永磁同步电动机高性能无传感器控制技术研究
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摘要
永磁同步电动机由于具有体积小、功率密度和效率高，运行性能好等优点，在理论研究和实际应用中得到广泛重视；目前，永磁同步电动机作为控制系统执行元件的核心已广泛地应用于数控机床、机器人以及航空、航天和航海等领域中。本文结合电动汽车应用的需要，以无位置传感器永磁同步电动机驱动系统为研究对象，有针对性地对电机转子位置和转速的在线估计、电机的控制策略以及死区补偿等问题进行了较为深入的研究。目的是为了降低电动汽车电气驱动系统的成本与复杂性，进一步提高控制系统的可靠性和控制性能。
在研究课题中，首先根据坐标变换理论推导了永磁同步电动机在两相静止坐标系下的电机模型，并结合扩展卡尔曼滤波器理论设计了相应的转子速度、位置观测器。虽然扩展卡尔曼滤波算法能实现电机的自启动，但由于转子初始位置角未知，算法在启动中可能会出现的收敛错误和失速问题，本文针对这一问题给出了详细解释并讨论了相关的解决方法。由于噪声协方差矩阵对估计性能有很大的影响，本文通过仿真分析了不同矩阵取值对结果产生的影响，并总结了一套参数试凑方法。
由于扩展卡尔曼滤波器的估计精度受电机模型参数变化影响，通过仿真总结了参数变化对估计精度影响的规律。针对这一问题，对自适应渐消扩展卡尔曼滤波器进行了较为深入的研究。引入衰减因子对原扩展卡尔曼滤波器的误差协方差矩阵进行加权，这样能够减小陈旧量测值对估计的影响，强化新的量测数据在滤波中所起的校正作用，从而能提高跟踪速度和估计精度。考虑到卡尔曼滤波器在高阶时计算量大的问题，引入一种两段式结构将扩展卡尔曼滤波器分解成两个并行的低阶滤波器，达到节省运算量的目的，通过乘法和加法运算量的对比体现出两段扩展卡尔曼滤波器在运算量上所具有的优势，利用滤波器之间的等效性验证了所提出滤波器的稳定性。结合自适应扩展卡尔曼滤波器和双段扩展卡尔曼滤波器各自的特点，提出一种新的自适应双段扩展卡尔曼滤波器，并采用相同的等效性证明验证了其稳定性，这种滤波器是将双段结构应用到自适应扩展卡尔曼滤波器上而得出，同时具有自适应滤波器强跟踪、鲁棒性好和双段滤波器节省运算量的优点。
在电流控制中，针对已有的线性比例微分控制策略存在的动态响应速度慢，对控制器参数的依赖度高等问题，采用一种无差拍预测电流控制方法来进行永磁同步电动机的电流控制。由于这类基于模型的控制方法对参数精确度要求较高，设计了扰动观测器来估计未建模的不确定项，针对电压型逆变器中的死区时间和非线性等因素造成的电压损失，通过相应的死区电压观测器在线估计，并将两个观测器的估计值加入到电压指令值中进行补偿。由于速度环PI控制器的非线性饱和特性，提出了一种变结构抗饱和PI速度控制器来提高转速控制性能。
针对自适应双段扩展卡尔曼滤波器和无差拍预测电流控制方法，设计了基于Expert3系统的全数字无位置传感器永磁同步电动机控制系统。在此基础上，对各研究内容进行了深入的仿真研究和实验验证。
Because of several advantages, such as compactness, high power density, high efficiencyand good operation performance, permanent magnet synchronous motors (PMSMs) areattracting extensive attention in theory research and practical application. Now, PMSMs,which are used as a core implementation component, have been widely used in CNC, robot,aerospace, marine and other fields. In this paper, according to the requirements of the electricvehicle control system, this dissertation made the studies on sensorless control of PMSM.Taking the sensorless PMSM control system as the research target, this dissertation conductedsome research in-depth on the following issues, including on-line estimation of the rotorposition and speed, control method of the motor, dead-time compensation and so on. It aimsto reduce the cost and complexity of drive system, and to further improve the reliability andcontrol performance of motor control system.
Based on coordinate transformation, PMSM model in the two-phase frame system wasderived firstly, and then an Extended Kalman Filter (EKF) for closed-loop rotor speed andposition estimation of PMSM was designed based on the above model. Although the initialrotor position is unknown, the sensorless control stategy has key ability of self-startup.Whereas, during startup transient, convergence error and stall issues may happen. In order tosolve these problems, detailed explanations for these issues are given and relevant solutionsare discussed.
Considering that the noise covariance matrix has a great impact on estimationperformance, the influence on estimates by noise covariance matrix is analyzed by simulationresults, and the trial-and-error method for setting noise covariance matrix is summarized.
This extended Kalman filtering technique requires complete specifications of dynamicalmodel parameters to guarantee estimation accuracy, and impact on estimation accuracy byparameters variation is summarized by simulation results. To solve this problem, an in-depthstudy on adaptive fading extended Kalman filter (AFEKF) is made. A fading factor, whichenhances the influence of innovation information, may be incorporated as a multiplier forimproving the tracking capability and estimation accuracy in high dynamic control of PMSM.
To reduce computational complexity, a nonlinear two-stage extended Kalman filter(NTSEKF), which employs the two-stage structure, is proposed by decoupling the EKF intotwo parallel reduced-order filters. By using the number of arithmetic operations(multiplications and additions) as the measure of computational complexity, thecomputational advantage of the two-stage Kalman filter over the conventional Kalman Filter has been demonstrated. Because EKF is uniformly asymptotically stable, the stability ofNTSEKF is verified by showing that NTSEKF is equivalent to EKF. Combining advantagesof NTSEKF and AFEKF, adaptive two-stage extended Kalman filter (ATEKF) is developedby decoupling the AFEKF into two parallel reduced-order filters. ATEKF has both strongrobustness against model-plant parameter mismatches and good real-time state tracking ability.The stability of ATEKF is verified by the same method as in NTSEKF.
Currently, linear PI controllers were mostly employed for the control of the current loop.PI controller gains excellent steady-state performance, but the dynamic response is slow andthe control effect depends greatly on the PI parameters. In order to overcome the drawbacksof the PI controller, this paper presented a novel control scheme for current loop by replacingthe PI controllers with predictive current control (PCC) controller. Inaccuracy in systemmodels may seriously degrade the performance of the PCC controller. Treating inaccuraciesas disturbances, the disturbances caused by the parameter variations and dead time arecompensated by the two online observers, respectively. Aiming at the saturation nonlinearityof the speed control loop PI controller, a variable structure anti-windup PI controller isproposed to improve the speed control performance.
Based on Expert3system, a full-digital sensorless PMSM control system is designed torealize the ATEKF and PCC controller. Based on these algorithms and hardware, in-depthsimulation research and experiment validation are made.
