spikes than that of the differential method.
Secondly, the ant colony vector moving algorithm is proposed to identify the load torque and moment of inertia for load-running PMSM servo system while run-time loading, in order to adjust the PI parameters and compensate the torque. Vector moving is decomposed into horizontal and vertical directions, one for moment of inertia, the other for load torque, and every ant position means one possible solution. With the sampled sequences of d-axis current and speed data, based on the minimum variance principle, the pheromone expression model is established, making the closer distance between the ant position and actual load and inertia, the more pheromone. The expecting distribution for ant colony is calculated after the total pheromone statistics. The ant colony is inspired to move towards the optimal direction with the convergence point for the identified results. The normalized distribution for ant colony is selected to improve convergence performance when the dynamic ant colony distribution is converted to the normalized range. Additonally, after analyzing the motor model, the output quantities error function which contains the parameters to be estimated, is established. The single-layer neural network using gradient method to dynamically update the weights is proposed to achieve estimation. Learning rate affects estimation accuracy and convergence rate.
Then, the deadbeat ripple-free method is proposed for the design of PMSM servo system's digital speed controller. The continuous domain transfer function of PMSM drive model is converted into the form of discrete Z-domain transfer function. According to the speed command input in the Z-transform form, the error transfer function is pre-determined, making the speed can be output stable within a limited sample periods. Then on the basis of deadbeat ripple-free zero-pole configuration principle, the Z-form digital speed controller is derived to keep the current command from the controller become stable in several periods.Finally, to resolve the velocity resonace in the spring connection, the notch filter is designed by FIR and IIR method.
The proposed ideas and methods have been verified by simulations and experiments, and the results shows that they are effective.In the follow-up study, these methods required to be constantly further improved so that they can be applied to the practical products.
首先,针对M法中根据位置编码器计算输出速度之缺陷,提出单维卡尔曼滤波器计算速度,并在此基础上计算加速度。分析M法测速特点后,建立系统噪声方差自适应的单维卡尔曼滤波器估算电机转速,由于系统误差主要与转速及其变化程度有关系,所以构建一个含转速及其变化程度的多项式关系式近似表示自适应噪声方差。以卡尔曼滤波器输出速度为参考速度,运用软件锁相环估算加速度,避免微分运算就可计算加速度。
然后,为调节基于PI控制的速度环PI系数需要辨识出转动惯量,提出用蚁群矢量移动算法同时辨识永磁交流伺服系统负载运行时的转动惯量和负载转矩,以利于速度环PI参数整定和转矩补偿。运用采样得到的d轴电流和速度序列数据,基于最小方差原理,建立蚂蚁信息素散发模型,使得蚂蚁位置与实际转动惯量和负载转矩越接近,蚂蚁散发的信息素越大。根据蚁群总信息素分布情况,计算蚁群的理想分布期望,与实际蚁群分布比较后,启发蚁群矢量移动,并朝最优方向聚集,收敛点为辨识最优解。另外,分析电机模型后,建立电机输出量的误差函数,使之含有各种待估参数,引入单层神经网络,运用梯度方法动态更新权值,再通过权值估算电机参数。
接着,提出最小拍法设计速度控制器。研究用最小拍无纹波数字化方法设计永磁交流伺服系统速度控制器。把电机传动过程模型的连续域传递函数转换成数字域Z形式传递函数,根据速度指令的Z变换输入形式,事先设定预期误差传递函数,使得在有限拍内就能输出稳定的速度信号,然后依据最小拍无纹波零极点配置原则,反推出数字控制器的形式,并使速度控制器输出的电流指令信号在有限拍内就能稳定。最后,描述柔性连接引起的速度谐振问题,利用IIR和FIR方法设计陷波器,比较两种方法,并做理论仿真。
本文提出的一些思路和方法有一定效果,以后研究中需要坚持不懈地完善这些方法,使之能够满足工程需求且应用于实际产品中。
The permanent magnet synchronous motor (PMSM) AC servo system has employed many perfect control strategies, such as vector control, direct torque control, sensorless control, and even many novel control strategies including intelligent control, sliding mode control,etc., have been applied into the system. However, because of its widely use in aerospace, machine tools, robotics, industrial automation, electrical industry and so on, it needs more and more high performance,and many scientists are still diligently studying some key aspects and detail technologies about the servo system. In this paper,some research about velociy control based on the vector control system such as identification of the moment of inertia, the design of speed controller,etc., which affect the servo sytem's performance, have been done through other new methods.
Firstly, the angular velocity and acceleration through first-order and second-order differential calculation of the position pulses from photoelectric encoder have serious errors. Single-dimension Kalman filter with adaptive system noise variance is proposed to estimate velocity, since the noise variance is associated with velocity and its variations. Combining with virtual error model method presented by Jazwinski, a polynomial expression multiplied by exponential is established to describe the adaptive noise variance approximately. Regarding the velocity out of Kalman filter as the reference input, the software PLL-type regulator is utilized to estimate acceleration, whose integral is another estimated velocity. Regulating the optimal proportional gain and integral gain, the acceleration can be estimated without differential computation when the PLL's estimated velocity can strictly follow the Kalman filter's estimated velocity. The step velocity and sinusoidal velocity signals are used to verify the above algorithm. The results demonstrate that the simplified single-dimension Kalman algorithm becomes succinct, and the filtered speed becomes smooth without jump and obvious ripple phenomenon, and the acceleration has fewer spikes than that of the differential method.
Secondly, the ant colony vector moving algorithm is proposed to identify the load torque and moment of inertia for load-running PMSM servo system while run-time loading, in order to adjust the PI parameters and compensate the torque. Vector moving is decomposed into horizontal and vertical directions, one for moment of inertia, the other for load torque, and every ant position means one possible solution. With the sampled sequences of d-axis current and speed data, based on the minimum variance principle, the pheromone expression model is established, making the closer distance between the ant position and actual load and inertia, the more pheromone. The expecting distribution for ant colony is calculated after the total pheromone statistics. The ant colony is inspired to move towards the optimal direction with the convergence point for the identified results. The normalized distribution for ant colony is selected to improve convergence performance when the dynamic ant colony distribution is converted to the normalized range. Additonally, after analyzing the motor model, the output quantities error function which contains the parameters to be estimated, is established. The single-layer neural network using gradient method to dynamically update the weights is proposed to achieve estimation. Learning rate affects estimation accuracy and convergence rate.
