基于自适应观测器和线性二次型调节器的高性能伺服系统谐振抑制

摘要
图/表
参考文献
相关文章 (6)

全文: PDF (39773 KB)
输出: BibTeX | EndNote (RIS)

摘要由于机械传动装置的限制,高性能伺服系统在高速正反转和快速定位等动态控制过程中容易发生机械谐振。采用考虑传动装置弹性的电机-负载双惯量机械模型,研究伺服系统的机械谐振抑制技术。以电机转速作为系统广义输出,建立基于双惯量机械模型的参考自适应观测器,实现负载惯量、负载转速和扭力矩的估计。基于观测器的估计状态和参数,设计速度环线性二次型调节器（LQR）来抑制双惯量系统中的机械谐振。为了验证观测器和LQR的有效性,利用Matlab/Simulink进行仿真研究,并在基于TMS320F28335DSP的平台上进行相关实验验证。仿真和实验表明自适应观测器能够较为精确地估计系统的参数和状态,同时也表明基于LQR的状态反馈控制能够有效地抑制传动系统中的机械谐振。

	服务

	把本文推荐给朋友
	加入我的书架
	加入引用管理器
	E-mail Alert
	RSS
	作者相关文章
	赵寿华
	毛永乐
	许翠翠
	陈阳生

关键词 ：高性能伺服, 机械谐振抑制, 双惯量系统, 自适应观测器, 在线线性二次型调节器

Abstract：In the applications of high performance servo system, high dynamic performance is needed to satisfy control demand. However, the limitations of transmission mechanisms in drive system lead to mechanical resonance. Therefore, this paper builds a model of 2-mass transmission mechanisms. Herein, using motor speed and q axis current, an adaptive observer can be established to estimate the load inertia, the load speed and the load torque. Based on the estimation results, a linear quadratic regulator (LQR) is designed to improve the speed performance, and is implemented in a TMS320F28335DSP based drive system. Related simulation and experimental studies have verified the effectiveness of the adaptive observer and LQR in torsional vibration suppression.

Key words： High performance servo system suppression of mechanical resonance 2-mass system adaptive observer on-line linear quadratic regulator

收稿日期: 2014-03-28 出版日期: 2016-04-01

PACS:

TM383.4

基金资助:国家重点基础研究发展计划（973计划）（2013CB035604）和高等学校博士学科点专项科研基金（20130101110112）资助项目

通讯作者: 陈阳生男,1969年生,教授,博士生导师,研究方向为电机设计及其驱动控制。E-mail: yschen@zju.edu.cn

作者简介: 赵寿华男,1984年生,博士研究生,研究方向为高性能永磁同步电机的驱动与控制。E-mail: zxz_9999@zju.edu.cn

引用本文:

赵寿华, 毛永乐, 许翠翠, 陈阳生. 基于自适应观测器和线性二次型调节器的高性能伺服系统谐振抑制[J]. 电工技术学报, 2016, 31(6): 108-117. Zhao Shouhua, Mao Yongle, Xu Cuicui, Chen Yangsheng. Torsional Vibration Suppression Based on Adaptive Observer and Linear Quadratic Regulator in High Performance Servo Drives. Transactions of China Electrotechnical Society, 2016, 31(6): 108-117.

链接本文:

