一种考虑跟随误差的S形轨迹残余振动抑制可靠性分析方法

doi:10.3901/JME.2024.16.390

机械工程学报 ›› 2024, Vol. 60 ›› Issue (16): 390-399.doi: 10.3901/JME.2024.16.390

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一种考虑跟随误差的S形轨迹残余振动抑制可靠性分析方法

胡俊宇¹, 韩旭^1,2, 陶友瑞², 李珊瑚³, 张建宁³

1. 湖南大学机械与运载工程学院长沙 410082;
2. 河北工业大学机械工程学院天津 300401;
3. 河北工业大学电气工程学院天津 300401

收稿日期:2023-11-10 修回日期:2024-03-02 出版日期:2024-08-20 发布日期:2024-10-21
作者简介:胡俊宇,男,1995年出生,博士研究生。主要研究方向为精密运动控制,柔性振动抑制。E-mail:junyuhu2021@hnu.edu.cn
韩旭(通信作者),男,1968年出生,博士,教授,博士研究生导师。主要研究方向为工业机器人可靠性、计算反求技术、优化理论与算法。E-mail:xhan@hebut.edu.cn

Reliability Analysis of Residual Vibration Suppression in Flexible Servo Systems under S-curve Trajectory with Bounded Uncertainty

HU Junyu¹, HAN Xu^1,2, TAO Yourui², LI Shanhu³, ZHANG Jianning³

1. College of Mechanical and Vehicle Engineering, Hunan University, Changsha 410082;
2. School of Mechanical Engineering, Hebei University of Technology, Tianjin 300401;
3. School of Electrical Engineering, Hebei University of Technology, Tianjin 300401

Received:2023-11-10 Revised:2024-03-02 Online:2024-08-20 Published:2024-10-21

摘要/Abstract

摘要： S形抑振轨迹规划方法因其高效便捷广泛用于柔性伺服系统残余振动抑制，实际抑振效果会受到伺服跟随误差的影响。基于区间过程模型，提出一种考虑跟随误差的伺服系统残余振动抑制可靠性分析方法。首先建立电机动子位移跟随误差的不确定程度到柔性末端振动响应区间的映射模型，为度量残余振动抑制的可靠性，分别提出残余振动能量抑制及振动抑制鲁棒性的可靠度评估模型。最后结合工程算例验证该方法的有效性，并量化位移跟随误差平稳区间过程特征参数(半径函数与自相关函数)对可靠度指标的影响程度。该可靠性分析方法为考虑跟随误差的柔性伺服系统残余振动抑制效果评估提供理论支撑。

关键词: 柔性伺服系统, S形轨迹规划, 残余振动, 主动抑振, 区间过程, 可靠性分析

Abstract: S-shape vibration suppression trajectory planning method is widely used in residual vibration suppression of flexible servo system because of its high efficiency and convenience. However, the actual vibration suppression effect is affected by following error generated by servo systems. Based on interval process model, a reliability analysis method for residual vibration suppression of flexible servo system considering following error is proposed. Firstly, a mapping model between the uncertainty of the displacement following error and the vibration response interval of the flexible end is established. In order to measure the reliability of residual vibration suppression, reliability evaluation models for residual vibration energy suppression and robustness of residual vibration suppression are proposed respectively. The effectiveness of the proposed method is verified by an engineering example, and the influence degree of the characteristic parameters (radius function and auto-correlation function) on the reliability index is quantified. The reliability analysis method provides theoretical support for the evaluation of residual vibration suppression effect of flexible servo system considering following error.

Key words: flexible servo system, S-curve trajectory, residual vibration, active vibration suppression, interval process, reliability analysis

中图分类号:

TG156

胡俊宇, 韩旭, 陶友瑞, 李珊瑚, 张建宁. 一种考虑跟随误差的S形轨迹残余振动抑制可靠性分析方法[J]. 机械工程学报, 2024, 60(16): 390-399.

HU Junyu, HAN Xu, TAO Yourui, LI Shanhu, ZHANG Jianning. Reliability Analysis of Residual Vibration Suppression in Flexible Servo Systems under S-curve Trajectory with Bounded Uncertainty[J]. Journal of Mechanical Engineering, 2024, 60(16): 390-399.

