全数字电主轴交流调速系统的研究
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摘要
本论文的主要工作围绕研制高性能、宽调速永磁同步电动机的全数字交流控制系统为工程背景展开，对控制系统的体系结构、提高控制系统精度与性能的控制方法、以及软硬件设计等问题进行了研究。
传统的矢量控制算法是建立在电动机数学模型的基础上的，系统的控制性能往往受模型的精确程度和电动机的参数影响较大。本论文在人工神经网络控制理论的基础上，针对永磁同步电动机矢量控制系统，构造实现最大转矩／电流控制的MIMO神经网络PID速度控制器。提出永磁同步电动机的NARMA神经网络电流控制器，并以神经网络速度控制器和NARMA电流控制器构成电动机矢量控制系统。通过大量仿真和实验表明，本系统不仅具有较好的动态和稳态性能，而且避免了系统的数学模型、电动机参数变化等因素的不良影响，有很好的自适应性和鲁棒性。
本文提出了一种利用数理统计中的相关性理论对神经网络的输入量进行选择的新方法。通过其相关系数绝对值的大小来判断该输入量与输出量的相关程度，进而对其进行取舍。该方法不仅可以提高神经网络数学模型的准确度，而且还有效的减小模型的复杂性。
为完成该863课题，通过对以永磁同步电动机为执行元件的机床电主轴系统的数学模型的分析，提出了基于工业用控制计算机的永磁同步电动机全数字式机床电主轴系统的硬件和软件实现方案。针对本课题要求宽调速范围的特点，设计了一个两档倍频电路。它能够根据指令实时的对编码器反馈回来的电机速度信号进行2倍频或4倍频处理，解决了用同一个编码器来检测电机低速和高速的矛盾。试验结果证明了有效性。
The researches of this thesis are carried out around the study and development of adjustable speed digital drive system of permanent magnet synchronous motor (PMSM) with wide range of variable speed and high performance, including the analysis of the system structure, the intelligent control method and the design of the system.
First of all, conventional vector control algorithm is dependent on the mathematical model of motor. Thus, the control performance of system is influenced to a great extent by the model precision and the parameters of motor. Based on artificial neutral network control theory, a MIMO neutral network PID speed regulator realizing the maximum torque with minimum current is conformed for a PMSM drive system. NARMA (Nonlinear
Autoregressive Moving Average) neutral network current controller of PMSM is proposed and it in company with neutral network speed regulator composes the PMSM vector control system. A number of simulation and experiments show that the system not only has good performance both in dynamic and steady state but also avoids the adverse effect
resulted from the inaccurate mathematical model and the parameter changes of the PMSM. Therefore, the system possesses a good self-adapting and robust.
The paper presents a new method of how to select the neural input variables by the correlation coefficient of mathematical statistics. According to the absolute value of correlation coefficient, the degree of correlation between input and output variables can be estimated and selected or not, which not only increases the neural network mathematical model accuracy, but also reduces the complexity.
For the accomplishment of the national 863-advanced project, the industry control computer is used as main control unite and the PWSM machine tools spindle drive system. The hardware and software of the system is studied and developed. Basing on the operating characteristics of the PMSM machine tool spindle drive system, a novel frequency multiplication circuits which can be switch to 2 or 4 times of base frequency is proposed in the paper. It resolves the paradox of using a same photoelectric encoder under high and low speed operating condition of motors.