Then, the deadbeat ripple-free method is proposed for the design of PMSM servo system's digital speed controller. The continuous domain transfer function of PMSM drive model is converted into the form of discrete Z-domain transfer function. According to the speed command input in the Z-transform form, the error transfer function is pre-determined, making the speed can be output stable within a limited sample periods. Then on the basis of deadbeat ripple-free zero-pole configuration principle, the Z-form digital speed controller is derived to keep the current command from the controller become stable in several periods.Finally, to resolve the velocity resonace in the spring connection, the notch filter is designed by FIR and IIR method.
The proposed ideas and methods have been verified by simulations and experiments, and the results shows that they are effective.In the follow-up study, these methods required to be constantly further improved so that they can be applied to the practical products.
引文
[1]寇宝泉,程树康.交流伺服电机及其控制[M].北京：机械工业出版社,2008.
[2]王成元,夏加宽,杨俊友,等.电机现代控制技术[M].北京：机械工业出版社,2007.
[3]黄声华,吴芳.永磁交流伺服系统国内外发展概况[J].微特电机.2008(5)：52-61.
[4]许峻峰,冯江华,许建平.永磁同步电动机控制策略综述[J].机车电传动,2005,28(3)：7-12.
[5]许大中.交流电机调速理论[M].杭州：浙江大学出版,1991.
[6]高景德,王祥熙衔,李发海.交流电机及其系统的分析[M].北京：清华大学出版礼.1993.
[7]满永奎.通用变频器及其应用.北京：机械工业出版社.1996.
[8]Blaker F. A New Quick—Response and High—Efficiency Control Strategy of an Induction Motor[J]. IEEE Transactions on Industry Application,1971,22(5): 820-827.
[9]Bose B K. Modern Power Electronics and AC Drives[M]. America:Pearson Education,Inc,2002.
[10]张刚.浅谈永磁同步电机伺服系统及其现状[J].现代企业文化.2008(9)：73-74.
[11]Takahashi I, Noguchi T. A New Quick-Response and High Eficiency Control Strategy of an Induction Motor[J]. IEEE Transactions on Industry Application,1988, 22(5):820-827.
[12]Depenbrock M. Direct Self-Control(DSC) of Inverter Fed Induction Machine[C]. Aachen Germany:In Proc. Power Electronics Specialist ConfeFence, 1987,632-641.
[13]Denpenbrock M. Direct Self-Control of Inverter Fed Induction Machine[J]. IEEE Transactions on Power Electronics,1989,3(41):420-429.
[14]Muhammed F R, Zhong L, Haque M E, et al. A direct torque-controlled interior permanent magnet synchronous machine dirve without a speed sensor [J]. IEEE Trans. On Energy Conversion,2003,18(1):17-22.
[15]Le Pioufle. Comparison of speed nonfinear control strategies for the synchronous servomotor[J]. Electric Machine and Power systems,1999.21:151-169.
[16]Remeo Ortega, Alessandro Aslfi, Nikita Barabanov. Nonlinear PI-control of uncertain systems:an alternative to parameter adaptation[J]. System and control letters,2002,47:259-278.
[17]Annaswamy A, Skantze F. Adaptive control of continuous-time systems with convex /concave parameterization[J].Automatica,1998,34(1):33-49.
[18]Ivan YuTyukin, DanilVProkhorov, ValeryATerekhov. Adaptive control with nonconvex parameterization[J]. IEEE Transaction on automatic control,2003, 48(4):554-567.
[19]Raymony B S, Jeffrey H L. Real-time Adaptive Control of the Permanent Magnet Synchronous Motor [J]. IEEE Transactions on Industry Applications,1991,27 (4): 706-714.
[20]Antti Piippo M H, Luomi J. Adaptation of Motor Parameters in Sensorless PMSM Drives[J]. IEEE Transactions on Industry Applications,2009,45(1):203-212.
[21]Zhu G, Kaddouri A, Dessaint L, et al. A nonlinear state observer for the sensorless control of a permanent-magnet AC machine[J]. IEEE Transactions on Industrial Electronics,2001,48(6):1098-1108.
[22]Wai R J. Total sliding-mode controller for PM synchronous servo motor drive using recurrent fuzzy neural network[J]. IEEE Transactions on Industrial Electronics,2001, 48, (5):926-944.
[23]Li S H, Liu Z G. Adaptive speed control for permanent-magnet synchronous motor system with variations of load inertia[J].IEEE Transactions on Industrial Electronics, 2009,56, (8):3050-3059.
[24]Lin Fj, Chiu S L, Shyu K K. Novel Sliding Mode Controller for Synchronous Motor Drive[J]. IEEE Transactions on Aerospace and Electronic Systems,1998,34(2):532-542.
[25]郭可忠,徐若颖.永磁同步电动机的滑模变结构控制[J].中小型电机.1997,24(5)：13-21.
[26]李鸿儒,白湘波,顺树生.基于神经网络的永磁同步电机的鲁棒控制[J].东北大学学报(自然科学版).2001,22(4)：362-365.
[27]郝东丽,郭彤颖,贾凯.基于神经网络的永磁同步电机矢量控制[J].电力电子技术,2004,38(4)：54-61.
[28]赵辉,冯英浚,张志忠,等.神经网络用于永磁同步电机系统波动力矩补偿[J].哈尔滨工业大学学报,2003,35(1)：5-12.
[29]Ohnishi K, Matsui N, hori Y. Estimation,identification,and sensorless control in motion control system[J].Proceedings of the IEEE,1994,82(8):1253-1265.
[30]Chen J L, Liu T H, Chen C L. Design and implementation of a novel high-performance sensorless control system for interior permanent magnet synchronous motors[J]. IET Electric Power Application,2010,4(4):226-240.
[31]秦峰,贺益康,刘毅,等.两种高频信号注入法的无传感器运行研究[J].中国电机工程学报,2005,25(5)：116-121.
[32]Schauder C. Adaptive speed identification for vector control of induction motors without rotational transducers [J]. IEEE Transactions on Industry Applications,1992,28(5):1054-1061.
[33]Chen J J, Chin K P. Minimum copper loss flux-weakening control of surface mounted permanent magnet synchronous motors[J]. IEEE Transactions on Power Electronics 2003,18(4):929-936.
