定子磁场定向无速度传感器系统研究与开发
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摘要
本文以感应电机基于定子磁场定向的无速度传感器控制为主要研究内容,针对其中的几个关键问题进行了深入的理论分析和研究,并且构建了DSP(TMS320LF2407A)+CPLD框架的硬件控制平台,在此平台上进行了感应电机按定子磁场定向的无速度传感器矢量控制的调速实验,从实验结果看系统具有较好的调速性能,较宽的调速范围。
     磁链估算是无速度传感器系统的核心问题。定子磁链估算相对于转子磁链估算需要的电机参数少,因此,定子磁场定向的无速度传感器系统参数鲁棒性强。本文详细阐述了定子磁场定向技术的出发点和原理,深入讨论了磁链和转矩的解耦方法,建立了感应电机按定子磁场定向的无速度传感器系统的控制结构,并理论分析了电感参数对不同参考系下无速度传感器系统的影响。
     定子电流和电压对定子磁链的估算有着直接影响。本文详细论述了非线性形态滤波器的原理,并将其引入电流信号的滤波,实验结果表明非线性形态滤波器在有效消除电流信号中正负脉冲干扰的同时很好地保留原有信号的特性,取得良好的滤波效果。本文深入分析了死区效应的产生机理、死区对电压基波分量和谐波分量的影响及其对电流波形的影响,提出了一种基于检测功率管实际导通时间的死区补偿和电机电压直接检测方法,利用检测的死区补偿时间进行死区补偿可以有效地提高波形质量,抑制谐波,同时检测到的电机相电压也具有较高的精度。
     在定子磁链观测方面,纯积分器很容易导致输出信号饱和与偏移,一阶低通滤波器可以在一定程度上抑制饱和与偏移,但不可避免地引入了幅值和相位误差。本文深入研究了带反馈补偿积分器的工作原理、特性及其相关参数的选取原则,指出阈值固定的双积分器可以有效抑制饱和与直流偏移,并且在低频饱和状态下可以完全补偿幅值和相位误差。将阈值固定的双积分器应用于实际系统取得良好的定子磁链观测效果。
     在仿真条件逼近实际工况的仿真环境下进行系统计算机仿真可以为研究工作提供具有很强的实际指导意义。本文在具有半物理仿真特性的SaberDesigner软件下,建立了感应电动机基于磁场定向的无速度传感器调速系统仿真平台,在此平台上对按转子磁场定向和定子磁场的无速度传感器系统进行了深入研究和对比,并且通过仿真实验研究了电机参数对上述两种磁场定向无速度传感器系统的影响。
     理论分析和仿真实验都表明无速度传感器系统严重依赖于电机参数的准确性。本文在借鉴其他学者研究成果的基础上,提出了一种改进的感应电机参数的离线检测方法。该方法结合SVPWM调制方式,并引入了电流调节器,加快了参数辨识过程,增强了系统的安全性,利用离散快速傅立叶变换(DFFT)计算电流电压的有效值和功率因数,增强了系统的抗干扰能力。上述方法充分利用现有的软、硬件条件,完全由系统自动完成,无需人工连线,非常适合于无速度传感器系统,实验结果具有良好的一致性和较高的精度。
     感应电机参数会随运行条件和环境的改变而变化,按定子磁场定向的无速度传感器系统中,定子磁链的估算和定子电阻密切相关。本文提出了一种定子电阻闭环在线估计方法。该方法原理简单、实现方便,仿真结果表明该方法可以很好地跟踪定子电阻的变化,改善系统的性能。采用动态转速估算法,在负载情况下,转子参数和电感参数会影响转差频率的估算。本文将PI自适应转速估算方法引入定子磁场定向的无速度传感器系统,避免了系统在负载情况下,估算转速受转子参数和电感参数影响的问题。从仿真结果看,采用这种估算策略的定子磁场定向无速度传感器系统具有较强的参数鲁棒性。
This dissertation focused on the speed sensorless vector control of induction motor (IM) based on stator flux orientation (SFO). The profound theoretical analysis and study have been made against some critical questions. In this dissertation, the hardware platform with the structure of DSP(TMS320LF2407A)+CPLD has been constructed, and the speed sensorless AC variable speed drive experiments of IM based on stator flux orientation have been performed. The preferable variable speed performance and wider speed range of the system have been proved by experiments.
