异步电机矢量控制系统参数自提交自适应问题研究
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摘要
矢量控制由于实现了励磁电流和转矩电流的解耦控制,而具有优良的动态性能。为了提高矢量控制系统的控制性能,提高系统对参数变化的鲁棒性,需要对电机参数进行离线和在线的辨识。本文将探讨如何在实验平台上实现矢量控制系统的参数自提交和转子电阻自适应,并对其参数辨识性能进行详细的研究。
首先介绍了三相异步电机的数学模型,详细阐述了异步电机参数自提交和转子电阻自适应的原理和方法。对自提交算法进行了仿真分析,验证了该方案的正确性和可行性。选择TMS320F2812 DSP为系统的控制芯片,设计了硬件控制电路,根据自提交控制算法和硬件电路,编写软件。研究了基于空间电压矢量的PWM控制方法,实现了VVVF电机控制算法。对采样电流进行FIR数字滤波处理,同时分析了死区时间和管压降对辨识结果的影响,进行了简单的补偿,提高了参数辨识的精度。实验结果表明该自提交算法具有较高的辨识精度。通过对不同容量电机进行辨识,进一步验证了该方法的正确性。
提出了一种新型的基于模型参考自适应的转子电阻在线辨识方法,该方法的辨识结果不受定子电阻的影响。将其与另外两种模型参考自适应(MRAS)辨识方法进行仿真对比,结果表明该方法具有动态性能好、鲁棒性强和受转矩和转速影响小等特点。并在多种工况下对该方法进行了细致的仿真分析,最后在DSP开发环境中编写软件实现该算法。仿真和实验结果表明该方法具有较高的稳态精度和较快的收敛速度,验证了该方案的正确性、可行性。
By decoupling between magnetizing current and torque current, the vector control strategy of induction machines can achieve excellent dynamic performances. In order to achieve high-performance vector control system and improve the robustness of the system, it is needed to identify the motor parameters. This paper will explore how to achieve high performance vector control system on experimental platform with motor parameters self-commission and adaptive, and with detailed study of the parameter identification performance.
Three-phase asynchronous motor mathematic model is first introduced. The principles and methods of motor parameters self-commission and rotor resistance adaptive are elaborated.The simulation analysis of parameter self-commission algorithm verificats the correctness and feasibility of this method. TMS320F2812 DSP is selected for control chip of the system, the hardware circuit is designed. The Software is composed according to the control algorithm and the hardware circuit. Space vector PWM control method is studied, and VVVF motor control algorithm is achieved. The FIR digital filter is design to filter sampling current , and mean while the influence of dead time and voltage drop on identification is analysed. A simple compensation is implemented which improves the accuracy of the parameter identification. Experimental results show that the self-commission algorithm has a high accuracy of the identification. The identification of different motors further verifies the validity of the method.
This paper proposes a new method of rotor resistance online identification. The identification result is not affected by stator resistance. At the same time, the other two identification methods of model reference adaptive system (MRAS) are compared, simulation results show that this method has a good dynamic performance, robustness and affected small by torque and speed. A detailed simulation analysis of this method is carried out in a variety of conditions, and the algorithm is finally achieved in DSP. Simulation and experimental results show that the method has a high steady-state accuracy and fast speed of convergence, the programme has verified the correctness and feasibility of this method.
首先介绍了三相异步电机的数学模型,详细阐述了异步电机参数自提交和转子电阻自适应的原理和方法。对自提交算法进行了仿真分析,验证了该方案的正确性和可行性。选择TMS320F2812 DSP为系统的控制芯片,设计了硬件控制电路,根据自提交控制算法和硬件电路,编写软件。研究了基于空间电压矢量的PWM控制方法,实现了VVVF电机控制算法。对采样电流进行FIR数字滤波处理,同时分析了死区时间和管压降对辨识结果的影响,进行了简单的补偿,提高了参数辨识的精度。实验结果表明该自提交算法具有较高的辨识精度。通过对不同容量电机进行辨识,进一步验证了该方法的正确性。
提出了一种新型的基于模型参考自适应的转子电阻在线辨识方法,该方法的辨识结果不受定子电阻的影响。将其与另外两种模型参考自适应(MRAS)辨识方法进行仿真对比,结果表明该方法具有动态性能好、鲁棒性强和受转矩和转速影响小等特点。并在多种工况下对该方法进行了细致的仿真分析,最后在DSP开发环境中编写软件实现该算法。仿真和实验结果表明该方法具有较高的稳态精度和较快的收敛速度,验证了该方案的正确性、可行性。
By decoupling between magnetizing current and torque current, the vector control strategy of induction machines can achieve excellent dynamic performances. In order to achieve high-performance vector control system and improve the robustness of the system, it is needed to identify the motor parameters. This paper will explore how to achieve high performance vector control system on experimental platform with motor parameters self-commission and adaptive, and with detailed study of the parameter identification performance.