[34]Tursini Marco,Chiricozzi Enzo, Petrella Roberto.Feedforward Flux-Weakening Control of Surface-Mounted Permanent-Magnet Synchronous Motors Accounting for Resistive Voltage Drop. IEEE Transactions on Industrial Electronics,2010,57(1): 440-448.
[35]Zhu Z Q, Chen Y S, Howe D. Online optimal flux-weakening control of permanent-magnet brushless AC drives. IEEE Transactions on Industry Applications,2000,36(6):1661-1668.
[36]王江,李韬,曾启明,等.基于观测器的永磁同步电动机微分代数非线性控制[J].中国电机工程学报,2005,25(2)：87-92.
[37]胡庆波,吕征宇.一种新颖的基于空间矢量PWM的死区补偿方法[J].中国电机 工程学报,2005,25(3)：13-17.
[38]Morel F, Retif J, Lin-Shi X, et al. A Comparative Study of Predictive Current Control Schemes for a Permanent-Magnet Synchronous Machine Drive[J]. IEEE Transactions on Industrial Electronics,2009,56(7):2715-2728.
[39]Mohamed Y A I, El-Saadany E F.A Current Control Scheme With an Adaptive Internal Model for Torque Ripple Minimization and Robust Current Regulation in PMSM Drive Systems[J]. IEEE Transactions on Energy Conversion,2008,23(1): 92-100.
[40]Seok J, Kim K, Lee D. Automatic Mode Switching of P-PI Speed Control for Industry Servo Drives Using Online Spectrum Analysis of Torque Command[J]. IEEE Transactions on Industrial Electronics,2007,54(5):2642-2647.
[41]高扬,杨明,于泳,等.基于扰动观测器的PMSM交流伺服系统低速控制[J].中国机电工程学报,2005,25(22)：125-129.
[42]陈荣,邓智泉,严仰光.基于负载观测器的伺服系统抗扰研究[J].中国电机工程学报,2004,24(8)：103-108.
[43]郑泽东,李永东,肖曦,等.永磁同步电机负载转矩观测器[J].电工技术学报,2010,25(2)：30-36.
[44]Tursini M, Parasiliti F, Zhang D. Real-time gain tuning of PI controllers for high-performance PMSM drives[J]. IEEE Transactions on Industry Applications, 2002,38(4):1018-1026.
[45]史婷娜,张典林,夏长亮,等.基于遗传整定的永磁交流伺服系统模糊免疫PID控制器[J].电工技术学报,2008,23(7)：45-50.
[46]Lin F, Lin C. A permanent-magnet synchronous motor servo drive using self-constructing fuzzy neural network controller [J]. IEEE Transactions on Energy Conversion,2004,19(1):66-72.
[47]齐放,邓智泉,仇志坚,等.基于MRAS内永磁同步电机无速度传感器[J].电工技术学报,2007,22(4)：53-58.
[48]张剑,温旭辉,刘钧,等.一种基于DSP的PMSM转子位置及速度估计新方法[J].中国电机工程学报,2006,26(12)：144-148.
[49]王丽梅,郭庆鼎.基于多重凸极跟踪的永磁同步电动机转子位置估计[J].中国电机工程学报,2007,27(24)：48-52.
[50]万山明,吴芳,黄声华.基于高频电压信号注入的永磁同步电机转子初始位置估计[J].中国电机工程学报,2008,28(33)：82-86.
[51]黄伟忠,宋春华.永磁交流伺服电机国内外市场概况[J].微特电机.2009(1)：59-62.
[52]北京智道顾问有限公司.2009年微电机行业发展预测与市场研究报告[M].智道顾问有限公司,2008.
[53]安川电机公司.安川电机样本[R].安川电机,2008.
[54]三菱电机公司.三菱伺服电机样本[R].三菱电机,2007.
[55]德国百格拉公司.德国百格拉伺服电机样本[R].德国百格拉,2006.
[56]德国BOSCH.德国BOSCH伺服电机样本[R].德国BOSCH,2007.
[57]和时利公司.和时利伺服电机样本[R].和时利公司,2008.
[58]王健.现代交流伺服系统技术和市场发展综述[J].伺服控制,2007,10(1)：16-21
[59]Japan Panasonic.AC Servo Moter Driver MINAS A-series Operating Manual[Z].2005.
[60]杨明,付博,李钊,等.永磁同步电动机矢量控制电压解耦控制研究[J].电气传动,2010,40(5)：24-28.
[61]Krause P C. Analysis of electric machinery [M]. McGraw-Hill,1986.
[62]陈坚.交流电机数学模型及调速系统[M].北京：国防工业出版社,1989.
[63]李崇坚,王祥珩,李发海,等.磁场定向控制交交变频同步电机系统的数学模型[J].清华大学学报(自然科学版),1995,35(4)：1-8.
[64]万山明.TMS320F281xDSP原理及应用实例[M].北京：北京航空航天大学出版社,2007.
[65]程善美,姜向龙,孙文焕,等.空间矢量PWM逆变器的仿真[J].微电机,2002,35(4)：30-33.
[66]熊健,康勇,张凯,等.电压空间矢量调制与常规SPWM的比较研究[J].电力 电子技术,1999(1)：25-28.
[67]吴芳,万山明,黄声华.一种过调制算法及其在永磁同步电动机弱磁控制中的应用[J].电工技术学报,2010,25(1)：58-63.
[68]宋刚,秦月霞,张凯,等.基于普通编码器的高精度测速方法[J].上海交通大学学报,2002,36(8)：1169-1172.
[69]万山明,吴芳,黄声华.同步电机超低速下的转速检测及控制[J].微电机,2007,40(8)：65-67.
[70]李琳,历明,艾华.微型光电编码器在电机角速率辨识中的应用[J].光学精密工程,2010,18(8)：1738-1745.
[71]王庆龙,张崇巍,张兴.交流电机无速度传感器矢量控制系统变结构模型参考自适应转速辨识[J].中国电机工程学报,2007,27(15)：70-74.
[72]王坚,年晓红,桂卫华,等.新型异步电机无速度传感器控制方法[J].中国电机工程学报,2008,28(3)：96-101.
