改进的强跟踪滤波算法及其在3PTT-2R伺服系统中的应用

姚禹; 张邦成; 蔡赟; 周志杰; 姜大伟; 高智

doi:10.3724/SP.J.1004.2014.01481

改进的强跟踪滤波算法及其在3PTT-2R伺服系统中的应用

doi: 10.3724/SP.J.1004.2014.01481

姚禹^1,2,
张邦成^1,2,
蔡赟^1,2,
周志杰³,
姜大伟^1,2,
高智^1,2

1.
长春工业大学机电工程学院长春 130012;
2.
长春工业大学软件职业技术学院长春 130012;
3.
中国人民解放军第二炮兵工程大学西安 710025

基金项目:

国家自然科学基金（61374138，61370031）和教育部新世纪人才支持计划（NCET-12-0731）资助

详细信息

作者简介:
姚禹吉林大学博士研究生，长春工业大学讲师. 主要研究方向为复杂机电系统建模、滤波和控制.E-mail：yaoyu@mail.ccut.edu.cn

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- 被引次数: 0
出版历程
- 收稿日期: 2013-08-30
- 修回日期: 2014-01-10
- 刊出日期: 2014-07-20

Improved Strong Track Filter and Its Application to Servo Control System of 3PTT-2R Institutions

1.
School of Mechatronic Engineering, Changchun University of Technology, Changchun 130012;
2.
School of Soft Technology, Institute of Automation, Changchun University of Technology, Changchun 130012;
3.
High-Tech Institute of Xi'an, Xi'an 710025

Funds:

Supported by National Natural Science Foundation of China (61374138, 61370031) and New Century Talents Program of Ministry of Education (NCET-12-0731)

摘要

摘要: 为解决3PTT-2R伺服系统由于模型不准确和负载扰动而引起的控制精度下降的问题，以5自由度3PTT-2R伺服系统为研究对象，建立包含执行系统、进给系统和驱动系统等若干子系统的3PTT-2R伺服系统数学模型，提出一种基于改进强跟踪滤波（Strong track filter，STF）的3PTT-2R伺服系统控制算法，并在理论上证明了稳定性.通过仿真分析，比较了STF、改进的STF算法稳定性，及对模型不确定性的鲁棒性，表明所提算法具有跟踪速度快、抑制噪声、精度高等优点.对试样进行表面粗糙度和表面轮廓度检测，实验结果进一步说明所建立的3PTT-2R伺服系统模型与实际非线性系统模型匹配，改进的STF算法具有较好的跟踪能力，鲁棒性强、控制精度高，进而提高了加工精度.
- 串并联机构 /
- 改进STF算法 /
- 跟踪误差 /
- 稳定性 /
- 鲁棒性
Abstract: In order to solve the problem of the declining control accuracy for 5-DOF 3PTT-2R series-parallel machine caused by inaccurate model and the load disturbance, an improved strong track fillter (STF) control method is proposed. The method takes into account the feed system, the implementation system, and servo motor. The improved STF is designed to suppress noise disturbances and its stability is proved. In the simulation, the performance of the improved STF estimation is analyzed and the tracking performances of the STF and improved STF in slowly varying and mutation status are compared. For the experiments of detecting surface roughness and profile, the improved STF tracking control algorithm has better tracking ability, stronger robustness, and higher machining accuracy.
- Series and parallel machine /
- improved strong track filter (STF) /
- tracking error /
- stability /
- robustness

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