参考文献

[1] ROTTWINKEL B. 发展中的半导体封装技术[J]. 中国集成电路,2019,28(12):41-42,47. ROTTWINKEL B. Developing semiconductor packaging technology[J]. China Integrated Circuit,2019,28(12):41-42,47
[2] IWASAKI M,SEKI K,MAEDA Y. High-precision motion control techniques:A promising approach to improving motion performance[J]. IEEE Ind. Electron. Mag,2012,6(1):32-40.
[3] SINGHOSE W. Command shaping for flexible systems:A review of the first 50 years[J]. Int. J. Precis. Eng. Manuf,2009,10(4):153-168.
[4] 杨明,曹佳,徐殿国. 基于输入整形技术的交流伺服系统抖动抑制[J]. 电工技术学报,2018,33(21):4979-4986. YANG Ming,CAO Jia,XU Dianguo. Jitter suppression of AC servo system based on input shaping technology[J] Journal of Electrotechnics,2018,33(21):4979-4986
[5] HA C,REW K,KIM K. Formulating a laplace domain approach for tuning motion profiles[C]//2011 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM),Budapest,2011:356-360.
[6] HA C,REW K,KIM K. Robust zero placement for motion control of lightly damped systems[J]. IEEE Trans. Ind. Electron,2013,60(9):3857-3864.
[7] HA C,LEE D. Analysis of embedded prefilters in motion profiles[J]. IEEE Trans. Ind. Electron,2016,65(2):1481-1489.
[8] BIAGIOTTI L,MELCHIORRI C. FIR filters for online trajectory planning with time- and frequency-domain specifications[J]. Control Eng. Pract,2012,20(12):1385-1399.
[9] BIAGIOTTI L,MELCHIORRI C,MORIELLO L. Optimal trajectories for vibration reduction based on exponential filters[J]. IEEE Trans. Control Syst. Technol.,2016,24(2):19.
[10] BIAGIOTTI L,MELCHIORRI C,MORIELLO L. Damped harmonic smoother for trajectory planning and vibration suppression[J]. IEEE Trans. Control Syst. Technol.,2020,28(2):626-634.
[11] OLABI A,BÉARÉE R,GIBARU O,et al. Feedrate planning for machining with industrial six-axis robots[J]. Control Eng. Pract.,2010,18(5):471-482.
[12] BÉARÉE R. New Damped-Jerk trajectory for vibration reduction[J]. Control Eng. Pract.,2014,28:112-120.
[13] BIAGIOTTI L,MELCHIORRI C. Trajectory planning for automatic machines and robots[M]. Berlin Heidelberg:Springer,2008.
[14] FRANKLIN G,POWELL J D,EMAMI-NAEINI A. Feedback control of dynamic systems[M]. Upper Saddle Rive:Prentice Hall,2010.
[15] JIANG Chao,HAN Xu,LIU Jie,et al. Correlation analysis of non-probabilistic convex model and corresponding structural reliability technique[J]. Comput. Methods Appl. Mech. Eng.,2011,200(33-36):2528-2546.
[16] JIANG Chao,NI Bingyu,HAN Xu,et al. Non-probabilistic convex model process:A new method of time-variant uncertainty analysis and its application to structural dynamic reliability problems[J]. Comput. Methods Appl. Mech. Eng.,2013(268):656-676.
[17] JIANG Chao,LI Jinwu,NI Bingyu,et al. Some significant improvements for interval process model and non-random vibration analysis method[J]. Comput. Methods Appl. Mech. Eng.,2019,357(1):112565.
[18] DAI Luyao,LI Xin,ZHU Yu,et al. The generation mechanism of tracking error during acceleration or deceleration phase in ultraprecision motion systems[J]. IEEE Trans. Ind. Electron.,2019,66(9):7109-7119.
[19] DAI Luyao,LI Xin,ZHU Yu,et al. Auto-tuning of model-based feedforward controller by feedback control signal in ultraprecision motion systems[J]. Mech. Syst. Signal Process.,2020,145:106764.
[20] PREUMOT A. Vibration control of active structures[M]. London:Springer,2011.
[21] LALANNE C,Sinusoidal vibration[M]. New York:John Wiley & Sons,Ltd.,2014.
[22] LALANNE C,Mechanical shock[M]. New York:John Wiley & Sons,Ltd.,2014.
[23] KOZAK K,SINGHOSE W,EBERT-UPHOFF I. Performance measures for input shaping and command generation[J]. J. Dyn. Syst. Meas. Control,2006,128:731-736.
[24] KOZAK K,HUEY J,SINGHOSE W. Performance measures for input shaping[C]//Proceedings of 2003 IEEE Conference on Control Applications,2003:1227-1232.
[25] SINGHOSE W,PAO L,A comparison of input shaping and time-optimal flexible-body control[J]. Control Eng. Pract.,1997,5(4):459-467.
[26] DORF R C. Modern control system[M]. Upper Saddle Rive:Prentice Hall,2016.
[27] JIANG Chao,NI Bingyu,LIU Ningyu. Interval process model and non-random vibration analysis[J]. J. Sound Vib.,2016,373:104-113.
[28] JIANG Chao,HAN Xu,LI D. A new interval comparison relation and application in interval number programming for uncertain problems[J]. Computers Materials and Continua,2012,27(3):275-303.
[29] NI Bingyu,JIANG Chao,LI Jinwu,et al. Interval K-L expansion of interval process model for dynamic uncertainty analysis[J]. J. Sound Vib.,2020,474:115254.

一种考虑跟随误差的S形轨迹残余振动抑制可靠性分析方法

Reliability Analysis of Residual Vibration Suppression in Flexible Servo Systems under S-curve Trajectory with Bounded Uncertainty

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