[73]文建平,曹秉刚.无速度传感器的内嵌式永磁同步电机自抗扰控制调速系统[J].中国电机工程学报,2009,29(30)：58-62.
[74]Belanger P R, Dobrovolny P, Helmy A, et al. Estimation of angular velocity and acceleration from shaft-encoder measurements [J]. International Journal of Robotics Research,1998,17(11):1225-1233.
[75]Merry R J E, VandeMJG, Molengraft, et al. Velocity and acceleration estimation for optical incremental encoders[J]. Mechatronics,2010,20(1):20-26.
[76]Kadhim A H, BabuTKM, Kelly D O. Measurement of steady-state and transient load-angle, angular velocity, and acceleration using an optical encoder [J]. IEEE Transactions on Instrumentation and Measurement,1992,41(4):486-489.
[77]孙凯,许镇琳,邹积勇.基于自抗扰控制器的永磁同步电机无位置传感器矢量控制系统[J].中国电机工程学报,2007,27(03)：18-22
[78]刘志刚,李世华.基于永磁同步电机模型辨识与补偿的自抗扰控制器[J].中国电机工程学报,2008,28(24)：118-223.
[79]Ovaska S J. Improving the velocity sensing resolution of pulse encoders by FIR prediction[J]. IEEE Transactions on Instrumentation and Measurement,1991,40(3): 657-658.
[80]Vainio, Renfors M, SaramakiT. Recursive implementation of FIR differentiators with optimum noise attenuation [J]. IEEE Transactions on Instrumentation and Measurement,1997,46(5):1202-1207.
[81]Kavanagh R C, Murphy J M D. The effects of quantization noise and sensor nonideality on digital differentiator-based rate measurement[J]. IEEE Transactions on Instrumentation and Measurement.,1998,47(6):1457-1463.
[82]胡明慧,王永山,邵惠鹤.基于改进的菜文森算法对电机转速特性的研究[J].中国电机工程学报,2007,27(30)：77-81.
[83]Lee S H, Lasky T A, Velinsky S A. Improved velocity estimation for low-speed and transient regimes using low-resolution encoders[J]. IEEE/ASME Transactions on Mechatronics,2004,9(3):553-560.
[84]Su Y X, Zheng C H, Mueller P C, et al. A simple improved velocity estimation for low-speed regions based on position measurements only[J]. IEEE Transactions on Control Systems Technology,2006,14(5):937-942.
[85]Lee S H, Song J B. Acceleration estimator for low-velocity and low-acceleration regions based on encoder position data[J]. IEEE Transactions on Mechatronics, 2001,6 (1):58-64.
[86]周晨,杨华勇,徐兵等.维纳数字滤波技术在轿厢速度反馈闭环控制的液压电梯中的应用[J].机床与液压,2000,28(5)：46-48.
[87]郑泽东,李永东,Maurice Fade,等.基于扩展Kalman滤波器的PMSM高性能控制系统[J].电工技术学报,2010,22(10)：18-24.
[88]张猛,肖曦,李永东.基于扩展卡尔曼滤波器的永磁同步电机转速和磁链观测器[J].中国电机工程学报,2007,27(36)：36-40.
[89]杨青智.机动目标跟踪技术的研究[D].西安：西安电子科技大学,2008.
[90]杨元喜.自适应导航定位[M].北京：测绘出版社,2006：78-80.
[91]Marco U, Francesco P, Zhang Daqing. Real-time gain tuning of PI controllers for high-performance PMSM drives[J]. IEEE Transactions on Industry Applications,2002,38(4):1018-1026.
[92]Choi J W, Lee S C. Antiwindup strategy for PI-Type speed controller[J]. IEEE Transactions on Industrial Electronics,2009,56(6):2039-2046.
[93]Choi J.W., Lee S.C., Kim H.G. Inertia identification algorithm for high-performance speed control of electric motors [J]. IEE Proceedings of Electric Power Applications, 2006,153(3):379-386.
[94]Yu jie,Guo,Lipei Huang. Inertia identification and auto-tuning of induction motor using MRAC [J].IEEE Transactions on Power Electronics,2002,13(4):47-54.
[95]安群涛,孙力,赵克.一种永磁同步电动机参数的自适应在线辨识方法[J].电工技术学报,2008,23(6)：31-36.
[96]Fukashi Andoh.Moment of inertia identification using the time average of the product of torque reference input and motor position [J]. IEEE Transaction on power electronics.2007,22(6):2534-2543.
[97]段海滨.蚁群算法原理及其应用[M].北京：科学技术出版社,2005.
[98]Dorigo M,Maniezzo V,Colorni A. Ant system optimization by a colony of cooperating agents[J].IEEE Transaction on Systems,Man,and Cybernetics-PartB,1996,26(1):29-41
[99]汪镭,吴启迪.蚁群算法在系统辨识中的应用[J]].自动化学报,2003,29(1)：101-109
[100]赵庆杞,黎明,张化光.基于蚁群算法的灵敏负荷调度[J].中国电机工程学报.2006,26(25)：15-21.
[101]刘永钦,沈艳霞,纪志成.改进型最小二乘法在PMSM参数辨识中的应用[J].微特电机,2008,36(11)：8-11.
[102]Samuel J., Underwood, Iqbal Husain. Online Parameter Estimation and Adaptive Control of Permanent-Magnet Synchronous Machines[J]. IEEE Transactions on Industrial Electronics,2010,57(7):2435-2443.
[103]贾正春,许强.智能型交流伺服系统的设计[C].台达电力电子新技术研讨会论文集.2003,76-80.
[104]张猛,肖曦,李永东.基于扩展卡尔曼滤波器的永磁同步电机转速和磁链观测器[J].中国电机工程学报,2007,27(36)：36-40.
[105]Kim N.J., Moon H.S.and Hyun D.S.. Inertia identification for the speed observer of the low speed control of induction machines [J]. IEEE Transactions on industry application,1996,32 (6):1371-1379.
[106]Ding F., Shi Y., Chen T.. Auxiliary Model Based Least Squares Identification Methods for Hammers Tein Output Error Systems[J]. Systems & Control Letters, 2007,56(5):373-380.
[107]Ding F., Chen T.. Performance Bounds of Forgetting Factor Least Squrares Algorithm for Time-varying Systems with Finite Measurement Data[J]. IEEE Transactions on Circuits and Systems,2005,52(3):555-566.