     The flux estimation is the most important question in speed sensorless control. Much less parameters in stator flux estimation are required than in rotor flux estimation. So the speed sensorless vector control of IM based on SFO is more robustness to parameters than it based on rotor flux orientation (RFO). In this dissertation, the start point and principle of the SFO have been represented in detail, the decoupling methods between flux and torque have been profound discussed, the control structure of the speed sensorless vector control based on SFO has been constructed, and the influences on the system performance by the inductances are also analyzed theoretically.
     The stator flux estimation is effected directly by stator current and voltage. In this dissertation, the theory of nonlinear morphological filter (NML) has been represented, and the NML is introduced into current filtering. It can be seen that the positive or negative plus disturbance is effectively eliminated in current signal and the primary characteristic of current signal is well preserved from experiment results. The production principle of dead-time, the effect of dead-time on fundamental voltage, harmonic voltage and current wave are discussed. A new method of dead-time compensation and phase-voltage measurement based on detecting the actual turn-on time of power tubes is presented in this dissertation. The harmonic is inhibited and the quality of wave is improved by using detected dead-time to compensation. At the same time, the measurement phase-voltage is high precision.
     In stator flux estimation, the saturation and DC drift will be easily produced by the pure integrator. The previous questions can be silenced by the one-order low pass filter (LPF), but the errors in magnitude and phase angle will be introduced inevitably. In this dissertation, the profound research on the theory, characteristic of the integrator with feedback compensation and the principle of parameter selection has been made. The limiting level fixed dual integrator can silence the saturation and DC drift questions, and can compensate completely the errors in magnitude and phase angle under the low frequency and saturation condition. The well stator flux observation result has been achieved by applying the limiting level fixed dual integrator to the stator flux observation.
     The computer simulation under the environment which approaches the actual work condition can supply the powerful guidance for research work. In this dissertation, the speed sensorless variable speed drive based on FO simulation platform of IM has been constructed on SaberDesigner which is a semi-physical simulation software. On the platform, the profound investigation and comparison between the speed sensorless system based on RFO and SFO has been performed, and the influences of IM parameter on the previous speed sensorless system has also been investigated.
     The parameter dependence of speed sensorless system can be indicated by means of theoretical analysis and simulation study. In this dissertation, based on the other scholars’research production, a modified off-line identification method of IM parameters has been presented. In this method, the SVPWM has been used. The identification procedure has been accelerated and the safety of system has been enhanced by applying the current regulator. The system anti-interference ability has been improved by utilizing the discrete fast fourier transform (DFFT) to calculate the effective value of voltage, current and the power factor. The existing conditions are utilized, the identification can be completed automatically, and no manual connection of electric wires action is required in the proposed method. This method is suitable to the speed sensorless scheme. The high uniformity and precision are presented from the experiment results.
     The parameters of IM will vary with the change of operating condition. The stator flux estimation nearly correlates with stator resistance in the speed sensorless system based on SFO. In this dissertation, a close loop on-line estimating method of stator resistance is presented. This method is easily realized and its theory is simple. The simulation results show that the stator resistance variation can be well traced and the system performance is improved by using this method. The slip frequency estimation will be effected by the rotor parameters and inductances when the dynamic speed estimation has been employed. The PI adaptive speed estimation method is introduced into the speed sensorless system based on SFO in this dissertation. So the influences of rotor parameters and inductances on speed estimation under the load condition have been avoided. It is showed that the speed sensorless system based on SFO used the previous speed estimation method is more robust to parameters from simulation results.