在研究课题中，首先根据坐标变换理论推导了永磁同步电动机在两相静止坐标系下的电机模型，并结合扩展卡尔曼滤波器理论设计了相应的转子速度、位置观测器。虽然扩展卡尔曼滤波算法能实现电机的自启动，但由于转子初始位置角未知，算法在启动中可能会出现的收敛错误和失速问题，本文针对这一问题给出了详细解释并讨论了相关的解决方法。由于噪声协方差矩阵对估计性能有很大的影响，本文通过仿真分析了不同矩阵取值对结果产生的影响，并总结了一套参数试凑方法。
由于扩展卡尔曼滤波器的估计精度受电机模型参数变化影响，通过仿真总结了参数变化对估计精度影响的规律。针对这一问题，对自适应渐消扩展卡尔曼滤波器进行了较为深入的研究。引入衰减因子对原扩展卡尔曼滤波器的误差协方差矩阵进行加权，这样能够减小陈旧量测值对估计的影响，强化新的量测数据在滤波中所起的校正作用，从而能提高跟踪速度和估计精度。考虑到卡尔曼滤波器在高阶时计算量大的问题，引入一种两段式结构将扩展卡尔曼滤波器分解成两个并行的低阶滤波器，达到节省运算量的目的，通过乘法和加法运算量的对比体现出两段扩展卡尔曼滤波器在运算量上所具有的优势，利用滤波器之间的等效性验证了所提出滤波器的稳定性。结合自适应扩展卡尔曼滤波器和双段扩展卡尔曼滤波器各自的特点，提出一种新的自适应双段扩展卡尔曼滤波器，并采用相同的等效性证明验证了其稳定性，这种滤波器是将双段结构应用到自适应扩展卡尔曼滤波器上而得出，同时具有自适应滤波器强跟踪、鲁棒性好和双段滤波器节省运算量的优点。
在电流控制中，针对已有的线性比例微分控制策略存在的动态响应速度慢，对控制器参数的依赖度高等问题，采用一种无差拍预测电流控制方法来进行永磁同步电动机的电流控制。由于这类基于模型的控制方法对参数精确度要求较高，设计了扰动观测器来估计未建模的不确定项，针对电压型逆变器中的死区时间和非线性等因素造成的电压损失，通过相应的死区电压观测器在线估计，并将两个观测器的估计值加入到电压指令值中进行补偿。由于速度环PI控制器的非线性饱和特性，提出了一种变结构抗饱和PI速度控制器来提高转速控制性能。
针对自适应双段扩展卡尔曼滤波器和无差拍预测电流控制方法，设计了基于Expert3系统的全数字无位置传感器永磁同步电动机控制系统。在此基础上，对各研究内容进行了深入的仿真研究和实验验证。
Because of several advantages, such as compactness, high power density, high efficiencyand good operation performance, permanent magnet synchronous motors (PMSMs) areattracting extensive attention in theory research and practical application. Now, PMSMs,which are used as a core implementation component, have been widely used in CNC, robot,aerospace, marine and other fields. In this paper, according to the requirements of the electricvehicle control system, this dissertation made the studies on sensorless control of PMSM.Taking the sensorless PMSM control system as the research target, this dissertation conductedsome research in-depth on the following issues, including on-line estimation of the rotorposition and speed, control method of the motor, dead-time compensation and so on. It aimsto reduce the cost and complexity of drive system, and to further improve the reliability andcontrol performance of motor control system.
Based on coordinate transformation, PMSM model in the two-phase frame system wasderived firstly, and then an Extended Kalman Filter (EKF) for closed-loop rotor speed andposition estimation of PMSM was designed based on the above model. Although the initialrotor position is unknown, the sensorless control stategy has key ability of self-startup.Whereas, during startup transient, convergence error and stall issues may happen. In order tosolve these problems, detailed explanations for these issues are given and relevant solutionsare discussed.
Considering that the noise covariance matrix has a great impact on estimationperformance, the influence on estimates by noise covariance matrix is analyzed by simulationresults, and the trial-and-error method for setting noise covariance matrix is summarized.
This extended Kalman filtering technique requires complete specifications of dynamicalmodel parameters to guarantee estimation accuracy, and impact on estimation accuracy byparameters variation is summarized by simulation results. To solve this problem, an in-depthstudy on adaptive fading extended Kalman filter (AFEKF) is made. A fading factor, whichenhances the influence of innovation information, may be incorporated as a multiplier forimproving the tracking capability and estimation accuracy in high dynamic control of PMSM.
To reduce computational complexity, a nonlinear two-stage extended Kalman filter(NTSEKF), which employs the two-stage structure, is proposed by decoupling the EKF intotwo parallel reduced-order filters. By using the number of arithmetic operations(multiplications and additions) as the measure of computational complexity, thecomputational advantage of the two-stage Kalman filter over the conventional Kalman Filter has been demonstrated. Because EKF is uniformly asymptotically stable, the stability ofNTSEKF is verified by showing that NTSEKF is equivalent to EKF. Combining advantagesof NTSEKF and AFEKF, adaptive two-stage extended Kalman filter (ATEKF) is developedby decoupling the AFEKF into two parallel reduced-order filters. ATEKF has both strongrobustness against model-plant parameter mismatches and good real-time state tracking ability.The stability of ATEKF is verified by the same method as in NTSEKF.
Currently, linear PI controllers were mostly employed for the control of the current loop.PI controller gains excellent steady-state performance, but the dynamic response is slow andthe control effect depends greatly on the PI parameters. In order to overcome the drawbacksof the PI controller, this paper presented a novel control scheme for current loop by replacingthe PI controllers with predictive current control (PCC) controller. Inaccuracy in systemmodels may seriously degrade the performance of the PCC controller. Treating inaccuraciesas disturbances, the disturbances caused by the parameter variations and dead time arecompensated by the two online observers, respectively. Aiming at the saturation nonlinearityof the speed control loop PI controller, a variable structure anti-windup PI controller isproposed to improve the speed control performance.
Based on Expert3system, a full-digital sensorless PMSM control system is designed torealize the ATEKF and PCC controller. Based on these algorithms and hardware, in-depthsimulation research and experiment validation are made.
引文
[1]王成元,夏加宽,杨俊友.电机现代控制技术[M].北京:机械工业出版社,2006:104-110
[2]唐任远.现代永磁电机理论与设计[M].北京:机械工业出版社,1997:12-30
[3]谭立新.永磁同步电机在电梯系统中的应用分析[J].机械研究与应用,2011,(06):157-158
[4]姚晓明.简谈永磁同步电机在电梯技术上的应用[J].科技信息,2010,(28):750,752
[5]彭海涛,何志伟,余海阔.电动汽车用永磁同步电机的发展分析[J].微电机,2010,(06):78-81
[6]代颖,王立欣,崔淑梅.电动汽车用永磁同步电机评述[J].微电机(伺服技术),2005,(03):84-86
[7]杨克信.永磁材料在永磁电机中的应用探讨[J].上海大中型电机,2004,(04):26-30
[8]杨大伟.稀土永磁材料及电机发展概况[J].微电机,1994,(02):26-31
[9]闵琳,权利,莫会成.永磁材料和永磁电机[J].电气技术,2006,(07):14-16,20
[10]袁磊.浅谈电力电子的发展及未来展望[J].科技风,2008,(04):58
[11]李现兵,师宇杰,王广州,等.浅谈现代电力电子器件的发展[J].电力电子,2005,(03):23-26,44
[12]崔晶,张丽娜.现代电力电子及电源技术的发展趋势[J].科技信息(科学教研),2008,(09):28,9
[13]蔡宣三.电力电子器件的模块化与集成化[J].今日电子,2004,(09):39-40,42
[14]刘亚静,李铁才.电机数字控制器发展现状[J].伺服控制,2011,(08):25-28,32
[15]胡海兵.电力电子集成系统中的数字控制平台研究[D].浙江大学,2007
[16] Bester D D, du Toit J A, Enslin J H R. High performance DSP/FPGA controllerfor implementation of computationally intensive algorithms[A]. Proceedings of the1998International Symposium on Industrial Electronics[C],1998,1:240-244