[108]Satyendra Bhama, Harpreet Singh. Single layer Neural Networks for Linear System Identification Using Gradient Descent Technique [J]. IEEE Transactions on Neural Networks,1993,4(5):884-888.
[109]万山明,吴芳,黄声华.全数字化交流伺服系统控制环分析[J].微电机,2009,36(7)：55-58.
[110]邹伯敏.自动控制理论[M].机械工业出版社,2004
[111]孙强,程明,周鹗等.新型双凸极永磁电机调速系统的变参数PI控制[J].中国电机工程学报,2003,23(6)：117-122.
[112]王江,王静,费向阳.永磁同步电动机的非线性PI速度控制[J].中国电机工程学报.2005,25(7)：125-130.
[113]王宏,于泳,徐殿国.永磁同步电动机位置伺服系统[J].中国电机工程学报,2004,24(7)：151-155.
[114]许强,贾正春,李朗如.永磁同步电动机的模型参考自适应速度控制[J].电气传动,1998,40(5)：3-8.
[115]李萍.最小拍无波纹直流电机控制系统仿真研究[J].计算机工程与设计,2009,30(8)：1998-2000.
[116]Wen P, Lu T W. Decoupling control of a twin rotor MIMO system using robust deadbeat control technique[J]. IET Control Theory and Applications, 2008,2(11):999-1007.
[117]Noriaki H, Makoto I, Motohiro K, et al. Deadbeat feedforward compensation with frequency shaping in fast and precise positioning [J].IEEE Transactions on Industrial Electronics,2009,56(10):3790-3797.
[118]Salgado M E, Oyarzun D A, Silva E I. H2 optimal ripple-free deadbeat controller design[J]. Automatica,2007,43(11):1961-1967.
[119]万山明,吴芳,黄声华.永磁同步电机的数字化电流控制环分析[J].华中科技大学学报(自然科学版),2007,35(5)：48-51.
[120]曹承志.微型计算机控制新技术[M].北京：机械工业出版社,2004.
[121]吴乃优,桦林,钢贺,等.大惯量调速系统机械谐振现象研究及其在机电一体化产品设计中的应用[J].天津师大学报(自然科学版),1993(1)：28-32.
[122]孙炳达.克服电气传动机械谐振的一种新的控制结构[J].电气传动,1998(1)：45-48.
[123]Zheng J, Feng Y, Yu X. Mechanical Resonance Suppressing Method for PMSM System based on High-order Sliding Modes[C]. The 33rd Annual Conference of the IEEE Industrial Electronics Society.Taipei,Taiwan:2007.704-709.
[124]Wang H, Lee D, Lee Z, et al. Vibration Rejection Scheme of Servo Drive System with Adaptive Notch Filter[C].37th IEEE Power Electronics Specialists Conference. 2006,1-6.
[125]Ellis G, Gao Z. Cures for low-frequency mechanical resonance in industrial servo systems[C]. Industry Applications Conference. Thirty-Sixth IAS Annual Meeting.2001,252-258.
[126]Ellis G, Lorenz R D. Resonant load control methods for industrial servo drives[C]. Industry Applications Conference.2000,1438-1445.
[127]Fu S C, Cheng S. Analysis and Suppression of Torsional Vibrations for the Permanent Magnet Synchronous Motor-Load System [C]. IEEE International Conference on Systems, Man, and Cybernetics.San Antonio,TX,USA,2009,3359-3364.
[128]胡清,童怀.伺服系统机械谐振问题的研究[J].电气传动,2000(3)：7-11.
[129]陈怀琛.数字信号处理教程-MATLAB释义与实现[M].北京：电子工业出版社,2004.
[2]王成元,夏加宽,杨俊友,等.电机现代控制技术[M].北京：机械工业出版社,2007.
[3]黄声华,吴芳.永磁交流伺服系统国内外发展概况[J].微特电机.2008(5)：52-61.
[4]许峻峰,冯江华,许建平.永磁同步电动机控制策略综述[J].机车电传动,2005,28(3)：7-12.
[5]许大中.交流电机调速理论[M].杭州：浙江大学出版,1991.
[6]高景德,王祥熙衔,李发海.交流电机及其系统的分析[M].北京：清华大学出版礼.1993.
[7]满永奎.通用变频器及其应用.北京：机械工业出版社.1996.
[8]Blaker F. A New Quick—Response and High—Efficiency Control Strategy of an Induction Motor[J]. IEEE Transactions on Industry Application,1971,22(5): 820-827.
[9]Bose B K. Modern Power Electronics and AC Drives[M]. America:Pearson Education,Inc,2002.
[10]张刚.浅谈永磁同步电机伺服系统及其现状[J].现代企业文化.2008(9)：73-74.
[11]Takahashi I, Noguchi T. A New Quick-Response and High Eficiency Control Strategy of an Induction Motor[J]. IEEE Transactions on Industry Application,1988, 22(5):820-827.
[12]Depenbrock M. Direct Self-Control(DSC) of Inverter Fed Induction Machine[C]. Aachen Germany:In Proc. Power Electronics Specialist ConfeFence, 1987,632-641.
[13]Denpenbrock M. Direct Self-Control of Inverter Fed Induction Machine[J]. IEEE Transactions on Power Electronics,1989,3(41):420-429.
[14]Muhammed F R, Zhong L, Haque M E, et al. A direct torque-controlled interior permanent magnet synchronous machine dirve without a speed sensor [J]. IEEE Trans. On Energy Conversion,2003,18(1):17-22.
[15]Le Pioufle. Comparison of speed nonfinear control strategies for the synchronous servomotor[J]. Electric Machine and Power systems,1999.21:151-169.
[16]Remeo Ortega, Alessandro Aslfi, Nikita Barabanov. Nonlinear PI-control of uncertain systems:an alternative to parameter adaptation[J]. System and control letters,2002,47:259-278.
[17]Annaswamy A, Skantze F. Adaptive control of continuous-time systems with convex /concave parameterization[J].Automatica,1998,34(1):33-49.
[18]Ivan YuTyukin, DanilVProkhorov, ValeryATerekhov. Adaptive control with nonconvex parameterization[J]. IEEE Transaction on automatic control,2003, 48(4):554-567.