引文
[1] Abbondanti, Brennen M. B. Variable speed induction motor drives use electronic slip calculator based on motor voltages and currents. IEEE Transactions on Industry Applications, 1975IA-11(5): 483~488
    [2] Ohtani T., Takada N., Tanaka K. Vector control of induction motor without shaft encoder. IEEE Transactions on Industry Applications, 1992, 28(1): 157~164
    [3] Ilas C., Bettini A., Ferraris L., et al. Comparison of different schemes without shaft sensors for field oriented control drives. in: IECON’94. Sensorless control of AC motor drives, 1994. 30~39
    [4] Ohyama K., Asher G. M., Summer M. Comparative experimental assessment for high-performance sensorless induction motor drives. in: Proceedings of the IEEE International Symposium on Industrial Electronics, 1999. 386~391
    [5] Holtz J. Sensorless control of induction motor drives. Proceedings of the IEEE, 2002, 90(8): 1359~1394
    [6] Joetten R., Maeder G. Control method for good dynamic performance induction motor drives based on current and voltage as measured quantities. IEEE Transactions on Industry Applications, 1983, 10(6): 436~442
    [7] 李永东. 交流电机数字控制系统. 北京:机械工业出版社,2002. 241~243
    [8] Kanmachi T., Takahashi I. Sensor-less speed control of an induction motor with no influence of secondary resistance variation. in: Conference record of the 1993 IEEE, 1993. 408~413
    [9] Hu J., Wu B. New integration algorithms for estimating motor flux over a wide speed range. IEEE Transactions on Power Electronics, 1998, 13(5): 969~977
    [10] Hurst D. K., Habetler T. G., Griva G., et al. Zero-speed tacholess IM torque control: simply a matter of stator voltage integration. IEEE Transactions on Industry Applications, 1998, 34(4): 790~795
    [11] Cirrincione M., Pucci M., Cirrincione G., et al. A new adaptive integration methodology for estimating flux in induction machine drives. IEEE Transactions on Industry Applications, 2004, 19(1): 25~34
    [12] Jiang J., Holtz J. Speed sensorless AC drive for high dynamic performance and steady state accuracy. in: Proceedings of the 1995 IEEE IECON 21st International Conference, 1995. 1029~1034
    [13] Lin S. Y., Wu H., Zhou Y. Y. Sensorless control of induction motors with on-line rotor time constant adaptive. IEEE Transactions on Industry Applications, 1998, 10(3): 1593~1598
    [14] Akatsu K., Kawamura A. Sensorless very low-speed and zero-speed estimations with online rotor resistance estimation of induction motor without signal injection. IEEE Transactions on Industry Applications, 1998, 36(3): 764~771
    [15] Hamajima T., Hasegawa M., Doki S., et al. Sensorless vector control of induction motor with stator resistance identification based on augmented error. in: PCC2002. Proceedings of the IEEE, 2002. 504~509
    [16] Yu X., Dunnigan M. W., Williams B. W. Phase voltage estimation of a PWM VSI and its application to vector-controlled induction machine parameter estimation. IEEE Transactions on Industry Applications, 2000, 47(5): 1181~1185
    [17] Kubota H., Matsuse K. The improvement of performance at low speed by offset compensation of stator voltage in sensorless vector controlled induction machines. in: Industry Applications Conference, 1996. Conference Record of the 1996 IEEE, 1996. 257~261
    [18] Edelbaher G., Urlep E., Curkovic M., et al. Low speed performance improvement in sensorless drive using measured stator voltages of PWM voltage source inverter. in: Industrial Technology, 2003. IEEE International Conference, 2003. 542~547
    [19] Holtz J., Quan J. T. Dift- and parameter-compensated flux estimator for persistent zero-stator-frequency operation of sensorless-controlled induction motors. IEEE Transactions on Industry Applications, 2003, 39(4): 1052~1060