[17]赵光宙,黄雷.交流传动的无速度传感器技术综述[J].电气应用,2008,(04):20-26
[18]张凌云,赖豪杰.先进控制理论及策略在电机控制中的应用[J].电机技术,2005,(02):39-42
[19] Morimoto M, Sumito K, Sato S, et al. High efficiency, unity power factor VVVFdrive system of an induction motor[J]. IEEE Transactions on Power Electronics,1991,6(3):498-503
[20] Chen S, Yeh S N. Optimal efficiency analysis of induction motors fed byvariable-voltage and variable-frequency source[J]. IEEE Transactions on EnergyConversion,1992,7(3):537-543
[21] F. B. The principle of field orientation as applied to the new Transvectorclosed-loop control system for rotating-field machines[R].1971
[22]王子辉.永磁同步电机全速度范围无位置传感器控制策略研究[D].杭州:浙江大学,2012
[23]尚喆.永磁同步电动机磁场定向控制的研究[D].杭州:浙江大学,2007
[24] Fazai R, Jalili-Kharaajoo M. High performance speed control of interiorpermanent magnet synchronous motors with maximum power factor operation[A].Proceedings of the200310th IEEE International Conference on Electronics, Circuitsand Systems.[C],2003,3:1125-1128
[25] Nakamura Y, Kudo T, Ishibashi F, et al. High-efficiency drive due to power factorcontrol of a permanent magnet synchronous motor[J]. IEEE Transactions on PowerElectronics,1995,10(2):247-253
[26] Inoue Y, Morimoto S, Sanada M. Comparative Study of PMSM Drive SystemsBased on Current Control and Direct Torque Control in Flux-Weakening ControlRegion[J]. IEEE Transactions on Industry Applications,2012,48(6):2382-2389
[27] Liu H, Zhu Z Q, Mohamed E, et al. Flux-Weakening Control of Nonsalient PolePMSM Having Large Winding Inductance, Accounting for Resistive Voltage Dropand Inverter Nonlinearities[J]. IEEE Transactions on Power Electronics,2012,27(2):942-952
[28] Sarikhani A, Mohammed O A. Demagnetization Control for Reliable FluxWeakening Control in PM Synchronous Machine[J]. IEEE Transactions on EnergyConversion,2012,27(4):1046-1055
[29] Zhao J, Liu W, Tan B. Research of maximum ratio of torque to current controlmethod for PMSM based on least square support vector machines[A]. Proceedings-International Conference on Electrical and Control Engineering[C],2010,10.1109/iCECE.2010.400:1623-1628
[30] Tahami F, Nademi H, Rezaei M. A high-performance vector-controlled PMSMdrive with maximum torque per ampere operation[A]. PECon2008-2008IEEE2ndInternational Power and Energy Conference[C],2008:254-258
[31] Zhao J, Liu W, Tan B. Research of maximum ratio of torque to current controlmethod for PMSM based on least square support vector machines[A]. Proceedings-International Conference on Electrical and Control Engineering2010[C],2010,10.1109/iCECE.2010.400:1623-1628
[32] Depenbrock M. Direkte selbstregelung (DSR) fur hochdynamischeDrehfeld-antriebe mit Stromrichterspeisung[J]. etz-Archiv,1985,7(7):211-218
[33] Takahashi I, Noguchi T. A New Quick-Response and High-Efficiency ControlStrategy of an Induction Motor[J]. IEEE Transactions on Industry Applications,1986,IA-22(5):820-827
[34] Faiz J, Mohseni-Zonoozi S H. A novel technique for estimation and control ofstator flux of a salient-pole PMSM in DTC method based on MTPF[J]. IEEETransactions on Industrial Electronics,2003,50(2):262-271
[35] Zhang Y, Zhu J, Xu W, et al. A Simple Method to Reduce Torque Ripple in DirectTorque-Controlled Permanent-Magnet Synchronous Motor by Using Vectors WithVariable Amplitude and Angle[J]. IEEE Transactions on Industrial Electronics,,2011,58(7):2848-2859
[36]周扬忠,胡育文,黄文新.低转矩磁链脉动型电励磁同步电机直接转矩驱动系统的研究[J].中国电机工程学报,2006,26(07):152-157
[37]李君,李毓洲.无速度传感器永磁同步电机的SVM-DTC控制[J].中国电机工程学报,2007,27(03):28-34
[38]苏成利.非线性模型预测控制的若干问题研究[D].杭州:浙江大学,2006
[39]席裕庚,李德伟,林姝.模型预测控制——现状与挑战[J].自动化学报,2013,39(03):222-236
[40]石宇静.复杂工业过程模型预测控制的研究[D].沈阳:东北大学,2009
[41]高丽媛.永磁同步电机的模型预测控制研究[D].杭州:浙江大学,2013
[42] Yu J, Teng Z, Zhang J, et al. Predictive current control and stability analysis ofactive power filter[J]. Diangong Jishu Xuebao/Transactions of China ElectrotechnicalSociety,2009,24(7):164-170
[43] Verne S A, Valla M I. Active power filter for medium voltage networks withpredictive current control[J]. Electric Power Systems Research,2010,80(12):1543-1551
[44] Moreno J C, Espi Huerta J M, Gil R G, et al. A robust predictive current controlfor three-phase grid-connected inverters[J]. IEEE Transactions on IndustrialElectronics,2009,56(6):1993-2004
[45] Moon G-W, Lee J-H, Youn M-J. Push-pull quantum series resonant rectifier withpredictive current control[J]. International Journal of Electronics,1995,79(3):363-377
[46] Xie Y, Ghaemi R, Sun J, et al. Model Predictive Control for a Full Bridge DC/DCConverter[J]. IEEE Transactions on Control Systems Technology,2012,20(1):164-172
[47] Quevedo D E, Aguilera R P, Perez M A, et al. Model Predictive Control of anAFE Rectifier With Dynamic References[J]. IEEE Transactions on Power Electronics,2012,27(7):3128-3136
[48] Barrero F, Prieto J, Levi E, et al. An enhanced predictive current control methodfor asymmetrical six-phase motor drives[J]. IEEE Transactions on IndustrialElectronics,2011,58(8):3242-3252
[49] Barrero F, Arahal M R, Gregor R, et al. One-step modulation predictive currentcontrol method for the asymmetrical dual three-phase induction machine[J]. IEEETransactions on Industrial Electronics,2009,56(6):1974-1983
[50] Mariethoz S, Domahidi A, Morari M. High-bandwidth explicit model predictivecontrol of electrical drives[J]. IEEE Transactions on Industry Applications,2012,48(6):1980-1992
[51] Dong L, Dou L, Chen J, et al. Hybrid model predictive control for speed controlof permanent magnet synchronous motor with saturation[J]. Journal of ControlTheory and Applications,2011,9(2):251-255
[52]席裕庚.预测控制[M].北京:国防工业出版社,1993:10-18
[53]舒迪前.预测控制系统及其应用[M].北京:机械工业出版社,1996:127-173
[54] Mohamed Y A R I. Design and Implementation of a Robust Current-ControlScheme for a PMSM Vector Drive With a Simple Adaptive Disturbance Observer[J].IEEE Transactions on Industrial Electronics,2007,54(4):1981-1988
[55]梁艳,李永东.无传感器永磁同步电机矢量控制系统概述[J].电气传动,2003,(04):4-9
[56] Suwankawin S, Sangwongwanich S. Design strategy of an adaptive full-orderobserver for speed-sensorless induction-motor Drives-tracking performance andstabilization[J]. IEEE Transactions on Industrial Electronics,2006,53(1):96-119