传统的矢量控制算法是建立在电动机数学模型的基础上的，系统的控制性能往往受模型的精确程度和电动机的参数影响较大。本论文在人工神经网络控制理论的基础上，针对永磁同步电动机矢量控制系统，构造实现最大转矩／电流控制的MIMO神经网络PID速度控制器。提出永磁同步电动机的NARMA神经网络电流控制器，并以神经网络速度控制器和NARMA电流控制器构成电动机矢量控制系统。通过大量仿真和实验表明，本系统不仅具有较好的动态和稳态性能，而且避免了系统的数学模型、电动机参数变化等因素的不良影响，有很好的自适应性和鲁棒性。
本文提出了一种利用数理统计中的相关性理论对神经网络的输入量进行选择的新方法。通过其相关系数绝对值的大小来判断该输入量与输出量的相关程度，进而对其进行取舍。该方法不仅可以提高神经网络数学模型的准确度，而且还有效的减小模型的复杂性。
为完成该863课题，通过对以永磁同步电动机为执行元件的机床电主轴系统的数学模型的分析，提出了基于工业用控制计算机的永磁同步电动机全数字式机床电主轴系统的硬件和软件实现方案。针对本课题要求宽调速范围的特点，设计了一个两档倍频电路。它能够根据指令实时的对编码器反馈回来的电机速度信号进行2倍频或4倍频处理，解决了用同一个编码器来检测电机低速和高速的矛盾。试验结果证明了有效性。
The researches of this thesis are carried out around the study and development of adjustable speed digital drive system of permanent magnet synchronous motor (PMSM) with wide range of variable speed and high performance, including the analysis of the system structure, the intelligent control method and the design of the system.
First of all, conventional vector control algorithm is dependent on the mathematical model of motor. Thus, the control performance of system is influenced to a great extent by the model precision and the parameters of motor. Based on artificial neutral network control theory, a MIMO neutral network PID speed regulator realizing the maximum torque with minimum current is conformed for a PMSM drive system. NARMA (Nonlinear
Autoregressive Moving Average) neutral network current controller of PMSM is proposed and it in company with neutral network speed regulator composes the PMSM vector control system. A number of simulation and experiments show that the system not only has good performance both in dynamic and steady state but also avoids the adverse effect
resulted from the inaccurate mathematical model and the parameter changes of the PMSM. Therefore, the system possesses a good self-adapting and robust.
The paper presents a new method of how to select the neural input variables by the correlation coefficient of mathematical statistics. According to the absolute value of correlation coefficient, the degree of correlation between input and output variables can be estimated and selected or not, which not only increases the neural network mathematical model accuracy, but also reduces the complexity.
For the accomplishment of the national 863-advanced project, the industry control computer is used as main control unite and the PWSM machine tools spindle drive system. The hardware and software of the system is studied and developed. Basing on the operating characteristics of the PMSM machine tool spindle drive system, a novel frequency multiplication circuits which can be switch to 2 or 4 times of base frequency is proposed in the paper. It resolves the paradox of using a same photoelectric encoder under high and low speed operating condition of motors.
引文
[1] F.Blaschke. The principle of field orientation as applied to the new transvector closed loop control system for rotating field machines. Siemens Ren. 1972, 34 (5):217～220