[19]Raymony B S, Jeffrey H L. Real-time Adaptive Control of the Permanent Magnet Synchronous Motor [J]. IEEE Transactions on Industry Applications,1991,27 (4): 706-714.
[20]Antti Piippo M H, Luomi J. Adaptation of Motor Parameters in Sensorless PMSM Drives[J]. IEEE Transactions on Industry Applications,2009,45(1):203-212.
[21]Zhu G, Kaddouri A, Dessaint L, et al. A nonlinear state observer for the sensorless control of a permanent-magnet AC machine[J]. IEEE Transactions on Industrial Electronics,2001,48(6):1098-1108.
[22]Wai R J. Total sliding-mode controller for PM synchronous servo motor drive using recurrent fuzzy neural network[J]. IEEE Transactions on Industrial Electronics,2001, 48, (5):926-944.
[23]Li S H, Liu Z G. Adaptive speed control for permanent-magnet synchronous motor system with variations of load inertia[J].IEEE Transactions on Industrial Electronics, 2009,56, (8):3050-3059.
[24]Lin Fj, Chiu S L, Shyu K K. Novel Sliding Mode Controller for Synchronous Motor Drive[J]. IEEE Transactions on Aerospace and Electronic Systems,1998,34(2):532-542.
[25]郭可忠,徐若颖.永磁同步电动机的滑模变结构控制[J].中小型电机.1997,24(5)：13-21.
[26]李鸿儒,白湘波,顺树生.基于神经网络的永磁同步电机的鲁棒控制[J].东北大学学报(自然科学版).2001,22(4)：362-365.
[27]郝东丽,郭彤颖,贾凯.基于神经网络的永磁同步电机矢量控制[J].电力电子技术,2004,38(4)：54-61.
[28]赵辉,冯英浚,张志忠,等.神经网络用于永磁同步电机系统波动力矩补偿[J].哈尔滨工业大学学报,2003,35(1)：5-12.
[29]Ohnishi K, Matsui N, hori Y. Estimation,identification,and sensorless control in motion control system[J].Proceedings of the IEEE,1994,82(8):1253-1265.
[30]Chen J L, Liu T H, Chen C L. Design and implementation of a novel high-performance sensorless control system for interior permanent magnet synchronous motors[J]. IET Electric Power Application,2010,4(4):226-240.
[31]秦峰,贺益康,刘毅,等.两种高频信号注入法的无传感器运行研究[J].中国电机工程学报,2005,25(5)：116-121.
[32]Schauder C. Adaptive speed identification for vector control of induction motors without rotational transducers [J]. IEEE Transactions on Industry Applications,1992,28(5):1054-1061.
[33]Chen J J, Chin K P. Minimum copper loss flux-weakening control of surface mounted permanent magnet synchronous motors[J]. IEEE Transactions on Power Electronics 2003,18(4):929-936.
[34]Tursini Marco,Chiricozzi Enzo, Petrella Roberto.Feedforward Flux-Weakening Control of Surface-Mounted Permanent-Magnet Synchronous Motors Accounting for Resistive Voltage Drop. IEEE Transactions on Industrial Electronics,2010,57(1): 440-448.
[35]Zhu Z Q, Chen Y S, Howe D. Online optimal flux-weakening control of permanent-magnet brushless AC drives. IEEE Transactions on Industry Applications,2000,36(6):1661-1668.
[36]王江,李韬,曾启明,等.基于观测器的永磁同步电动机微分代数非线性控制[J].中国电机工程学报,2005,25(2)：87-92.
[37]胡庆波,吕征宇.一种新颖的基于空间矢量PWM的死区补偿方法[J].中国电机 工程学报,2005,25(3)：13-17.
[38]Morel F, Retif J, Lin-Shi X, et al. A Comparative Study of Predictive Current Control Schemes for a Permanent-Magnet Synchronous Machine Drive[J]. IEEE Transactions on Industrial Electronics,2009,56(7):2715-2728.
[39]Mohamed Y A I, El-Saadany E F.A Current Control Scheme With an Adaptive Internal Model for Torque Ripple Minimization and Robust Current Regulation in PMSM Drive Systems[J]. IEEE Transactions on Energy Conversion,2008,23(1): 92-100.
[40]Seok J, Kim K, Lee D. Automatic Mode Switching of P-PI Speed Control for Industry Servo Drives Using Online Spectrum Analysis of Torque Command[J]. IEEE Transactions on Industrial Electronics,2007,54(5):2642-2647.
[41]高扬,杨明,于泳,等.基于扰动观测器的PMSM交流伺服系统低速控制[J].中国机电工程学报,2005,25(22)：125-129.
[42]陈荣,邓智泉,严仰光.基于负载观测器的伺服系统抗扰研究[J].中国电机工程学报,2004,24(8)：103-108.
[43]郑泽东,李永东,肖曦,等.永磁同步电机负载转矩观测器[J].电工技术学报,2010,25(2)：30-36.
[44]Tursini M, Parasiliti F, Zhang D. Real-time gain tuning of PI controllers for high-performance PMSM drives[J]. IEEE Transactions on Industry Applications, 2002,38(4):1018-1026.
[45]史婷娜,张典林,夏长亮,等.基于遗传整定的永磁交流伺服系统模糊免疫PID控制器[J].电工技术学报,2008,23(7)：45-50.
[46]Lin F, Lin C. A permanent-magnet synchronous motor servo drive using self-constructing fuzzy neural network controller [J]. IEEE Transactions on Energy Conversion,2004,19(1):66-72.
[47]齐放,邓智泉,仇志坚,等.基于MRAS内永磁同步电机无速度传感器[J].电工技术学报,2007,22(4)：53-58.
[48]张剑,温旭辉,刘钧,等.一种基于DSP的PMSM转子位置及速度估计新方法[J].中国电机工程学报,2006,26(12)：144-148.
[49]王丽梅,郭庆鼎.基于多重凸极跟踪的永磁同步电动机转子位置估计[J].中国电机工程学报,2007,27(24)：48-52.
[50]万山明,吴芳,黄声华.基于高频电压信号注入的永磁同步电机转子初始位置估计[J].中国电机工程学报,2008,28(33)：82-86.
[51]黄伟忠,宋春华.永磁交流伺服电机国内外市场概况[J].微特电机.2009(1)：59-62.