[57] Kubota K, Matsuse K, Nakano T. DSP-based speed adaptive flux observer ofinduction motor[J]. IEEE Transactions on Industry Applications,1993,29(2):344-348
[58] Kubota K, Sato I, Tamura Y, et al. Regenerating-mode low-speed operation ofsensorless induction motor drive with adaptive observer[J]. IEEE Transactions onIndustry Applications,2002,38(4):1081-1086
[59] Chan T F, Wang W, Borsje P, et al. Sensorless permanent-magnet synchronousmotor drive using a reduced-order rotor flux observer[J]. IET Electric PowerApplications,2008,2(2):88-98
[60] Hinkkanen M, Tuovinen T, Harnefors L, et al. A Combined Position andStator-Resistance Observer for Salient PMSM Drives: Design and StabilityAnalysis[J]. IEEE Transactions on Power Electronics,2012,27(2):601-609
[61]苏健勇,李铁才,杨贵杰. PMSM无位置传感器控制中数字滑模观测器抖振现象分析与抑制[J].电工技术学报,2009,24(08):58-64
[62]程帅,姜海博,黄进,等.基于滑模观测器的单绕组多相无轴承电机无位置传感器控制[J].电工技术学报,2012,27(07):71-77
[63] Utkin V, Lee H. Chattering Problem in Sliding Mode Control Systems[A].Proceedings of the2006International Workshop on Variable Structure System[C],2006,10.1109/VSS.2006.1644542:346-350
[64] Paponpen K, Konghirun M. An Improved Sliding Mode Observer for SpeedSensorless Vector Control Drive of PMSM[A]. Conference Proceedings-IPEMC2006: CES/IEEE5th International Power Electronics and Motion ControlConference[C],2006,2:1-5
[65] Li C, Elbuluk M. A robust sliding mode observer for permanent magnetsynchronous motor drives[A]. IECON Proceedings[C],2002,2:1014-1019
[66] Yu S H, Hu J S. Stability and performance of single-bit sigma-delta modulatorsoperated in quasi-sliding mode[J]. Circuits, Systems, and Signal Processing,2006,25(5):571-590
[67] Corradini M L, Ippoliti G, Longhi S, et al. A Quasi-Sliding Mode Approach forRobust Control and Speed Estimation of PM Synchronous Motors[J]. IEEETransactions on Industrial Electronics,2012,59(2):1096-1104
[68]高为炳,程勉.变结构控制系统的品质控制[J].控制与决策,1989,4(04):1-6
[69]高为炳.非线性系统的变结构控制[J].自动化学报,1989,15(05):408-415
[70]米阳,李文林,井元伟.基于幂次趋近律的一类离散时间系统的变结构控制[J].控制与决策,2008,23(06):643-646
[71]张巍巍,王京.基于指数趋近律的非奇异Terminal滑模控制[J].控制与决策,2012,27(06):909-913
[72]王静.基于无传感器的电动汽车电机控制技术研究[D].广州:华南理工大学,2012
[73]刘英培,万健如,梁鹏飞.基于扩展卡尔曼滤波器和空间电压矢量调制的永磁同步电机直接转矩控制[J].中国电机工程学报,2009,29(27):67-74
[74]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
[75]尹忠刚,赵昌,钟彦儒,等.采用抗差扩展卡尔曼滤波器的感应电机转速估计方法[J].中国电机工程学报,2012,32(18):152-159,190
[76] Szabat K, Orlowska-Kowalska T, Dyrcz K P. Extended Kalman filters in thecontrol structure of two-mass drive system[J]. Bulletin of the Polish Academy ofSciences: Technical Sciences,2006,54(3):315-325
[77] Orlowska-Kowalska T, Szabat K. Neural-Network application for mechanicalvariables estimation of a two-mass drive system[J]. IEEE Transactions on IndustrialElectronics,2007,54(3):1352-1364
[78] Dah-Jing J, Sheng-Hung W. Adaptive Fuzzy Strong Tracking Extended KalmanFiltering for GPS Navigation[J]. IEEE Sensors Journal,2007,7(5):778-789
[79] Soken H E, Hajiyev C. Adaptive Unscented Kalman Filter with multiple fadingfactors for pico satellite attitude estimation[A]. Proceedings of4th InternationalConference on Recent Advances Space Technologies[C],2009,10.1109/RAST.2009.5158254:541-546
[80]王庆龙.交流电机矢量控制系统滑模变结构控制策略研究[D].合肥:合肥工业大学,2007
[81] Khlaief A, Boussak M, Chaari A. A MRAS-based stator resistance and speedestimation for sensorless vector controlled IPMSM drive[J]. Electric Power SystemsResearch,2014,1081-15
[82] Piippo A, Hinkkanen M, Luomi J. Analysis of an Adaptive Observer forSensorless Control of Interior Permanent Magnet Synchronous Motors[J]. IEEETransactions on Industrial Electronics,2008,55(2):570-576
[83] Limei W, Lorenz R D. Rotor position estimation for permanent magnetsynchronous motor using saliency-tracking self-sensing method[A]. Proceedings ofIEEE35th IAS Annual Meeting[C],2000,1:445-450vol.1
[84] Jansen P L, Lorenz R D. Transducerless field orientation concepts employingsaturation-induced saliencies in induction machines[J]. IEEE Transactions on IndustryApplications,1996,32(6):1380-1393
[85] Noguchi T, Takehana K, Kondo S. Mechanical-sensorless robust control ofpermanent magnet synchronous motor using phase information of harmonic reactivepower[A]. Conference Record-IAS Annual Meeting[C],2000,3:1781-1786
[86] Jang J-H, Sul S-K, Ha J-I, et al. Sensorless drive of surface-mountedpermanent-magnet motor by high-frequency signal injection based on magneticsaliency[J]. IEEE Transactions on Industry Applications,2003,39(4):1031-1039
[87] Zhou Y, Cui Y, Wang X, et al. Technique on fuzzy sliding mode observer forpermanent magnet synchronous motor (PMSM) sensorless detection[J]. Journal ofHarbin Engineering University,2013,34(6):728-733
[88] Gumus B, Ozdemir M. Sensorless vector control of a Permanent magnetsynchronuous motor with fuzzy logic observer[J]. Electrical Engineering,2006,88(5):395-402
[89] Mese E, Torrey D A. An approach for sensorless position estimation for switchedreluctance motors using artificial neural networks[J]. IEEE Transactions on PowerElectronics,2002,17(1):66-75
[90] Heredia J R, Hidalgo F P, Duran Paz J L. Sensorless control of induction motorsby artificial neural networks[J]. IEEE Transactions on Industrial Electronics,2001,48(5):1038-1040
[91] Garcia P, Briz F, Raca D, et al. Saliency-tracking-based sensorless control of acmachines using structured neural networks[J]. IEEE Transactions on IndustryApplications,2007,43(1):77-86
[92] Chaoui H, Sicard P. Adaptive Lyapunov-based neural network sensorless controlof permanent magnet synchronous machines[J]. Neural Computing and Applications,2011,20(5):717-727
[93] Seong-Hwan K, Tae-Sik P, Ji-Yoon Y, et al. Speed-sensorless vector control of aninduction motor using neural network speed estimation[J]. IEEE Transactions onIndustrial Electronics,2001,48(3):609-614
[94] Batzel T D, Lee K Y. An approach to sensorless operation of thepermanent-magnet synchronous motor using diagonally recurrent neural networks[J].IEEE Transactions on Energy Conversion,2003,18(1):100-106
[95]张嗣瀛,高立群.现代控制理论[M].北京:清华大学出版社,2006:91-95
[96]刘豹,唐万生.现代控制理论[M].北京:机械工业出版社,2011:1-80
[97]肖春燕.电压空间矢量脉宽调制技术的研究及其实现[D].南昌:南昌大学,2005
[98] Grewal M S, Andrews A P. Kalman Filtering: Theory and Practice UsingMATLAB[M]. Hoboken: Wiley-IEEE Press,2001:169-182