[2] B.K.Bose. Power electronics and motion control-technology status and recent trends. IEEE Trans.Ind.Appl., 1993, 29 (5):902～909
[3] B.J.Baliga. Power semiconductor devices for variable-frequency drives. Proceedings of the IEEE, 1994,82 (8):1112～1122
[4] H.Le-Huy. Microprocessors and digital IC's for motion control. Proceedings of the IEEE, 1994,82(8):1140～1161
[5] S.A.Nasar, I.Boldea and L.E.Unnewehr. Permanent magnet, reluctance, and self-synchronous motors. CRC Press, 1993
[6] 唐任远等．现代永磁电机理论与设计．北京：机械工业出版社，1997
[7] 尹华杰．主轴永磁同步电动机电磁结构及“弱磁”问题的研究．华中理工大学博士学位论文．1994
[8] 张伯霖，李锻能等．高速加工对机床传动与结构的影响．制造技术与机床．1998(11)：5～7
[9] 魏志强，王先逵等．高速加工机床及其关键技术．制造技术与机床．1998(1)：5～7
[10] 张伯霖等．高速加工机床的发展状况．机械开发．1999(1)：1～5
[11] 郭振宏．宽恒功率调速范围主轴永磁同步电动机及其传动系统的研究．沈阳工业大学博士学位论文．1999
[12] 万文斌．高恒功率调速比永磁同步电动机传动系统的研究．沈阳工业大学博士学位论文．2001
[13] S.Morimoro, M.Sanada and Y.Takeda. Wide-Speed Operation of Interior Permanent Magnet Synchronous Motors with High Performance Current Regulator. IEEE Trans. Ind. Appl. 1994, 30(4): 920～926
[14] LeonhardW. Microprocessor Control of High Dynamic Performance AC Driver, A Survey. Automatic, 1986,22(1): 1～9
[15] Morimoto M, et al. Single-chip Microcomputer Control of the Inverter by the
Magnetic Flux Control PWM Method. IEEE IE, 1989,36(1): 42～47
[16] Ohmae et al. A Microprocessor-Controlled High-Accuracy Wide Range Speed Regulator for Motor Drives. IEEE IE, 1982,29(3): 207～211
[17] Caro J, et al. A Microprocessor-Based of a DC Driving Taking into Account the Load's Variation. IEEE IA, 1986,22(6): 982～988
[18] Ohish K, et al. Adaptive DC Servo Drive Control Taking Force Disturbance Suppression into Account. IEEE IA, 1988,24(1): 171～175
[19] 邓忠华．高性能全数字交流伺服系统的研究华中理工大学博士学位论文．1994
[20] 郭庆鼎等．DSP在高性能电气传动中的优势、限制及应用．电气传动，1991，21(5)：34～41
[21] H.Le-Huy, K.Slimani and P.Viarouge. A Predictive Current Controller for Synchronous Servo Drives. European Conf. Power Electron. Appl. Firenze. Italy, 1991(9)
[22] T.M.Jahns, G.B.Kliman and T.W.Neumann. Interior Permanent Magnet Synchronous Motors for Adjustable-speed Drives. IEEE Trans.Ind.Appl. 1994,22(4):738～747
[23] B.K.Bose. A High Performance Inverter-fed Drive System of an Interior Permanent Magnet Synchronous Machine. Proc. IEEE IAS Mtg. 1987:269～276
[24] P.Pillay and R.Krishnan. Modeling, simulation and Analysis of Permanent Magnet Motor Drives, Part Ⅰ:the Permanent-Magnet Synchronous Motor Drive. IEEE Trans. Ind.Appl. 1994,25(2):.265～273
[25] 林金铭．近年电机理论和实践的某些进展和趋势．中小型电机．1994，21(5)：3～6
[26] W.L.Soong,D.A.Station and T.J.E.Miller. Design of a new axially-laminated interior permanent magnet motor. IEEE Trans. Ind.Appl. 1995,31(2):398～407
[27] 李春元，冯员锟．多变量非线性控制的逆系统方法．北京：清华大学出版社．1991
[28] 孙毅勇，冯国楠，孙亮．自适应滑模跟踪控制交流伺服系统．电气传动．1998(3)
[29] A.Sabanovic and F.Bilalovic. Sliding Mode Control of ac Drives. Proc. IEEE IAS Mtg. 1986:50～55
[30] B.K.Bose. Expert System, Fuzzy logic, and Neural Network Applications in Power Electronics and Motion Control. Proceedings of the IEEE. 1994,82(8):1303～1323