Three-phase asynchronous motor mathematic model is first introduced. The principles and methods of motor parameters self-commission and rotor resistance adaptive are elaborated.The simulation analysis of parameter self-commission algorithm verificats the correctness and feasibility of this method. TMS320F2812 DSP is selected for control chip of the system, the hardware circuit is designed. The Software is composed according to the control algorithm and the hardware circuit. Space vector PWM control method is studied, and VVVF motor control algorithm is achieved. The FIR digital filter is design to filter sampling current , and mean while the influence of dead time and voltage drop on identification is analysed. A simple compensation is implemented which improves the accuracy of the parameter identification. Experimental results show that the self-commission algorithm has a high accuracy of the identification. The identification of different motors further verifies the validity of the method.
This paper proposes a new method of rotor resistance online identification. The identification result is not affected by stator resistance. At the same time, the other two identification methods of model reference adaptive system (MRAS) are compared, simulation results show that this method has a good dynamic performance, robustness and affected small by torque and speed. A detailed simulation analysis of this method is carried out in a variety of conditions, and the algorithm is finally achieved in DSP. Simulation and experimental results show that the method has a high steady-state accuracy and fast speed of convergence, the programme has verified the correctness and feasibility of this method.
引文
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[29]Luiz Antonio de Souza Rubeiro,Cursino Brandao Jacobina Antonio Marcus Nogueira Lima Alexandre Cunha Oliveira.Real-Time Estimation of the Electric Parameters of an Induction Machine Using Sinusoidal PWM Voltage Waveforms[C].Thirty-Second IAS Annual Meeting,IAS apos 97.,Conference Record of the 1997 IEEE Vol.1,5-9 Oct 1997.Page(s):746-752.
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[36]陈伟,瞿文龙,陆海峰.一种基于M RAS的异步电机速度辨识方法[J].北京:《电工电能新技术》,2006第25卷第2期,2006.4。
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[2]Jehudi Maes,Jan A.Melkebeek.Speed-sensorless direct torque control of induction motors using an adaptive flux observer[J].IEEE Transactions on industry application,Vol.36,No.3,May/June 2000.Page(s):778-785.
[3]冯垛生,曾岳南编著.无速度传感器矢量控制原理与实践.北京:机械工业出版社,2001。
[4]陈伯时.电力拖动自动控制系统[M].北京:机械工业出版社,1997。
[5]夏超英.交直流传动系统的自适应控制[M].北京:机械工业出版社,2001。
[6]陈伯时,陈敏逊.交流调速系统[M].北京:机械工业出版社,1999。
[7]王兆安,黄俊.电力电子技术[M].北京:机械工业出版社,2000。
[8]李永东.交流电机数字控制系统[M].北京:机械工业出版社,2002。
[9]G.Narayanan and V.T.Ranganathan.Synchronised PWM strategies based on space vector approach.Part2:Performance assessment and application to V/F drives[C].IEE Proceedings-Electric Power Applications,Vol.146,Issue 3,May 1999.Page(s):276-281.
[10]C.Lascu,LBoldea and F.Blaabje.A modified direct torque control(DTC)for induction motor sensorless drive[J].IEEE Transactions on Industry Applications,Vol.36,Issue 1,Jan/Feb 2000.Page(s):122-130.
[11]黄斌.异步电机直接矢量控制开发与转子电阻辨识方法研究[D].北京:清华大学工学硕士学位论文,2004.6。
[12]李发海,王岩,电机与拖动基础[M],北京:清华大学出版社,2003.6。
[13]余功军.感应电动机的无速度传感器矢量控制若干问题研究[D].西安:西安理工大学博士学位论文,1999年。
[14]许镇琳,何启莲,李国民,王秀芝,马小亮.异步机矢量控制系统的电机参数自设定[J].北京:《电工技术学报》,1995年第1期,1995.2。
[15]王明渝,冼成瑜,惠娅倩.感应电动机矢量控制参数离线辨识技术[J].北京:《电工技术学报》,2006年第21卷第8期,2006.8。
[16]刘宏鑫,张科孟,王玉雷,异步电机参数辨识方法发明专利公开说明书[P],公开号:CNl354557A,2002.6
[17]Jens Godberson.A Stand-Still Method for Estimating the Rotor Resistance of Induction Motors[C].Thirty-Fourth IAS Annual Meeting,Industry Applications Conference,Vol.2,1999.Page(s):900-905.
[18]H.Schierling.Self-commissioning-A Novel Feature of Modem Inverter-Fed Induction Motor Drives [J].Power Electronics and Variable-Speed Drives,13-15 Jul 1988.Page(s):287-290.
