系统仿真学报 ›› 2018, Vol. 30 ›› Issue (3): 994-1001.doi: 10.16182/j.issn1004731x.joss.201803028

• 仿真应用工程 • 上一篇    下一篇

冗余度机器人变负载预测模糊自适应滑模控制

贺军1, 骆敏舟2, 赵江海2, 徐林森2, 李涛2   

  1. 1.中国科学技术大学信息科学技术学院,安徽 合肥 230026;
    2.中国科学院合肥物质科学研究院先进制造技术研究所,江苏 常州 213164
  • 收稿日期:2016-02-25 出版日期:2018-03-08 发布日期:2019-01-02
  • 作者简介:贺军(1986-),男,陕西,博士生,研究方向为双臂机器及嵌入式系统;骆敏舟(1973-),男,安徽,博士,博导,研究员,研究方向为机电一体化等。
  • 基金资助:
    国家自然科学基金(51405469),国家科技支撑计划(2015BAK06B02),江苏省科技支撑计划(BE2013003)

Adaptive Fuzzy Sliding Mode Controller with Predictive Control for Redundant Manipulators with Variable Payload

He Jun1,2, Luo Minzhou2, Zhao Jianghai2, Xu Linsen2, Li Tao2   

  1. 1.School of Information Science and Technology, University of Science and Technology of China,Hefei 230026, China;
    2.Institute of Advanced Manufacturing Technology, Hefei Institute of Physical Science, Chinese Academy of Sciences, Changzhou 213164, China
  • Received:2016-02-25 Online:2018-03-08 Published:2019-01-02

摘要: 提出了基于变负载卡尔曼预测模糊自适应滑模控制算法(AFSMCK),该算法可实现冗余度机器人在变负载情况下的精确控制。该方法有效的解决了机器人因模型不确定以及末端变负载对机器人系统的影响,实现机器人的稳定控制。设计出一个基于迭代算法的卡尔曼预测控制器可精确预测变负载的大小。采用自适应模糊逻辑算法,逼近滑模控制器中的切换增益,消除滑模控制的抖动问题。根据李亚普洛夫理论设计了滑模控制律和自适应控制律,进一步保证了闭环系统的稳定性。提出的理论和控制方法通过仿真实验进一步得到了验证。

关键词: 机器人控制, 模糊逻辑, 自适应控制, 冗余度机器人, 卡尔曼预测控制

Abstract: This paper presents an adaptive fuzzy sliding mode controller with Kalman predictive control (AFSMCK) for the redundant robotic manipulator handling a variable payload to achieve a precise trajectory tracking in the task space. This approach could be applied to solve the problems caused by the variable payload and model uncertainties. A Kalman predictive controller using the recursive algorithm is presented for an accurate prediction of a variable payload. The adaptive fuzzy logic algorithm is designed to approximate the parameters of the sliding mode controller to avoid chattering in real time. Lyapunov theory is applied to guarantee the stability of the proposed closed-loop robotic system. The effectiveness of the proposed control approach and theoretical discussion are proved by comparative simulation on a seven-link robot.

Key words: robot control, fuzzy logic, adaptive control, redundant manipulators, Kalman predictive control

中图分类号: