东北大学学报:自然科学版 ›› 2018, Vol. 39 ›› Issue (3): 378-383.DOI: 10.12068/j.issn.1005-3026.2018.03.015

• 机械工程 • 上一篇    下一篇

基于T-S模糊补偿的六轴机械臂的滑模鲁棒控制

王宏, 郑天奇, 纪俐, 陆志国   

  1. (东北大学 机械工程与自动化学院, 辽宁 沈阳110819)
  • 收稿日期:2016-10-09 修回日期:2016-10-09 出版日期:2018-03-15 发布日期:2018-03-09
  • 通讯作者: 王宏
  • 作者简介:冯明杰(1971-), 男, 河南禹州人, 东北大学副教授; 王恩刚(1962-), 男, 辽宁沈阳人, 东北大学教授,博士生导师.王宏(1960-),女,辽宁沈阳人,东北大学教授,博士生导师.
  • 基金资助:
    国家自然科学基金资助项目(51171041).国家自然科学基金资助项目(51505069); 辽宁省高等学校创新团队项目(LT2014006).

Six-Axis Manipulator’s Sliding Mode Robust Control Based on T-S Fuzzy Compensation

WANG Hong, ZHENG Tian-qi, JI Li, LU Zhi-guo   

  1. School of Mechanical Engineering & Automation, Northeastern University, Shenyang 110819, China.
  • Received:2016-10-09 Revised:2016-10-09 Online:2018-03-15 Published:2018-03-09
  • Contact: WANG Hong
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摘要: 通过一种简单的模糊滑模控制以达到机械臂跟踪的最佳运动轨迹.所提方法的核心是通过线性化反馈方法,将机械臂动力学的已知部分去除,然后用经典的滑模控制克服系统的不确定性,之后应用T-S模糊模型,将经典的滑模控制器转化为规则十分简单的模糊滑模控制器.仿真分析表明,在不确定性存在的情况下,所提出的控制律全局渐近稳定.最后,通过六轴机械臂的Matlab/Adams联合仿真,验证了模型的准确性,并且通过与经典滑模控制比较得出了在结构化和非结构化的不确定性存在条件下该控制方案的优越性.

关键词: 六轴机械臂, 滑模控制, 模糊控制, Lyapunov稳定, 联合仿真

Abstract: A simple fuzzy sliding mode control was proposed to obtain the optimum movement of a manipulator’s trajectory tracking. The core of the proposed method is to use the feedback linearization method to remove the known kinetics of the manipulator, use the classical sliding mode control to overcome the system uncertainty, and then apply the T-S fuzzy model to translate the classical sliding mode controller into a fuzzy sliding mode controller with very simple fuzzy rules. The simulation results showed that in the case of uncertainty, the proposed control law is globally asymptotically stable. Finally, the co-simulation of the six-axis manipulator by Matlab / Adams verified the accuracy of the model. By comparing the classical sliding mode control result, the proposed method under the conditions of structured and unstructured uncertainties has a high performance.

Key words: six-axis manipulator, sliding mode control, fuzzy control, Lyapunov stability, co-simulation

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