    [20] Chung D. W., Sul S. K. Analysis and compensation of current measurement error in vector-controlled AC motor drives. IEEE Transactions on Industry Applications, 2003, 39(4): 1052~1060
    [21] Schauder C. Adaptive speed identification for vector control of induction motors without rotational transducers. IEEE Transactions on Industry Applications, 1992, 28(5): 1054~1061
    [22] Peng F. Z., Fukao T. Robust speed identification for speed sensorless vector control of induction motors. IEEE Transactions on Industry Applications, 1994, 30(5): 1234~1240
    [23] Tsuji M., Chen S., Izumi K., et al. A sensorless vector control system for induction motors using q-axis flux with stator resistance identification. IEEE Transactions on Industry Applications, 2001, 48(1): 185~194
    [24] 王文森,李永东,王光辉等. 基于 PI 自适应法的无速度传感器异步电动机矢量控制系统. 电工技术学报,2002,17(1):1~6
    [25] 陈硕,吴臻鹏,阮成功. 基于变参数 PI 自适应法的无速度传感器矢量控制系统速度推算方法. 福州大学学报(自然科学版),2003,31(1):65~68
    [26] Jemli M., Boussak M., Gossa M., et al. Rotor time constant identification in vector controlled induction motor applied flux model reference adaptive system (MRAS). in: Electrotechnical Conference, 1994. Proceedings., 7th Mediterranean, 1994. 797~800
    [27] Lazhar B. B., Susumu T. Speed control of induction motor without rotational transducers. in: Industry Applications Conference, 1998. 625~632
    [28] Han W. Y., Kim S. M., Kim S. J., et al. Sensorless vector control of induction motor using improved self-tuning fuzzy PID controller. in: SICE Annual Conference. 2003. 3112~3117
    [29] Cirrincione M., Pucci M. An MRAS-based sensorless high-performance induction motor drive with a predictive adaptive model. IEEE Transactions on Industry Applications, 2005, 52(2): 532~551
    [30] Kubota H., Matsuse K. New adaptive flux observer of induction motor for wide speed range motor drives. in: Conf. Rec. IEEE IECON'90 1990. 921~92
    [31] Kubota H., Matsuse K., Nakano T. DSP-based speed adaptive flux observer of induction motor". IEEE Transactions on Industry Applications. 1993, 29(2): 344~348
    [32] Kubota H., Matsuse K. Speed sensorless field-oriented control of induction motor with rotor resistance adaptation. IEEE Transactions on Industry Applications. 1994, 30(5): 1219~1224
    [33] Marchesoni M., Segarichi P., Soressi E. A simple approach to flux and speed observation in induction motor drives. IEEE Transactions on Industry Applications. 1997, 44(4): 528~535
    [34] Lovati T., Marchesoni M., Oberti M. A microcontroller-based sensorless stator flux-oriented asynchronous motor drive for traction application. IEEE Transactions on Power Electronics, 1998, 13(4): 777~784
    [35] Jeong S. Y., Choi Y. O. Application of extended luenberger observer for induction motor control. in: Proceedings of ICPE'98, 1998. 304-309
    [36] Henneberger G., Brunsbach B. J. Field-oriented control of synchronous and asynchronous drives without mechanical sensors using a Kalman filter. EPE'91, 1991. 3664~3671
    [37] Kim Y. R., Sul S. K., Park M. H. Speed sensorless vector control of induction motor using an extended Kalman filter. IEEE Transactions on Industry Applications, 1994, 30(5): 1225~1233
    [38] Hilairet M., Auger F., Darengosse C. Two efficient Kalman filters for velocity estimation of induction motors. IEEE PESC'2000, 2000. 891~896
    [39] Hurst K. D., Habetler T. G. Speed sensorless field-oriented control of induction machines using current harmonic spectral estimation. in: Proc. of IEEE IAS Ann. Mtg., 1994. 601~607
    [40] Briz F., Diez A., Denger M. W. Dynamic operation of carrier signal injection based sensorless direct field oriented AC drives. in: Proc. of IEEE IAS Ann. Mtg., 1999. 2313~2320