[52]北京智道顾问有限公司.2009年微电机行业发展预测与市场研究报告[M].智道顾问有限公司,2008.
[53]安川电机公司.安川电机样本[R].安川电机,2008.
[54]三菱电机公司.三菱伺服电机样本[R].三菱电机,2007.
[55]德国百格拉公司.德国百格拉伺服电机样本[R].德国百格拉,2006.
[56]德国BOSCH.德国BOSCH伺服电机样本[R].德国BOSCH,2007.
[57]和时利公司.和时利伺服电机样本[R].和时利公司,2008.
[58]王健.现代交流伺服系统技术和市场发展综述[J].伺服控制,2007,10(1)：16-21
[59]Japan Panasonic.AC Servo Moter Driver MINAS A-series Operating Manual[Z].2005.
[60]杨明,付博,李钊,等.永磁同步电动机矢量控制电压解耦控制研究[J].电气传动,2010,40(5)：24-28.
[61]Krause P C. Analysis of electric machinery [M]. McGraw-Hill,1986.
[62]陈坚.交流电机数学模型及调速系统[M].北京：国防工业出版社,1989.
[63]李崇坚,王祥珩,李发海,等.磁场定向控制交交变频同步电机系统的数学模型[J].清华大学学报(自然科学版),1995,35(4)：1-8.
[64]万山明.TMS320F281xDSP原理及应用实例[M].北京：北京航空航天大学出版社,2007.
[65]程善美,姜向龙,孙文焕,等.空间矢量PWM逆变器的仿真[J].微电机,2002,35(4)：30-33.
[66]熊健,康勇,张凯,等.电压空间矢量调制与常规SPWM的比较研究[J].电力 电子技术,1999(1)：25-28.
[67]吴芳,万山明,黄声华.一种过调制算法及其在永磁同步电动机弱磁控制中的应用[J].电工技术学报,2010,25(1)：58-63.
[68]宋刚,秦月霞,张凯,等.基于普通编码器的高精度测速方法[J].上海交通大学学报,2002,36(8)：1169-1172.
[69]万山明,吴芳,黄声华.同步电机超低速下的转速检测及控制[J].微电机,2007,40(8)：65-67.
[70]李琳,历明,艾华.微型光电编码器在电机角速率辨识中的应用[J].光学精密工程,2010,18(8)：1738-1745.
[71]王庆龙,张崇巍,张兴.交流电机无速度传感器矢量控制系统变结构模型参考自适应转速辨识[J].中国电机工程学报,2007,27(15)：70-74.
[72]王坚,年晓红,桂卫华,等.新型异步电机无速度传感器控制方法[J].中国电机工程学报,2008,28(3)：96-101.
[73]文建平,曹秉刚.无速度传感器的内嵌式永磁同步电机自抗扰控制调速系统[J].中国电机工程学报,2009,29(30)：58-62.
[74]Belanger P R, Dobrovolny P, Helmy A, et al. Estimation of angular velocity and acceleration from shaft-encoder measurements [J]. International Journal of Robotics Research,1998,17(11):1225-1233.
[75]Merry R J E, VandeMJG, Molengraft, et al. Velocity and acceleration estimation for optical incremental encoders[J]. Mechatronics,2010,20(1):20-26.
[76]Kadhim A H, BabuTKM, Kelly D O. Measurement of steady-state and transient load-angle, angular velocity, and acceleration using an optical encoder [J]. IEEE Transactions on Instrumentation and Measurement,1992,41(4):486-489.
[77]孙凯,许镇琳,邹积勇.基于自抗扰控制器的永磁同步电机无位置传感器矢量控制系统[J].中国电机工程学报,2007,27(03)：18-22
[78]刘志刚,李世华.基于永磁同步电机模型辨识与补偿的自抗扰控制器[J].中国电机工程学报,2008,28(24)：118-223.
[79]Ovaska S J. Improving the velocity sensing resolution of pulse encoders by FIR prediction[J]. IEEE Transactions on Instrumentation and Measurement,1991,40(3): 657-658.
[80]Vainio, Renfors M, SaramakiT. Recursive implementation of FIR differentiators with optimum noise attenuation [J]. IEEE Transactions on Instrumentation and Measurement,1997,46(5):1202-1207.
[81]Kavanagh R C, Murphy J M D. The effects of quantization noise and sensor nonideality on digital differentiator-based rate measurement[J]. IEEE Transactions on Instrumentation and Measurement.,1998,47(6):1457-1463.
[82]胡明慧,王永山,邵惠鹤.基于改进的菜文森算法对电机转速特性的研究[J].中国电机工程学报,2007,27(30)：77-81.
[83]Lee S H, Lasky T A, Velinsky S A. Improved velocity estimation for low-speed and transient regimes using low-resolution encoders[J]. IEEE/ASME Transactions on Mechatronics,2004,9(3):553-560.
[84]Su Y X, Zheng C H, Mueller P C, et al. A simple improved velocity estimation for low-speed regions based on position measurements only[J]. IEEE Transactions on Control Systems Technology,2006,14(5):937-942.
[85]Lee S H, Song J B. Acceleration estimator for low-velocity and low-acceleration regions based on encoder position data[J]. IEEE Transactions on Mechatronics, 2001,6 (1):58-64.
[86]周晨,杨华勇,徐兵等.维纳数字滤波技术在轿厢速度反馈闭环控制的液压电梯中的应用[J].机床与液压,2000,28(5)：46-48.
[87]郑泽东,李永东,Maurice Fade,等.基于扩展Kalman滤波器的PMSM高性能控制系统[J].电工技术学报,2010,22(10)：18-24.
[88]张猛,肖曦,李永东.基于扩展卡尔曼滤波器的永磁同步电机转速和磁链观测器[J].中国电机工程学报,2007,27(36)：36-40.
[89]杨青智.机动目标跟踪技术的研究[D].西安：西安电子科技大学,2008.
[90]杨元喜.自适应导航定位[M].北京：测绘出版社,2006：78-80.
[91]Marco U, Francesco P, Zhang Daqing. Real-time gain tuning of PI controllers for high-performance PMSM drives[J]. IEEE Transactions on Industry Applications,2002,38(4):1018-1026.
[92]Choi J W, Lee S C. Antiwindup strategy for PI-Type speed controller[J]. IEEE Transactions on Industrial Electronics,2009,56(6):2039-2046.