https://dgjsxb.ces-transaction.com/CN/Y2016/V31/I6/108

[1] 王伟华, 肖曦, 丁有爽. 永磁同步电机改进电流预测控制[J]. 电工技术学报, 2013, 28(3): 50-55. Wang Weihua, Xiao Xi, Ding Youshuang. An improved predictive current control method for permanent magnet synchronous motors[J]. Transac- tions of China Electrotechnical Society, 2013, 28(3): 50-55.
[2] 卢达, 赵光宙, 曲轶龙, 等. 永磁同步电机无参数整定自抗扰控制器[J]. 电工技术学报, 2013, 28(3): 27-34. Lu Da, Zhao Guangzhou, Qu Yilong, et al. Permanent magnet synchronous motor control system based on no manual tuned active disturbance rejection control[J]. Transactions of China Electrotechnical Society, 2013, 28(3): 27-34.
[3] 杨俊友, 刘永恒, 白殿春, 等. 基于迭代学习与小波滤波器的永磁直线伺服系统扰动抑制[J]. 电工技术学报, 2013, 28(3): 87-92. Yang Junyou, Liu Yongheng, Bai Dianchun, et al. Disturbance rejection for PMLSM based on iterative learning control and wavelet filter[J]. Transactions of China Electrotechnical Society, 2013, 28(3): 87-92.
[4] Vukosavic S N, Stojic M R. Suppression of torsional oscillations in a high performance speed servo drive[J]. IEEE Transactions on Industrial Electronics, 1998, 45(1): 108-117.
[5] Lee D H, Lee J H, Ahn J W. Mechanical vibration reduction control of two-mass permanent magnet synchronous motor using adaptive notch filter with fast Fourier transform analysis[J]. IET Electric Power Applications, 2012, 6(7): 455-461.
[6] 杨明, 胡浩, 徐殿国. 永磁交流伺服系统机械谐振成因及其抑制[J]. 电机与控制学报, 2012, 16(1): 79-84. Yang Ming, Hu Hao, Xu Dianguo. Cause and suppression of mechanical resonance in PMSM servo system[J]. The Electric Machines and Control, 2012, 16(1): 79-84.
[7] Orlowska-Kowalska T, Szabat K. Control of the drive system with stiff and elastic couplings using adaptive neuro-fuzzy approach[J]. IEEE Transactions on Industrial Electronics, 2007, 54(1): 228-240.
[8] Orlowska-Kowalska T, Szabat K. Damping of tor- sional vibrations in two-mass system using adaptive sliding neuro-fuzzy approach[J]. IEEE Transactions on Industrial Informatics, 2008, 4(1): 47-57.
[9] Orlowska-Kowalska T, Dybkowski M, Szabat K. Adaptive sliding-mode neuro-fuzzy control of the two-mass induction motor drive without mechanical sensors[J]. IEEE Transactions on Industrial Elec- tronics, 2010, 57(2): 553-564.
[10] Orowska-Kowalska T, Kaminski M, Szabat K. Implementation of a sliding-mode controller with an integral function and fuzzy gain value for the electrical drive with an elastic joint[J]. IEEE Transactions on Industrial Electronics, 2010, 57(4): 1309-1317.
[11] Cychowski M, Szabat K, Orlowska-Kowalska T. Constrained model predictive control of the drive system with mechanical elasticity[J]. IEEE Transa- ctions on Industrial Electronics, 2009, 56(6): 1963- 1973.
[12] Muszynski R, Deskur J. Damping of torsional vibrations in high-dynamic industrial drives[J]. IEEE Transactions on Industrial Electronics, 2010, 57(2): 544-552.
[13] Szabat K, Orlowska-Kowalska T. Vibration supper- ssion in a two-mass drive system using PI speed controller and additional feedbacks-comparative study[J]. IEEE Transactions on Industrial Electronics, 2007, 54(2): 1193-1206.
[14] O'Sullivan T M, Bingham C M, Schofield N. Observer-based tuning of two-inertia servo-drive systems with integrated SAW torque transducers[J]. IEEE Transactions on Industrial Electronics, 2007, 54(2): 1080-1091.
[15] Ji J K, Sul S K. Kalman filter and LQ based speed controller for torsional vibration suppression in a 2-mass motor drive system[J]. IEEE Transactions on Industrial Electronics, 1995, 42(6): 564-571.
[16] Zhang G. Speed control of two-inertia system by PI/ PID control[J]. IEEE Transactions on Industrial Electronics, 2000, 47(3): 603-609.
[17] Szabat K, Orlowska-Kowalska T. Performance improvement of industrial drives with mechanical elasticity using nonlinear adaptive Kalman filter[J]. IEEE Transactions on Industrial Electronics, 2008, 55(3): 1075-1084.
[18] I. D. 朗道. 自适应控制–模型参考方法[M]. 吴百凡, 译. 北京: 国防工业出版社, 1985.
[19] 吴受章. 最优控制理论与应用[M]. 北京: 机械工业出版社, 2011.