    [41] Holtz J. Senserless position control of induction motors-An emerging technology. IEEE Transactions on Industry Applications, 1998, 45(11): 840~852
    [42] Kozo I. High frequency injection method improved by flux observer for sensorless control of an Induction Motor. PCC2002, 2002. 516~521
    [43] Blaschke F., Vander B. J., Vandenput A. Sensorless direct field orientation at zero flux frequency. in: Proc. of IAS Ann. Mtg, 1996. 189~196
    [44] Gerrada G. A., Tanfiq J. A. Convergence of rotor flux estimation in field oriented control. in: Third International Conference on Power Electronics and Variable-Speed Drives, 1998. 291~295
    [45] Hurst K. D., Habetler T. G. A comparison of spectrum estimation techniques for sensorless speed detection in induction machines. IEEE Trans. on Industry Applications, 1997, 33(4): 898~905
    [46] Pereira L. F., Haffner J. F., Hemerly E. M. Direct vector control for a servo-positioner using an alternative rotor flux estimation algorithm. in: IECON'98, 1998. 1603~1608
    [47] Xu X. Y., Novotny D. W. Implementation of direct stator flux oriented control on a versatile DSP based system. IEEE Trans. on Industry Application, 1991, 27(4): 694~700
    [48] Xue Y., Xu X. Y., Habetler T.G., et al. A low cost stator flux oriented voltage source variable speed drive. in: Industry Applications Society Annual Meeting, 1990. 410~415
    [49] Lovati V., Marchesoni M., Oberti M., et al. An induction motor drive with stator flux oriented control low-cost implementation. in: Proc. ISIE'96 Conf., 1996. 168~173
    [50] Xue Y. H., Xu X. Y., Habetler T. G., et al. A stator flux-oriented voltage source variable-speed drive based on DC link measurement. IEEE Trans. On Industry Applications. 1991, 27(5): 962~969
    [51] Holtz J., Quan J. T. Sensorless vector control of induction motors at very low speed using a nonlinear inverter model and parameter identification. IEEE Transactions on Industry Applications, 2002, 38(4): 1087~1095
    [52] Bose B. K. 现代电力电子学与交流传动(英文版). 北京:机械工业出版社,2003. 381~384
    [53] Idris N. R. N., Yatim A. H. M. An improved stator flux estimation in steady-state operation for direct torque control of induction machines. IEEE Trans. on Industry Applications. 2002, 38(1): 110~116
    [54] Tsuji M., Chen S., Izumi K., et al. Stability improvement of speed sensorless induction motor vector control system using q-axis flux with stator resistance identification. in: Power Electronics Specialists Conference, 1998. 1587~1592
    [55] 程曙,徐国卿,许哲雄. SPWM 逆变器死区效应分析.电力系统及其自动化学报. 20022(6): 39~42
    [56] 刘陵顺,尚安利,顾文锦. SPWM 逆变器死区效应的研究.电机与控制学报. 2001, 5(4): 237~241
    [57] 何建军,周鹊. PWM 逆变器中死区效应的定量分析.东南大学学报.1997, 27(5): 128~132
    [58] 严青,王离九. 感应电机定子磁通定向(SFO)控制中的死区效应分析.华中理工大学学报. 1994, 22(8): 97~100
    [59] Jeong S. G., Lee B. S., Kim K. S., et al. The analysis and compensation of dead time effects in PWM inverters. IEEE. Trans. on Industry Electronics. 1991, 38(2): 108~114
    [60] Dodson R.C., Evans P.E., Yazhi H.T. Compensating for dead time degradation of PWM inverter waveforms. Electric Power Applications, IEE Proceedings B. 1990, 137(2):73~81
    [61] Murai Y., Watanabe T., Iwasaki H. Waveform distortion and correction circuit for PWM inverters with switching lag-times. IEEE Trans. on Industry Applications. 1987, 23(5): 881~886
    [62] Liu Y. H., Chen C. L. Novel dead time compensation method for induction motor drives using space vector modulation. IEE Proceeding of Power Application. 1998, 145(4): 387~392
    [63] Munoz A. R., Lipo T. A. On-Line dead-time compensation technique for open-loop PWM-VSI drives. IEEE Transactions on Power Electronics. 1999, 14(4): 683~689