[93]Choi J.W., Lee S.C., Kim H.G. Inertia identification algorithm for high-performance speed control of electric motors [J]. IEE Proceedings of Electric Power Applications, 2006,153(3):379-386.
[94]Yu jie,Guo,Lipei Huang. Inertia identification and auto-tuning of induction motor using MRAC [J].IEEE Transactions on Power Electronics,2002,13(4):47-54.
[95]安群涛,孙力,赵克.一种永磁同步电动机参数的自适应在线辨识方法[J].电工技术学报,2008,23(6)：31-36.
[96]Fukashi Andoh.Moment of inertia identification using the time average of the product of torque reference input and motor position [J]. IEEE Transaction on power electronics.2007,22(6):2534-2543.
[97]段海滨.蚁群算法原理及其应用[M].北京：科学技术出版社,2005.
[98]Dorigo M,Maniezzo V,Colorni A. Ant system optimization by a colony of cooperating agents[J].IEEE Transaction on Systems,Man,and Cybernetics-PartB,1996,26(1):29-41
[99]汪镭,吴启迪.蚁群算法在系统辨识中的应用[J]].自动化学报,2003,29(1)：101-109
[100]赵庆杞,黎明,张化光.基于蚁群算法的灵敏负荷调度[J].中国电机工程学报.2006,26(25)：15-21.
[101]刘永钦,沈艳霞,纪志成.改进型最小二乘法在PMSM参数辨识中的应用[J].微特电机,2008,36(11)：8-11.
[102]Samuel J., Underwood, Iqbal Husain. Online Parameter Estimation and Adaptive Control of Permanent-Magnet Synchronous Machines[J]. IEEE Transactions on Industrial Electronics,2010,57(7):2435-2443.
[103]贾正春,许强.智能型交流伺服系统的设计[C].台达电力电子新技术研讨会论文集.2003,76-80.
[104]张猛,肖曦,李永东.基于扩展卡尔曼滤波器的永磁同步电机转速和磁链观测器[J].中国电机工程学报,2007,27(36)：36-40.
[105]Kim N.J., Moon H.S.and Hyun D.S.. Inertia identification for the speed observer of the low speed control of induction machines [J]. IEEE Transactions on industry application,1996,32 (6):1371-1379.
[106]Ding F., Shi Y., Chen T.. Auxiliary Model Based Least Squares Identification Methods for Hammers Tein Output Error Systems[J]. Systems & Control Letters, 2007,56(5):373-380.
[107]Ding F., Chen T.. Performance Bounds of Forgetting Factor Least Squrares Algorithm for Time-varying Systems with Finite Measurement Data[J]. IEEE Transactions on Circuits and Systems,2005,52(3):555-566.
[108]Satyendra Bhama, Harpreet Singh. Single layer Neural Networks for Linear System Identification Using Gradient Descent Technique [J]. IEEE Transactions on Neural Networks,1993,4(5):884-888.
[109]万山明,吴芳,黄声华.全数字化交流伺服系统控制环分析[J].微电机,2009,36(7)：55-58.
[110]邹伯敏.自动控制理论[M].机械工业出版社,2004
[111]孙强,程明,周鹗等.新型双凸极永磁电机调速系统的变参数PI控制[J].中国电机工程学报,2003,23(6)：117-122.
[112]王江,王静,费向阳.永磁同步电动机的非线性PI速度控制[J].中国电机工程学报.2005,25(7)：125-130.
[113]王宏,于泳,徐殿国.永磁同步电动机位置伺服系统[J].中国电机工程学报,2004,24(7)：151-155.
[114]许强,贾正春,李朗如.永磁同步电动机的模型参考自适应速度控制[J].电气传动,1998,40(5)：3-8.
[115]李萍.最小拍无波纹直流电机控制系统仿真研究[J].计算机工程与设计,2009,30(8)：1998-2000.
[116]Wen P, Lu T W. Decoupling control of a twin rotor MIMO system using robust deadbeat control technique[J]. IET Control Theory and Applications, 2008,2(11):999-1007.
[117]Noriaki H, Makoto I, Motohiro K, et al. Deadbeat feedforward compensation with frequency shaping in fast and precise positioning [J].IEEE Transactions on Industrial Electronics,2009,56(10):3790-3797.
[118]Salgado M E, Oyarzun D A, Silva E I. H2 optimal ripple-free deadbeat controller design[J]. Automatica,2007,43(11):1961-1967.
[119]万山明,吴芳,黄声华.永磁同步电机的数字化电流控制环分析[J].华中科技大学学报(自然科学版),2007,35(5)：48-51.
[120]曹承志.微型计算机控制新技术[M].北京：机械工业出版社,2004.
[121]吴乃优,桦林,钢贺,等.大惯量调速系统机械谐振现象研究及其在机电一体化产品设计中的应用[J].天津师大学报(自然科学版),1993(1)：28-32.
[122]孙炳达.克服电气传动机械谐振的一种新的控制结构[J].电气传动,1998(1)：45-48.
[123]Zheng J, Feng Y, Yu X. Mechanical Resonance Suppressing Method for PMSM System based on High-order Sliding Modes[C]. The 33rd Annual Conference of the IEEE Industrial Electronics Society.Taipei,Taiwan:2007.704-709.
[124]Wang H, Lee D, Lee Z, et al. Vibration Rejection Scheme of Servo Drive System with Adaptive Notch Filter[C].37th IEEE Power Electronics Specialists Conference. 2006,1-6.
[125]Ellis G, Gao Z. Cures for low-frequency mechanical resonance in industrial servo systems[C]. Industry Applications Conference. Thirty-Sixth IAS Annual Meeting.2001,252-258.
[126]Ellis G, Lorenz R D. Resonant load control methods for industrial servo drives[C]. Industry Applications Conference.2000,1438-1445.
[127]Fu S C, Cheng S. Analysis and Suppression of Torsional Vibrations for the Permanent Magnet Synchronous Motor-Load System [C]. IEEE International Conference on Systems, Man, and Cybernetics.San Antonio,TX,USA,2009,3359-3364.
[128]胡清,童怀.伺服系统机械谐振问题的研究[J].电气传动,2000(3)：7-11.
[129]陈怀琛.数字信号处理教程-MATLAB释义与实现[M].北京：电子工业出版社,2004.