[99] Mathworks. Simulink[EB/OL].http://www.mathworks.cn/products/simulink/description1.html
[100] Lin W B, Chiang H K, Yeh C H. Sensorless vector control of synchronousreluctance motor with extended kalman filter[J]. ICIC Express Letters,2013,7(6):1773-1779
[101] Dhaouadi R, Mohan N, Norum L. Design and implementation of an extendedKalman filter for the state estimation of a permanent magnet synchronous motor[J].IEEE Transactions on Power Electronics,1991,6(3):491-497
[102] Chbeb A, Jemli M, Boussak M, et al. Sensorless speed control of permanentmagnet synchronous motor drive using extended kalman filter with initial rotorposition estimation[J]. Journal of Electrical Systems,2009,5(2):1-19
[103] Jetto L, Longhi S, Venturini G. Development and experimental validation of anadaptive extended Kalman filter for the localization of mobile robots[J]. IEEETransactions on Robotics and Automation,1999,15(2):219-229
[104] Ciabattoni L, Corradini M L, Grisostomi M, et al. Adaptive extended kalmanfilter for robust sensorless control of PMSM drives[A]. Proceedings of the50thIEEE Conference on Decision and Control[C],2011:934-939
[105] Stirban A, Boldea I, Andreescu G-D, et al. Motion sensorless control of BLDCPM motor with offline FEM info assisted state observer[A]. Proceedings of theInternational Conference on Optimisation of Electrical and Electronic Equipment[C],2010:321-328
[106] Jiang D, Lai R, Wang F, et al. Start-up Transient Improvement for SensorlessControl Approach of PM Motor[A]. Conference Proceedings-IEEE Applied PowerElectronics Conference and Exposition[C],2010:408-413
[107] Bolognani S, Zigliotto M, Zordan M. Extended-range PMSM sensorless speeddrive based on stochastic filtering[J]. IEEE Transactions on Power Electronics,2001,16(1):110-117
[108] Bolognani S, Tubiana L, Zigliotto M. Extended Kalman filter tuning insensorless PMSM drives[J]. IEEE Transactions on Industry Applications,2003,39(6):1741-1747
[109]杨柳庆,肖前贵,牛妍,等.基于渐消卡尔曼滤波器的定位系统设计[J].南京航空航天大学学报,2012,44(1):134-138
[110]徐定杰,贺瑞,沈锋, et al.基于新息协方差的自适应渐消卡尔曼滤波器[J].系统工程与电子技术,2011,33(12):2696-2699
[111] Liu K, Zhu Z Q, Stone D A. Parameter estimation for condition monitoring ofPMSM stator winding and rotor permanent magnets[J]. IEEE Transactions onIndustrial Electronics,2013,60(12):5902-5913
[112] Nahid-Mobarakeh B, Meibody-Tabar F, Sargos F-M. Mechanical sensorlesscontrol of PMSM with online estimation of stator resistance[J]. IEEE Transactions onIndustry Applications,2004,40(2):457-471
[113] Karanayil B, Rahman M F, Grantham C. Online stator and rotor resistanceestimation scheme using artificial neural networks for vector controlled speedsensorless induction motor drive[J]. IEEE Transactions on Industrial Electronics,2007,54(1):167-176
[114] Shi Y, Sun K, Ma H, et al. Permanent magnet flux identification of IPMSMbased on EKF with speed sensorless control[A]. IECON2010Proceedings[C],2010:2252-2257
[115]周东华,席裕庚,张钟俊.非线性系统带次优渐消因子的扩展卡尔曼滤波[J].控制与决策,1990,5(05):1-6
[116]周东华,席裕庚,张钟俊.一种带多重次优渐消因子的扩展卡尔曼滤波器[J].自动化学报,1991,17(06):689-695,758
[117] Reif K, Gunther S, Yaz E, et al. Stochastic stability of the discrete-timeextended Kalman filter[J]. IEEE Transactions on Automatic Control,1999,44(4):714-728
[118] Friedland B. Treatment of bias in recursive filtering[J]. IEEE Transactions onAutomatic Control,1969,14(4):359-367
[119] Hsieh C-S, Chen F-C. Optimal solution of the two-stage Kalman estimator[J].IEEE Transactions on Automatic Control,1999,44(1):194-199
[120] Mendel J. Extension of Friedland's bias filtering technique to a class ofnonlinear systems[J]. IEEE Transactions on Automatic Control,1976,21(2):296-298
[121] Hsieh C-S. General two-stage extended Kalman filters[J]. IEEE Transactions onAutomatic Control,2003,48(2):289-293
[122] Hilairet M, Auger F, Berthelot E. Speed and rotor flux estimation of inductionmachines using a two-stage extended Kalman filter[J]. Automatica,2009,45(8):1819-1827
[123]王伟华,肖曦.永磁同步电机高动态响应电流控制方法研究[J].中国电机工程学报,2013,33(21):117-123+200
[124]王恩德,黄声华.表贴式永磁同步电机伺服系统电流环设计[J].中国电机工程学报,2012,32(33):82-88+179
[125] Kim H, Son J, Lee J. A High-Speed Sliding-Mode Observer for the SensorlessSpeed Control of a PMSM[J]. IEEE Transactions on Industrial Electronics,2011,58(9):4069-4077
[126] Boileau T, Leboeuf N, Nahid-Mobarakeh B, et al. Online Identification ofPMSM Parameters: Parameter Identifiability and Estimator Comparative Study[J].IEEE Transactions on Industry Applications,2011,47(4):1944-1957
[127] Zhu G, Dessaint L A, Akhrif O, et al. Speed tracking control of apermanent-magnet synchronous motor with state and load torque observer[J].Industrial Electronics, IEEE Transactions on,2000,47(2):346-355
[128] Rouche N, Habets P, Laloy M. Stability Theory by Liapunov's DirectMethod[M]. New York: Springer-Verlag,1979:1-80
[129]杨立永,张云龙,陈智刚.基于参数辨识的PMSM电流环在线自适应控制方法[J].电工技术学报,2012,27(03):86-91
[130]王新勇,许炜,汪显博,等.光伏并网逆变器固定开关频率控制策略的研究[J].电源技术,2011,35(4):443-445,448
[131]张文海.永磁直流力矩电机的阻尼和阻尼系数计算[J].微电机,2010,43(10):108-109
[132] Liu Y H, Chen C L. Novel dead time compensation method for induction motordrives using space vector modulation[J]. IEE Proceedings: Electric PowerApplications,1998,145(4):387-392
[133] Blaabjerg F, Pedersen J K, Thoegersen P. Improved modulation techniques forPWM-VSI drives[J]. IEEE Transactions on Industrial Electronics,1997,44(1):87-95
[134]王庆义,邓歆,罗慧,等.一种新的基于SVPWM策略的死区补偿方法[J].电气传动,2008,38(2):19-22,26
[135] Kim H S, Moon H T, Youn M J. On-line dead-time compensation method usingdisturbance observer[J]. IEEE Transactions on Power Electronics,2003,18(6):1336-1345
[136]顾卫钢.手把手教你学DSP:基于TMS320X281x[M].北京:北京航空航天大学出版社,2011:8-25
[137]杨光宇,高晓蓉,王黎,等.基于TI C6000系列DSP的C/C++程序优化技术[J].现代电子技术,2009,(08):56-59
[138]刁一平,赵晓群.基于TI C6000DSP的C/C++语言代码效率优化[J].微计算机应用,2007,28(05):544-548
[2]唐任远.现代永磁电机理论与设计[M].北京:机械工业出版社,1997:12-30
[3]谭立新.永磁同步电机在电梯系统中的应用分析[J].机械研究与应用,2011,(06):157-158
[4]姚晓明.简谈永磁同步电机在电梯技术上的应用[J].科技信息,2010,(28):750,752
[5]彭海涛,何志伟,余海阔.电动汽车用永磁同步电机的发展分析[J].微电机,2010,(06):78-81
[6]代颖,王立欣,崔淑梅.电动汽车用永磁同步电机评述[J].微电机(伺服技术),2005,(03):84-86
[7]杨克信.永磁材料在永磁电机中的应用探讨[J].上海大中型电机,2004,(04):26-30
[8]杨大伟.稀土永磁材料及电机发展概况[J].微电机,1994,(02):26-31
[9]闵琳,权利,莫会成.永磁材料和永磁电机[J].电气技术,2006,(07):14-16,20
[10]袁磊.浅谈电力电子的发展及未来展望[J].科技风,2008,(04):58
[11]李现兵,师宇杰,王广州,等.浅谈现代电力电子器件的发展[J].电力电子,2005,(03):23-26,44
[12]崔晶,张丽娜.现代电力电子及电源技术的发展趋势[J].科技信息(科学教研),2008,(09):28,9
[13]蔡宣三.电力电子器件的模块化与集成化[J].今日电子,2004,(09):39-40,42
[14]刘亚静,李铁才.电机数字控制器发展现状[J].伺服控制,2011,(08):25-28,32
[15]胡海兵.电力电子集成系统中的数字控制平台研究[D].浙江大学,2007
[16] Bester D D, du Toit J A, Enslin J H R. High performance DSP/FPGA controllerfor implementation of computationally intensive algorithms[A]. Proceedings of the1998International Symposium on Industrial Electronics[C],1998,1:240-244
[17]赵光宙,黄雷.交流传动的无速度传感器技术综述[J].电气应用,2008,(04):20-26
[18]张凌云,赖豪杰.先进控制理论及策略在电机控制中的应用[J].电机技术,2005,(02):39-42
[19] Morimoto M, Sumito K, Sato S, et al. High efficiency, unity power factor VVVFdrive system of an induction motor[J]. IEEE Transactions on Power Electronics,1991,6(3):498-503
[20] Chen S, Yeh S N. Optimal efficiency analysis of induction motors fed byvariable-voltage and variable-frequency source[J]. IEEE Transactions on EnergyConversion,1992,7(3):537-543
[21] F. B. The principle of field orientation as applied to the new Transvectorclosed-loop control system for rotating-field machines[R].1971
[22]王子辉.永磁同步电机全速度范围无位置传感器控制策略研究[D].杭州:浙江大学,2012
[23]尚喆.永磁同步电动机磁场定向控制的研究[D].杭州:浙江大学,2007
[24] Fazai R, Jalili-Kharaajoo M. High performance speed control of interiorpermanent magnet synchronous motors with maximum power factor operation[A].Proceedings of the200310th IEEE International Conference on Electronics, Circuitsand Systems.[C],2003,3:1125-1128
[25] Nakamura Y, Kudo T, Ishibashi F, et al. High-efficiency drive due to power factorcontrol of a permanent magnet synchronous motor[J]. IEEE Transactions on PowerElectronics,1995,10(2):247-253
[26] Inoue Y, Morimoto S, Sanada M. Comparative Study of PMSM Drive SystemsBased on Current Control and Direct Torque Control in Flux-Weakening ControlRegion[J]. IEEE Transactions on Industry Applications,2012,48(6):2382-2389
[27] Liu H, Zhu Z Q, Mohamed E, et al. Flux-Weakening Control of Nonsalient PolePMSM Having Large Winding Inductance, Accounting for Resistive Voltage Dropand Inverter Nonlinearities[J]. IEEE Transactions on Power Electronics,2012,27(2):942-952
[28] Sarikhani A, Mohammed O A. Demagnetization Control for Reliable FluxWeakening Control in PM Synchronous Machine[J]. IEEE Transactions on EnergyConversion,2012,27(4):1046-1055
[29] Zhao J, Liu W, Tan B. Research of maximum ratio of torque to current controlmethod for PMSM based on least square support vector machines[A]. Proceedings-International Conference on Electrical and Control Engineering[C],2010,10.1109/iCECE.2010.400:1623-1628
[30] Tahami F, Nademi H, Rezaei M. A high-performance vector-controlled PMSMdrive with maximum torque per ampere operation[A]. PECon2008-2008IEEE2ndInternational Power and Energy Conference[C],2008:254-258
[31] Zhao J, Liu W, Tan B. Research of maximum ratio of torque to current controlmethod for PMSM based on least square support vector machines[A]. Proceedings-International Conference on Electrical and Control Engineering2010[C],2010,10.1109/iCECE.2010.400:1623-1628
[32] Depenbrock M. Direkte selbstregelung (DSR) fur hochdynamischeDrehfeld-antriebe mit Stromrichterspeisung[J]. etz-Archiv,1985,7(7):211-218
[33] Takahashi I, Noguchi T. A New Quick-Response and High-Efficiency ControlStrategy of an Induction Motor[J]. IEEE Transactions on Industry Applications,1986,IA-22(5):820-827
[34] Faiz J, Mohseni-Zonoozi S H. A novel technique for estimation and control ofstator flux of a salient-pole PMSM in DTC method based on MTPF[J]. IEEETransactions on Industrial Electronics,2003,50(2):262-271
[35] Zhang Y, Zhu J, Xu W, et al. A Simple Method to Reduce Torque Ripple in DirectTorque-Controlled Permanent-Magnet Synchronous Motor by Using Vectors WithVariable Amplitude and Angle[J]. IEEE Transactions on Industrial Electronics,,2011,58(7):2848-2859
[36]周扬忠,胡育文,黄文新.低转矩磁链脉动型电励磁同步电机直接转矩驱动系统的研究[J].中国电机工程学报,2006,26(07):152-157
[37]李君,李毓洲.无速度传感器永磁同步电机的SVM-DTC控制[J].中国电机工程学报,2007,27(03):28-34
[38]苏成利.非线性模型预测控制的若干问题研究[D].杭州:浙江大学,2006
[39]席裕庚,李德伟,林姝.模型预测控制——现状与挑战[J].自动化学报,2013,39(03):222-236
[40]石宇静.复杂工业过程模型预测控制的研究[D].沈阳:东北大学,2009
[41]高丽媛.永磁同步电机的模型预测控制研究[D].杭州:浙江大学,2013
[42] Yu J, Teng Z, Zhang J, et al. Predictive current control and stability analysis ofactive power filter[J]. Diangong Jishu Xuebao/Transactions of China ElectrotechnicalSociety,2009,24(7):164-170
[43] Verne S A, Valla M I. Active power filter for medium voltage networks withpredictive current control[J]. Electric Power Systems Research,2010,80(12):1543-1551
[44] Moreno J C, Espi Huerta J M, Gil R G, et al. A robust predictive current controlfor three-phase grid-connected inverters[J]. IEEE Transactions on IndustrialElectronics,2009,56(6):1993-2004
[45] Moon G-W, Lee J-H, Youn M-J. Push-pull quantum series resonant rectifier withpredictive current control[J]. International Journal of Electronics,1995,79(3):363-377
[46] Xie Y, Ghaemi R, Sun J, et al. Model Predictive Control for a Full Bridge DC/DCConverter[J]. IEEE Transactions on Control Systems Technology,2012,20(1):164-172
[47] Quevedo D E, Aguilera R P, Perez M A, et al. Model Predictive Control of anAFE Rectifier With Dynamic References[J]. IEEE Transactions on Power Electronics,2012,27(7):3128-3136
[48] Barrero F, Prieto J, Levi E, et al. An enhanced predictive current control methodfor asymmetrical six-phase motor drives[J]. IEEE Transactions on IndustrialElectronics,2011,58(8):3242-3252
[49] Barrero F, Arahal M R, Gregor R, et al. One-step modulation predictive currentcontrol method for the asymmetrical dual three-phase induction machine[J]. IEEETransactions on Industrial Electronics,2009,56(6):1974-1983
[50] Mariethoz S, Domahidi A, Morari M. High-bandwidth explicit model predictivecontrol of electrical drives[J]. IEEE Transactions on Industry Applications,2012,48(6):1980-1992
[51] Dong L, Dou L, Chen J, et al. Hybrid model predictive control for speed controlof permanent magnet synchronous motor with saturation[J]. Journal of ControlTheory and Applications,2011,9(2):251-255
[52]席裕庚.预测控制[M].北京:国防工业出版社,1993:10-18
[53]舒迪前.预测控制系统及其应用[M].北京:机械工业出版社,1996:127-173
[54] Mohamed Y A R I. Design and Implementation of a Robust Current-ControlScheme for a PMSM Vector Drive With a Simple Adaptive Disturbance Observer[J].IEEE Transactions on Industrial Electronics,2007,54(4):1981-1988
[55]梁艳,李永东.无传感器永磁同步电机矢量控制系统概述[J].电气传动,2003,(04):4-9
[56] Suwankawin S, Sangwongwanich S. Design strategy of an adaptive full-orderobserver for speed-sensorless induction-motor Drives-tracking performance andstabilization[J]. IEEE Transactions on Industrial Electronics,2006,53(1):96-119
[57] Kubota K, Matsuse K, Nakano T. DSP-based speed adaptive flux observer ofinduction motor[J]. IEEE Transactions on Industry Applications,1993,29(2):344-348
[58] Kubota K, Sato I, Tamura Y, et al. Regenerating-mode low-speed operation ofsensorless induction motor drive with adaptive observer[J]. IEEE Transactions onIndustry Applications,2002,38(4):1081-1086
[59] Chan T F, Wang W, Borsje P, et al. Sensorless permanent-magnet synchronousmotor drive using a reduced-order rotor flux observer[J]. IET Electric PowerApplications,2008,2(2):88-98
[60] Hinkkanen M, Tuovinen T, Harnefors L, et al. A Combined Position andStator-Resistance Observer for Salient PMSM Drives: Design and StabilityAnalysis[J]. IEEE Transactions on Power Electronics,2012,27(2):601-609
[61]苏健勇,李铁才,杨贵杰. PMSM无位置传感器控制中数字滑模观测器抖振现象分析与抑制[J].电工技术学报,2009,24(08):58-64
[62]程帅,姜海博,黄进,等.基于滑模观测器的单绕组多相无轴承电机无位置传感器控制[J].电工技术学报,2012,27(07):71-77
[63] Utkin V, Lee H. Chattering Problem in Sliding Mode Control Systems[A].Proceedings of the2006International Workshop on Variable Structure System[C],2006,10.1109/VSS.2006.1644542:346-350
[64] Paponpen K, Konghirun M. An Improved Sliding Mode Observer for SpeedSensorless Vector Control Drive of PMSM[A]. Conference Proceedings-IPEMC2006: CES/IEEE5th International Power Electronics and Motion ControlConference[C],2006,2:1-5
[65] Li C, Elbuluk M. A robust sliding mode observer for permanent magnetsynchronous motor drives[A]. IECON Proceedings[C],2002,2:1014-1019
[66] Yu S H, Hu J S. Stability and performance of single-bit sigma-delta modulatorsoperated in quasi-sliding mode[J]. Circuits, Systems, and Signal Processing,2006,25(5):571-590
[67] Corradini M L, Ippoliti G, Longhi S, et al. A Quasi-Sliding Mode Approach forRobust Control and Speed Estimation of PM Synchronous Motors[J]. IEEETransactions on Industrial Electronics,2012,59(2):1096-1104
[68]高为炳,程勉.变结构控制系统的品质控制[J].控制与决策,1989,4(04):1-6
[69]高为炳.非线性系统的变结构控制[J].自动化学报,1989,15(05):408-415
[70]米阳,李文林,井元伟.基于幂次趋近律的一类离散时间系统的变结构控制[J].控制与决策,2008,23(06):643-646
[71]张巍巍,王京.基于指数趋近律的非奇异Terminal滑模控制[J].控制与决策,2012,27(06):909-913
[72]王静.基于无传感器的电动汽车电机控制技术研究[D].广州:华南理工大学,2012
[73]刘英培,万健如,梁鹏飞.基于扩展卡尔曼滤波器和空间电压矢量调制的永磁同步电机直接转矩控制[J].中国电机工程学报,2009,29(27):67-74
[74]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
[75]尹忠刚,赵昌,钟彦儒,等.采用抗差扩展卡尔曼滤波器的感应电机转速估计方法[J].中国电机工程学报,2012,32(18):152-159,190
[76] Szabat K, Orlowska-Kowalska T, Dyrcz K P. Extended Kalman filters in thecontrol structure of two-mass drive system[J]. Bulletin of the Polish Academy ofSciences: Technical Sciences,2006,54(3):315-325
[77] Orlowska-Kowalska T, Szabat K. Neural-Network application for mechanicalvariables estimation of a two-mass drive system[J]. IEEE Transactions on IndustrialElectronics,2007,54(3):1352-1364
[78] Dah-Jing J, Sheng-Hung W. Adaptive Fuzzy Strong Tracking Extended KalmanFiltering for GPS Navigation[J]. IEEE Sensors Journal,2007,7(5):778-789
[79] Soken H E, Hajiyev C. Adaptive Unscented Kalman Filter with multiple fadingfactors for pico satellite attitude estimation[A]. Proceedings of4th InternationalConference on Recent Advances Space Technologies[C],2009,10.1109/RAST.2009.5158254:541-546
[80]王庆龙.交流电机矢量控制系统滑模变结构控制策略研究[D].合肥:合肥工业大学,2007
[81] Khlaief A, Boussak M, Chaari A. A MRAS-based stator resistance and speedestimation for sensorless vector controlled IPMSM drive[J]. Electric Power SystemsResearch,2014,1081-15
[82] Piippo A, Hinkkanen M, Luomi J. Analysis of an Adaptive Observer forSensorless Control of Interior Permanent Magnet Synchronous Motors[J]. IEEETransactions on Industrial Electronics,2008,55(2):570-576
[83] Limei W, Lorenz R D. Rotor position estimation for permanent magnetsynchronous motor using saliency-tracking self-sensing method[A]. Proceedings ofIEEE35th IAS Annual Meeting[C],2000,1:445-450vol.1
[84] Jansen P L, Lorenz R D. Transducerless field orientation concepts employingsaturation-induced saliencies in induction machines[J]. IEEE Transactions on IndustryApplications,1996,32(6):1380-1393
[85] Noguchi T, Takehana K, Kondo S. Mechanical-sensorless robust control ofpermanent magnet synchronous motor using phase information of harmonic reactivepower[A]. Conference Record-IAS Annual Meeting[C],2000,3:1781-1786
[86] Jang J-H, Sul S-K, Ha J-I, et al. Sensorless drive of surface-mountedpermanent-magnet motor by high-frequency signal injection based on magneticsaliency[J]. IEEE Transactions on Industry Applications,2003,39(4):1031-1039
[87] Zhou Y, Cui Y, Wang X, et al. Technique on fuzzy sliding mode observer forpermanent magnet synchronous motor (PMSM) sensorless detection[J]. Journal ofHarbin Engineering University,2013,34(6):728-733
[88] Gumus B, Ozdemir M. Sensorless vector control of a Permanent magnetsynchronuous motor with fuzzy logic observer[J]. Electrical Engineering,2006,88(5):395-402
[89] Mese E, Torrey D A. An approach for sensorless position estimation for switchedreluctance motors using artificial neural networks[J]. IEEE Transactions on PowerElectronics,2002,17(1):66-75
[90] Heredia J R, Hidalgo F P, Duran Paz J L. Sensorless control of induction motorsby artificial neural networks[J]. IEEE Transactions on Industrial Electronics,2001,48(5):1038-1040
[91] Garcia P, Briz F, Raca D, et al. Saliency-tracking-based sensorless control of acmachines using structured neural networks[J]. IEEE Transactions on IndustryApplications,2007,43(1):77-86
[92] Chaoui H, Sicard P. Adaptive Lyapunov-based neural network sensorless controlof permanent magnet synchronous machines[J]. Neural Computing and Applications,2011,20(5):717-727
[93] Seong-Hwan K, Tae-Sik P, Ji-Yoon Y, et al. Speed-sensorless vector control of aninduction motor using neural network speed estimation[J]. IEEE Transactions onIndustrial Electronics,2001,48(3):609-614
[94] Batzel T D, Lee K Y. An approach to sensorless operation of thepermanent-magnet synchronous motor using diagonally recurrent neural networks[J].IEEE Transactions on Energy Conversion,2003,18(1):100-106
[95]张嗣瀛,高立群.现代控制理论[M].北京:清华大学出版社,2006:91-95
[96]刘豹,唐万生.现代控制理论[M].北京:机械工业出版社,2011:1-80
[97]肖春燕.电压空间矢量脉宽调制技术的研究及其实现[D].南昌:南昌大学,2005
[98] Grewal M S, Andrews A P. Kalman Filtering: Theory and Practice UsingMATLAB[M]. Hoboken: Wiley-IEEE Press,2001:169-182
[99] Mathworks. Simulink[EB/OL].http://www.mathworks.cn/products/simulink/description1.html
[100] Lin W B, Chiang H K, Yeh C H. Sensorless vector control of synchronousreluctance motor with extended kalman filter[J]. ICIC Express Letters,2013,7(6):1773-1779
[101] Dhaouadi R, Mohan N, Norum L. Design and implementation of an extendedKalman filter for the state estimation of a permanent magnet synchronous motor[J].IEEE Transactions on Power Electronics,1991,6(3):491-497
[102] Chbeb A, Jemli M, Boussak M, et al. Sensorless speed control of permanentmagnet synchronous motor drive using extended kalman filter with initial rotorposition estimation[J]. Journal of Electrical Systems,2009,5(2):1-19
[103] Jetto L, Longhi S, Venturini G. Development and experimental validation of anadaptive extended Kalman filter for the localization of mobile robots[J]. IEEETransactions on Robotics and Automation,1999,15(2):219-229
[104] Ciabattoni L, Corradini M L, Grisostomi M, et al. Adaptive extended kalmanfilter for robust sensorless control of PMSM drives[A]. Proceedings of the50thIEEE Conference on Decision and Control[C],2011:934-939
[105] Stirban A, Boldea I, Andreescu G-D, et al. Motion sensorless control of BLDCPM motor with offline FEM info assisted state observer[A]. Proceedings of theInternational Conference on Optimisation of Electrical and Electronic Equipment[C],2010:321-328
[106] Jiang D, Lai R, Wang F, et al. Start-up Transient Improvement for SensorlessControl Approach of PM Motor[A]. Conference Proceedings-IEEE Applied PowerElectronics Conference and Exposition[C],2010:408-413
[107] Bolognani S, Zigliotto M, Zordan M. Extended-range PMSM sensorless speeddrive based on stochastic filtering[J]. IEEE Transactions on Power Electronics,2001,16(1):110-117
[108] Bolognani S, Tubiana L, Zigliotto M. Extended Kalman filter tuning insensorless PMSM drives[J]. IEEE Transactions on Industry Applications,2003,39(6):1741-1747
[109]杨柳庆,肖前贵,牛妍,等.基于渐消卡尔曼滤波器的定位系统设计[J].南京航空航天大学学报,2012,44(1):134-138
[110]徐定杰,贺瑞,沈锋, et al.基于新息协方差的自适应渐消卡尔曼滤波器[J].系统工程与电子技术,2011,33(12):2696-2699
[111] Liu K, Zhu Z Q, Stone D A. Parameter estimation for condition monitoring ofPMSM stator winding and rotor permanent magnets[J]. IEEE Transactions onIndustrial Electronics,2013,60(12):5902-5913
[112] Nahid-Mobarakeh B, Meibody-Tabar F, Sargos F-M. Mechanical sensorlesscontrol of PMSM with online estimation of stator resistance[J]. IEEE Transactions onIndustry Applications,2004,40(2):457-471
[113] Karanayil B, Rahman M F, Grantham C. Online stator and rotor resistanceestimation scheme using artificial neural networks for vector controlled speedsensorless induction motor drive[J]. IEEE Transactions on Industrial Electronics,2007,54(1):167-176
[114] Shi Y, Sun K, Ma H, et al. Permanent magnet flux identification of IPMSMbased on EKF with speed sensorless control[A]. IECON2010Proceedings[C],2010:2252-2257
[115]周东华,席裕庚,张钟俊.非线性系统带次优渐消因子的扩展卡尔曼滤波[J].控制与决策,1990,5(05):1-6
[116]周东华,席裕庚,张钟俊.一种带多重次优渐消因子的扩展卡尔曼滤波器[J].自动化学报,1991,17(06):689-695,758
[117] Reif K, Gunther S, Yaz E, et al. Stochastic stability of the discrete-timeextended Kalman filter[J]. IEEE Transactions on Automatic Control,1999,44(4):714-728
[118] Friedland B. Treatment of bias in recursive filtering[J]. IEEE Transactions onAutomatic Control,1969,14(4):359-367
[119] Hsieh C-S, Chen F-C. Optimal solution of the two-stage Kalman estimator[J].IEEE Transactions on Automatic Control,1999,44(1):194-199
[120] Mendel J. Extension of Friedland's bias filtering technique to a class ofnonlinear systems[J]. IEEE Transactions on Automatic Control,1976,21(2):296-298
[121] Hsieh C-S. General two-stage extended Kalman filters[J]. IEEE Transactions onAutomatic Control,2003,48(2):289-293
[122] Hilairet M, Auger F, Berthelot E. Speed and rotor flux estimation of inductionmachines using a two-stage extended Kalman filter[J]. Automatica,2009,45(8):1819-1827
[123]王伟华,肖曦.永磁同步电机高动态响应电流控制方法研究[J].中国电机工程学报,2013,33(21):117-123+200
[124]王恩德,黄声华.表贴式永磁同步电机伺服系统电流环设计[J].中国电机工程学报,2012,32(33):82-88+179
[125] Kim H, Son J, Lee J. A High-Speed Sliding-Mode Observer for the SensorlessSpeed Control of a PMSM[J]. IEEE Transactions on Industrial Electronics,2011,58(9):4069-4077
[126] Boileau T, Leboeuf N, Nahid-Mobarakeh B, et al. Online Identification ofPMSM Parameters: Parameter Identifiability and Estimator Comparative Study[J].IEEE Transactions on Industry Applications,2011,47(4):1944-1957
[127] Zhu G, Dessaint L A, Akhrif O, et al. Speed tracking control of apermanent-magnet synchronous motor with state and load torque observer[J].Industrial Electronics, IEEE Transactions on,2000,47(2):346-355
[128] Rouche N, Habets P, Laloy M. Stability Theory by Liapunov's DirectMethod[M]. New York: Springer-Verlag,1979:1-80
[129]杨立永,张云龙,陈智刚.基于参数辨识的PMSM电流环在线自适应控制方法[J].电工技术学报,2012,27(03):86-91
[130]王新勇,许炜,汪显博,等.光伏并网逆变器固定开关频率控制策略的研究[J].电源技术,2011,35(4):443-445,448
[131]张文海.永磁直流力矩电机的阻尼和阻尼系数计算[J].微电机,2010,43(10):108-109
[132] Liu Y H, Chen C L. Novel dead time compensation method for induction motordrives using space vector modulation[J]. IEE Proceedings: Electric PowerApplications,1998,145(4):387-392
[133] Blaabjerg F, Pedersen J K, Thoegersen P. Improved modulation techniques forPWM-VSI drives[J]. IEEE Transactions on Industrial Electronics,1997,44(1):87-95
[134]王庆义,邓歆,罗慧,等.一种新的基于SVPWM策略的死区补偿方法[J].电气传动,2008,38(2):19-22,26
[135] Kim H S, Moon H T, Youn M J. On-line dead-time compensation method usingdisturbance observer[J]. IEEE Transactions on Power Electronics,2003,18(6):1336-1345
[136]顾卫钢.手把手教你学DSP:基于TMS320X281x[M].北京:北京航空航天大学出版社,2011:8-25
[137]杨光宇,高晓蓉,王黎,等.基于TI C6000系列DSP的C/C++程序优化技术[J].现代电子技术,2009,(08):56-59
[138]刁一平,赵晓群.基于TI C6000DSP的C/C++语言代码效率优化[J].微计算机应用,2007,28(05):544-548