    [64] Sukeqawa T., Mizuno K. Fully digital vector controlled PWM VSI-fed AC drives with an inverter dead-time compensator strategy. IEEE Trans. on Industry Applications. 1991, 27(3): 552~559
    [65] Ataianese C., Capraro D., Tomasso G. A low cost digital SVM modulator with dead time compensation. PESC2001, 2001. 158~163
    [66] Lin J. L. A new approach of dead-time compensation for PWM voltage inverters. IEEE Trans. on Circuits and Systems. 2002, 49(4): 476~482
    [67] Leggate D., Russel J. Pulse-based dead-time compensator for PWM voltage inverters. IEEE Trans. on Industrial Electronics. 1997, 44(2): 191~197
    [68] Choi J .W., Sul S. K. New dead time compensation eliminating zero current clamping in voltage-fed PWM inverter. in: Industry Applications Society Annual Meeting, 1994. 977~984
    [69] Ficarra M. C., Eguilaz J. M. M., Peracaula J. Fuzzy control of an induction motor with compensation of system dead-time. PESC '96, 1996. 677~681
    [70] Jung J. H., Nam K. H. A PI-type dead-time compensation method for vector controlled GTO inverters. IEEE Trans. on Industry Applications. 1998, 34(3): 452~457
    [71] Choi Y. W., Ha J. I., Ki S. Suppression of vibration for elevator system using dead-time compensation with current prediction. in: Proc. of Advanced Motion Control, 2000. 439~442
    [72] Attaianese C., Tomasso G. Predictive compensation of dead-time effects in VSI feeding induction motors. IEEE Transactions on Industry Applications. 2001, 37(3): 856~863
    [73] Tonelli M., Battaioto P. FPGA implementation of an universal space vector modulator. in: IECON'01, 2001. 1172~117
    [74] Ataianese C., Capraro G. Hardware dead time compensation for VSI based electrical drives. in: ISIE'01, 2001. 759~764
    [75] Shin M. H., Hyun D. S., Cho S. B., et al. An improved stator flux estimation for speed sensorless stator flux orientation control of induction motors. IEEE Transactions on power electronics. 2000, 15(2): 312~318
    [76] 黎亚元,唐浦华,宋昌林.直接转矩控制中一种磁链估计新方法.中国电机工程学报.2000, 20(5): 22~29
    [77] Schierling H. Self-commissioning—A novel feature of modern induction motor drives. in: Proc. IEE Conf. Power Electron. Variable Speed Drives, 1988. 287~290.
    [78] Kerkman R. J., Thunes J. D., Rowan T. M., et al. A frequency-based determination of transient inductance and rotor resistance for field commissioning purposes. IEEE Transactions on power applications. 1996, 32(3): 577~584
    [79] Wang C., Novotny D. W., Lipo T. A. An automated rotor time constant measurement system for indirect field-oriented drives. 1998, 24(1): 151~159
    [80] Seok J. K., Moon S. I., Sul S. K. Induction machine parameter identification using PWM inverter at standstill. IEEE Trans. Energy Conversion. 1997, 12(2): 127~132
    [81] Attaianese C., Nardi V., Tomasso G. A self-commissioning algorithm for VSI-Fed induction motors. IEEE Trans. Power Electron. 2002, 17(6): 1017~1023
    [82] Gastli A., Matsui N. Stator flux controlled V/f PWM inverter with identification of IM parameters. IEEE Trans. Ind. Electron. 1992, 39(4): 334~340
    [83] Yang G., Chin T. H. Adaptive-speed Identification scheme for a vector controlled speed Sensorless inverter induction motor drive. IEEE Trans. Ind. Applicat. 1993, 29 (4): 820~825
    [84] 余功军,杨耕,钟彦儒. 无速度传感器矢量控制变频调速器的研究. 电力电子技术. 1999, 33(5): 15~17
    [85] Bose B. K., Patel N. R. Quasi-fuzzy estimation of stator resistance of induction motor. IEEE Trans. on Power Electronics. 1998, 13(3): 401~409
    [86] Zhong L., Rahman M. F., Lim K.W., et al. A fuzzy observer for induction motor stator resistance for application in direct torque control. in: Proc. of Power Electronics and Drive Systems, 1997. 91~96
    [87] Hu Y. W., Tang L. X. A resistor on-line fuzzy observer of induction motor direct torque control (DTC) system. in: IPEMC'94, 1994. 715~720