[31] 黄立培，冯光，吴凯．变频调速技术．电工技术学报．1999(增刊)，14：54～58
[32] Y.Yu.Tzou and S.Y.Lin. Fuzzy tuning Current-Vector Control of a Three-Phase PWM Inverter for High-performance AC Drives. IEEE Trans. Ind. Electron. 1998, 45(5):782～791
[33] L.B.Gutierrez and J.A.Lowe. Implementation of a Neural Network Tracking Controller for a Single Flexible Link: Comparison with PD and PID Controllers. IEEE Trans. Ind. Electron. 1998,45(2):307～319
[34] B.K.Bose. Fuzzy Logic and Neural Networks in Power Electronics and Drives. IEEE Ind. Appl. 2000(3): 57～63
[35] A.Rubaai and R,Kotaru .Online Identification and Control of a DC Motor Using Learning Adaptaion of Neural Networks. IEEE Trans. Ind. Appl. 1999,36(3): 935～942
[36] 张昌凡，王耀南，李梦秋．模糊神经滑模控制在交流伺服系统中的应用．电机与控制学报，1999(12)
[37] Cao Zhitong and Cao Jiwei. System identification and simulation for dynamic characteristics of PMSM by neural network with feedback. 第五届国际制造会议论文集．北京：1999，11
[38] 袁曾任．人工神经元网络及其应用．北京：清华大学出版社．1999
[39] 周鹗，曾朝辉，高性能永磁同步电机矢量控制系统研究．电机与控制学报．1997，1(1)：1-6
[40] 许大中编著．交流电机调速理论．杭州：浙江大学出版社．1991年
[41] 王成元，周美文，郭庆鼎．矢量控制交流伺服驱动电动机．北京：机械工业出版社．1994
[42] S.Morimoto,Y.Takeda and T.Hirasa. Current Phase Control Methods for Permanent Magnet Synchronous Motors. IEEE Trans. Power Electron.1990, 5(2): 133～139
[43] 张乃尧，阎平凡．神经网络与模糊控制．北京：清华大学出版社．1998，10
[44] 王顺晃 舒迪前．智能控制系统及其应用．北京：机械工业出版社．1997
[45] D.Hammerstron. Neural networks at work. IEEE Spectrum, vol. 30, 1993(7): 26～32
[46] 郭庆鼎，王军．基于在线辩识补偿的永磁直线同步电机模型参考自适应神经网络速度控制．电气传动．2000(4)：16～19
[2] B.K.Bose. Power electronics and motion control-technology status and recent trends. IEEE Trans.Ind.Appl., 1993, 29 (5):902～909
[3] B.J.Baliga. Power semiconductor devices for variable-frequency drives. Proceedings of the IEEE, 1994,82 (8):1112～1122
[4] H.Le-Huy. Microprocessors and digital IC's for motion control. Proceedings of the IEEE, 1994,82(8):1140～1161
[5] S.A.Nasar, I.Boldea and L.E.Unnewehr. Permanent magnet, reluctance, and self-synchronous motors. CRC Press, 1993
[6] 唐任远等．现代永磁电机理论与设计．北京：机械工业出版社，1997
[7] 尹华杰．主轴永磁同步电动机电磁结构及“弱磁”问题的研究．华中理工大学博士学位论文．1994
[8] 张伯霖，李锻能等．高速加工对机床传动与结构的影响．制造技术与机床．1998(11)：5～7
[9] 魏志强，王先逵等．高速加工机床及其关键技术．制造技术与机床．1998(1)：5～7
[10] 张伯霖等．高速加工机床的发展状况．机械开发．1999(1)：1～5
[11] 郭振宏．宽恒功率调速范围主轴永磁同步电动机及其传动系统的研究．沈阳工业大学博士学位论文．1999
[12] 万文斌．高恒功率调速比永磁同步电动机传动系统的研究．沈阳工业大学博士学位论文．2001
[13] S.Morimoro, M.Sanada and Y.Takeda. Wide-Speed Operation of Interior Permanent Magnet Synchronous Motors with High Performance Current Regulator. IEEE Trans. Ind. Appl. 1994, 30(4): 920～926
[14] LeonhardW. Microprocessor Control of High Dynamic Performance AC Driver, A Survey. Automatic, 1986,22(1): 1～9
[15] Morimoto M, et al. Single-chip Microcomputer Control of the Inverter by the
Magnetic Flux Control PWM Method. IEEE IE, 1989,36(1): 42～47
[16] Ohmae et al. A Microprocessor-Controlled High-Accuracy Wide Range Speed Regulator for Motor Drives. IEEE IE, 1982,29(3): 207～211
[17] Caro J, et al. A Microprocessor-Based of a DC Driving Taking into Account the Load's Variation. IEEE IA, 1986,22(6): 982～988