[19]M.Cirrincione,M.Pucci,G.Vitale.A Least-Squares Based Methodology for Estimating the Electrical Parameter of Induction Machine at Standstill[C].Proceedings of the 2002 IEEE International Symposium on Industrial Electronics,Vol.2,2002.Page(s):541-547.
[20]李建军,盛洁波,王翠,桂卫华.异步电机定转子参数的辨识方法研究[J].北京:《电工技术学报》,2006第21卷第1期,2006.1。
[21]韩林.电机参数检测与辨识[D].杭州:浙江大学硕士学位论文,2004.3。
[22]Kaiyu Wang,John Chiasson,Marc Bodson and Leon M.Tolbert.A Nonlinear Least-Squares Approach for Identification of the Induction Motor Parameters[J].IEEE Transactions on Automatic Control,Vol.50,Issue 10,Oct.2005 Page(s):1622-1628.
[23]A.Dell'Aquila,V.Giliberti,F.S.Lovecchio,L.Salvatore.Real-time Estimation of Induction Motor Parameter by LSE[C].20th International conference on Industrial Electronics Control and Instrumentation Vol.3,5-9 Sep.1994.Page(s):2127-2131o
[24]F.Alonge,F.D'Ippolito,S.La Barbera F.M.Raimondi.Parameter Identification of a Mathmatical Model of Induction Motors Via Least Square Technics[C].Proceedings of the 1998 IEEE International Conference on Control Applications,Vol.1,1-4 Sep.1998.Page(s):491-496.
[25]Li-Cheng zai,Christopher L.DeMacro,Thomas A.Lipo,An Extended Kalman Filter Approach to Rotor Time Constant Measurement in PWM Induction Motor Drives[J],IEEE Transactions on Industry Applications,Vol.28,Jan/Feb 1992.Page(s):96-104.
[26]Mohamed Menaa,Omar Touhami,Richid Ibtiouen.Estimation of Rotor Resistance of an Induction Motor Using Extended Kalman Filter and Spiral Vector Theory[C].Proceedings of 2003 IEEE Conference on Control Applications,2003.Vol.2,23-25 June 2003.Page(s):1262-1266.
[27]David J.Atkinson,Paul P.Acarnley,John W.Finch.Observers for Induction Motor State and Parameter Estimation[J].IEEE Transaction on Industry Application,Vol.27,No.6,November/December 1991.Page(s):1119-1127.
[28]Zein Ismail,Loron Luc,Forgez Christophe.An Extended Kalman Filter and an Appropriate Model for the Real-time Estimation of the Induction Motor Variables and Parameters[J].IEEE Transaction on Industry Applications,Vol.36,No.4,May/June 2000.
[29]Luiz Antonio de Souza Rubeiro,Cursino Brandao Jacobina Antonio Marcus Nogueira Lima Alexandre Cunha Oliveira.Real-Time Estimation of the Electric Parameters of an Induction Machine Using Sinusoidal PWM Voltage Waveforms[C].Thirty-Second IAS Annual Meeting,IAS apos 97.,Conference Record of the 1997 IEEE Vol.1,5-9 Oct 1997.Page(s):746-752.
[30]汪镭,周兴国,吴启迪.基于Hopfield神经网络的线性系统参数辨识方案及在鼠笼式电机传动系统参数辨识中的应用研究[J].北京:《中国电机工程学报》,2001年第21卷第1期,2001.1。
[31]K.S.Huang,Q.H.Wu,D.R.Turner.Effective Identification of Induction Motor Parameter Based on Fewer Measurements[J].IEEE Transactions on Enengy Conversion,Vo1.17,No.1,March 2002.Page(s):55-60.
[32]Hisao Kubota,Daisuke Youshihara,Kouki Matsuse.Rotor Resistance Adaptation for Sensorless Vector-Controlled Induction Machines[J].Electrical Engineering in Japan,Vol.125,No.2,1998. Page(s):65-72.
[33]Li Zhen,Longya Xu.Sensodess Field Orientation Control of Induction Machines Based on a Mutual MRAS Scheme[J].Transactions on Industrial Electronics,IEEE Vol.45,Issue 5,Oct 1998 Page(s):824-831.
[34]Habib-ur Rehman,Adnan Derdiyok,Mustafa K.Guven,Ongya Xu..An MRAS Scheme for On-line Rotor Resistance Adaptation of an Induction Machine[C].2001 IEEE 32nd Annual Power Electronics Specialists Conference,Vol.2.2001.PESC.Page(s):817-822.
[35]Hisao Kubota,Kouki Matsuse.Speed Sensorless Field-Oriented Control of Induction Motor with Rotor Resistance Adaptation[J].IEEE Transaction on Industry Applications,Vol.30,No.5,September/October 1994.Page(s):414-418.
[36]陈伟,瞿文龙,陆海峰.一种基于M RAS的异步电机速度辨识方法[J].北京:《电工电能新技术》,2006第25卷第2期,2006.4。
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