    [88] Cabrera L. A., Elbuluk M. E., Husain. Tuning the stator resistance of induction motors using artificial neural network. IEEE Trans. on Power Electronics. 1997, 12(5): 779~787
    [89] Campbell A., Sumner M., Curtis M. An improved sensorless vector controlled induction motor drive employing artificial neural networks for stator resistance estimation. in: Proc. of Power Electronics and Variable Speed Drives, 2000: 274~279
    [90] 陈坚. 交流电机数学模型及调速系统. 武汉:华中理工大学出版社,1986. 40~78
    [91] Xu X. Y., Doncker R. D., Novotny D. W. A stator flux oriented induction motor drive. in: PESC’88 Rec., 1988. 870~876
    [92] 宗孔德,胡广书. 数字信号处理. 北京:清华大学出版社,1988. 11~5
    [93] 张贤达. 现代信号处理. 北京:清华大学出版社,1995. 20~29
    [94] Soille P., Talbot H. Directional morphological filtering. IEEE Trans. on Pattern Analysis and Machine Intelligence. 2001, 23(11): 1313~1327
    [95] 唐常青,吕宏伯. 数学形态学方法及其应用. 北京:科学出版社,1990. 10~21
    [96] Jiang S. D., Lu Z. M. Morphological filter based noise removal from vibration signals of fighter plane. in: Proceedings of International Symposium on Intelligent Multimedia, 2001. 251~254
    [97] 于泳. 变频空调压缩机电机无速度传感器矢量控制系统研究:[博士学位论文]。哈尔滨工业大学:哈尔滨工业大学图书馆, 2003. Murai Y., Riyanto A., Nakamura H., et al. PWM strategy for high carrier inverters eliminating current clamps during switching dead-time. in:
    [98] Conference Record of the 1992 IEEE, 1992. 317~322
    [99] Baghli L., Razik H., Rezzoug A. A stator flux oriented drive for an induction motor with Extra (α , β) Coils. in: IECON'98, 1998. 2522~2526
    [100] Habetler T. G., Profumo F., Griva G., et al. Stator resistance tuning in a stator-flux field-oriented drive using an instantaneous hybrid flux estimator. IEEE Trans. on Power Electronics. 1998, 13(1): 125~133
    [101] 徐金榜. 三相电压源 PWM 整流器控制技术研究:[博士学位论文]。华中科技大学:华中科技大学图书馆, 2004.
    [102] Lin Y. N., Chen C. L. Automatic IM parameter measurement under sensorless field-oriented control. IEEE Trans. on Industrial Electronics. 1999, 46(1): 111~118
    [103] 余功军,钟彦儒,杨耕. 无速度传感器矢量控制系统中的电机参数辨识. 电气传动.1999, 30(1): 7~10
    [104] Hayes M. H. 数字信号处理. 张建华等译. 北京:科学出版社,2002. 112~124
    [105] 邹云屏,李潇. 信号变换与处理. 武汉:华中理工大学出版社,1994. 222~229
    [106] Cirrincione M., Pucci M., Cirrincione G., et al. A new experimental application of least-squares techniques for the estimation of the induction motor parameters. IEEE Trans. on Industrial Electronics. 2002, 32(5): 1171~1180
    [107] Moucary C. E., Garcia G., Mendes E. Robust rotor flux, rotor resistance and speed estimation of an induction machine using the extended Kalman filter. in: Proc. of the 1999 IEEE international symposium on industrial electronics, 1999. 742~746
    [108] Corcoles F., Pedra J., Salichs M., et al. Analysis of the induction machine parameter identification. IEEE Trans. on Energy Conversion. 2002, 17(2): 183~190
    [109] Szabados B., Ye M. Dynamic parameter identification of induction machines using spectral analysis and output error optimization. in: Instrument and Measurement Technology Conference 2004, 2004. 2200~2203
    [110] Ohnishi K., Matsui N., Hori Y. Estimation, identification, and sensorless control in motion control system. Proc. of the IEEE’94. 1994, 82(8): 1253~1265
    [111] Mitronikas E. D., Safacas A. N., Tatakis E. C. A new stator resistance tuning method for stator-flux-oriented vector-controlled induction motor drive. IEEE Trans. on Industrial Electronics. 2001, 48(6): 1148~1157
    [112] 邱阿瑞,尹雁,王光辉等. 基于 DSP 的无速度传感器异步电机矢量控制系统. 清华大学学报(自然科学版). 2001, 41(3): 21~24
    [113] 廖勇,张凤蕊. 无传感器矢量控制系统及其速度估算的研究. 电工技术学报. 2004, 19(2): 36~40
    [114] 宫明玉,廖晓钟,冬雷. 无速度传感器异步电机按定子磁链定向的矢量控制系统. 2005, 35(7): 20~23

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