[18] Ohish K, et al. Adaptive DC Servo Drive Control Taking Force Disturbance Suppression into Account. IEEE IA, 1988,24(1): 171～175
[19] 邓忠华．高性能全数字交流伺服系统的研究华中理工大学博士学位论文．1994
[20] 郭庆鼎等．DSP在高性能电气传动中的优势、限制及应用．电气传动，1991，21(5)：34～41
[21] H.Le-Huy, K.Slimani and P.Viarouge. A Predictive Current Controller for Synchronous Servo Drives. European Conf. Power Electron. Appl. Firenze. Italy, 1991(9)
[22] T.M.Jahns, G.B.Kliman and T.W.Neumann. Interior Permanent Magnet Synchronous Motors for Adjustable-speed Drives. IEEE Trans.Ind.Appl. 1994,22(4):738～747
[23] B.K.Bose. A High Performance Inverter-fed Drive System of an Interior Permanent Magnet Synchronous Machine. Proc. IEEE IAS Mtg. 1987:269～276
[24] P.Pillay and R.Krishnan. Modeling, simulation and Analysis of Permanent Magnet Motor Drives, Part Ⅰ:the Permanent-Magnet Synchronous Motor Drive. IEEE Trans. Ind.Appl. 1994,25(2):.265～273
[25] 林金铭．近年电机理论和实践的某些进展和趋势．中小型电机．1994，21(5)：3～6
[26] W.L.Soong,D.A.Station and T.J.E.Miller. Design of a new axially-laminated interior permanent magnet motor. IEEE Trans. Ind.Appl. 1995,31(2):398～407
[27] 李春元，冯员锟．多变量非线性控制的逆系统方法．北京：清华大学出版社．1991
[28] 孙毅勇，冯国楠，孙亮．自适应滑模跟踪控制交流伺服系统．电气传动．1998(3)
[29] A.Sabanovic and F.Bilalovic. Sliding Mode Control of ac Drives. Proc. IEEE IAS Mtg. 1986:50～55
[30] B.K.Bose. Expert System, Fuzzy logic, and Neural Network Applications in Power Electronics and Motion Control. Proceedings of the IEEE. 1994,82(8):1303～1323
[31] 黄立培，冯光，吴凯．变频调速技术．电工技术学报．1999(增刊)，14：54～58
[32] Y.Yu.Tzou and S.Y.Lin. Fuzzy tuning Current-Vector Control of a Three-Phase PWM Inverter for High-performance AC Drives. IEEE Trans. Ind. Electron. 1998, 45(5):782～791
[33] L.B.Gutierrez and J.A.Lowe. Implementation of a Neural Network Tracking Controller for a Single Flexible Link: Comparison with PD and PID Controllers. IEEE Trans. Ind. Electron. 1998,45(2):307～319
[34] B.K.Bose. Fuzzy Logic and Neural Networks in Power Electronics and Drives. IEEE Ind. Appl. 2000(3): 57～63
[35] A.Rubaai and R,Kotaru .Online Identification and Control of a DC Motor Using Learning Adaptaion of Neural Networks. IEEE Trans. Ind. Appl. 1999,36(3): 935～942
[36] 张昌凡，王耀南，李梦秋．模糊神经滑模控制在交流伺服系统中的应用．电机与控制学报，1999(12)
[37] Cao Zhitong and Cao Jiwei. System identification and simulation for dynamic characteristics of PMSM by neural network with feedback. 第五届国际制造会议论文集．北京：1999，11
[38] 袁曾任．人工神经元网络及其应用．北京：清华大学出版社．1999
[39] 周鹗，曾朝辉，高性能永磁同步电机矢量控制系统研究．电机与控制学报．1997，1(1)：1-6
[40] 许大中编著．交流电机调速理论．杭州：浙江大学出版社．1991年
[41] 王成元，周美文，郭庆鼎．矢量控制交流伺服驱动电动机．北京：机械工业出版社．1994
[42] S.Morimoto,Y.Takeda and T.Hirasa. Current Phase Control Methods for Permanent Magnet Synchronous Motors. IEEE Trans. Power Electron.1990, 5(2): 133～139
[43] 张乃尧，阎平凡．神经网络与模糊控制．北京：清华大学出版社．1998，10
[44] 王顺晃 舒迪前．智能控制系统及其应用．北京：机械工业出版社．1997
[45] D.Hammerstron. Neural networks at work. IEEE Spectrum, vol. 30, 1993(7): 26～32
[46] 郭庆鼎，王军．基于在线辩识补偿的永磁直线同步电机模型参考自适应神经网络速度控制．电气传动．2000(4)：16～19