[1]陈刚,张介,李旭,等.无人驾驶机器人机械腿非线性模糊自适应反演滑模控制[J].东南大学学报(自然科学版),2020,50(3):570-579.[doi:10.3969/j.issn.1001-0505.2020.03.021]
 Chen Gang,Zhang Jie,Li Xu,et al.Nonlinear fuzzy adaptive backstepping sliding mode control for mechanical legs on unmanned robot[J].Journal of Southeast University (Natural Science Edition),2020,50(3):570-579.[doi:10.3969/j.issn.1001-0505.2020.03.021]
点击复制

无人驾驶机器人机械腿非线性模糊自适应反演滑模控制()
分享到:

《东南大学学报(自然科学版)》[ISSN:1001-0505/CN:32-1178/N]

卷:
50
期数:
2020年第3期
页码:
570-579
栏目:
交通运输工程
出版日期:
2020-05-20

文章信息/Info

Title:
Nonlinear fuzzy adaptive backstepping sliding mode control for mechanical legs on unmanned robot
作者:
陈刚1张介1李旭2张为公2
1 南京理工大学机械工程学院, 南京 210094; 2 东南大学仪器科学与工程学院, 南京 210096
Author(s):
Chen Gang1 Zhang Jie1 Li Xu2 Zhang Weigong2
1 School of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China
2 School of Instrument Science and Engineering, Southeast University, Nanjing 210096, China
关键词:
无人驾驶机器人 摩擦干扰 模糊自适应反演滑模控制 非线性干扰观测器
Keywords:
unmanned robot friction disturbance fuzzy adaptive backstepping sliding mode control nonlinear disturbance observer
分类号:
U463.6
DOI:
10.3969/j.issn.1001-0505.2020.03.021
摘要:
为了实现无人驾驶机器人机械腿位置精确跟踪及提高车速跟踪精度,针对机械腿受到的非线性干扰,提出了一种基于非线性干扰观测器的机械腿模糊自适应反演滑模控制方法.首先,通过对机械腿机构操纵踏板时的位置运动分析,建立了机械腿运动学模型,构建了考虑运动副非线性摩擦的机械腿动力学模型,描述了机械腿关节间摩擦力矩与相对速度之间的关系,求得了摩擦参数.接着,设计了油门/制动机械腿切换控制器和非线性干扰观测器.最后,针对观测误差以及其他不确定干扰,设计了模糊自适应反演滑模控制器,进行了李雅普诺夫稳定性分析.实验结果表明,所提方法有效削减了控制输出的抖振,且相较于未对摩擦进行补偿的情况,机械腿位置最大跟踪误差从5.5×10-2 rad减小为1.1×10-3 rad,最大车速跟踪误差从2.21 km/h减小为1.91 km/h.基于干扰观测器的机械腿模糊自适应反演滑模控制方法能够有效提高机械腿跟踪精度与车速跟踪精度.
Abstract:
To accurately track the position of mechanical legs for unmanned robot and improve the tracking accuracy of the vehicle speed, a fuzzy adaptive backstepping sliding mode control method based on the nonlinear disturbance observer was proposed to deal with the non-linear disturbance to the mechanical legs. First, a kinematics model of mechanical legs was established by analyzing the position and the motion of the mechanical leg mechanism when it operated the pedal. The dynamics model of mechanical legs considering the non-linear friction of the motion pair was constructed. The relation between the friction moment and the relative velocity of the joint of the mechanical legs was described, and the friction parameters were obtained. Then, a throttle/brake mechanical leg switching controller and a non-linear disturbance observer were designed. Finally, a fuzzy adaptive backstepping sliding mode controller was designed for the observation error and other uncertain disturbances, and the Lyapunov stability was analyzed. The experimental results show that the method can effectively reduce the chattering of the control output, and the maximum tracking error of the mechanical leg position is reduced from 5.5 × 10-2 rad to 1.1 × 10-3 rad, and the maximum speed tracking error is reduced from 2.21 km/h to 1.91 km/h, compared with the case without the friction compensation. The fuzzy adaptive backstepping sliding mode control method based on the disturbance observer can improve the tracking accuracy of the mechanical legs and the tracking accuracy of the vehicle speeds.

参考文献/References:

[1] Chen G, Zhang W G. Hierarchical coordinated control method for unmanned robot applied to automotive test[J].IEEE Transactions on Industrial Electronics, 2016, 63(2): 1039-1051. DOI:10.1109/tie.2015.2477266.
[2] Chen G, Zhang W G. Digital prototyping design of electromagnetic unmanned robot applied to automotive test[J].Robotics and Computer-Integrated Manufacturing, 2015, 32: 54-64. DOI:10.1016/j.rcim.2014.09.004.
[3] Hirata N, Mizutani N, Matsui H, et al. Fuel consumption in a driving test cycle by robotic driver considering system dynamics[C]// IEEE International Conference on Robotics and Automation(ICRA). Seattle, Washington, USA, 2015: 3374-3379. DOI: 10.1109/ICRA.2015.7139665.
[4] 吴俊, 陈刚. 驾驶机器人车辆的多模式切换控制[J]. 汽车工程, 2018, 40(10): 1215-1222. DOI:10.19562/j.chinasae.qcgc.2018.010.014.
Wu J, Chen G. Multi-mode switching control for robot driven vehicles[J]. Automotive Engineering, 2018, 40(10): 1215-1222. DOI:10.19562/j.chinasae.qcgc.2018.010.014. (in Chinese)
[5] 陈刚, 吴俊. 无人驾驶机器人车辆非线性模糊滑模车速控制[J]. 中国公路学报, 2019, 32(6): 114-123. DOI: 10.19721/j.cnki.1001-7372.2019.06.012.
Chen G, Wu J. Nonlinear fuzzy sliding mode speed control for unmanned driving robotic vehicle[J]. China Journal of Highway and Transport, 2019, 32(6): 114-123. DOI:10.19721/j.cnki.1001-7372.2019.06.012. (in Chinese)
[6] 王和荣, 陈刚. 无人驾驶机器人机械腿模糊监督控制[J]. 汽车工程, 2019, 41(5): 522-529, 536. DOI:10.19562/j.chinasae.qcgc.2019.05.007.
Wang H R, Chen G. Fuzzy supervisory control of mechanical legs of unmanned robots[J]. Automotive Engineering, 2019, 41(5): 522-529, 536. DOI:10.19562/j.chinasae.qcgc.2019.05.007. (in Chinese)
[7] 刘坤明, 徐国艳, 余贵珍. 驾驶机器人机械腿动力学建模与仿真分析[J]. 北京航空航天大学学报, 2016, 42(8): 1709-1714. DOI:10.13700/j.bh.1001-5965.2015.0519.
Liu K M, Xu G Y, Yu G Z.Dynamic modeling and simulation analysis of robot driver’s mechanical legs[J]. Journal of Beijing University of Aeronautics and Astronautics, 2016, 42(8): 1709-1714. DOI:10.13700/j.bh.1001-5965.2015.0519. (in Chinese)
[8] 张达, 原大宁, 刘宏昭. 考虑关节摩擦的3-UPS/PU并联机构模糊自适应滑模控制[J]. 中国机械工程, 2017, 28(4): 391-397, 403. DOI:10.3969/j.issn.1004-132X.2017.04.003.
Zhang D, Yuan D N, Liu H Z.Adaptive fuzzy sliding mode control of 3-UPS/PU parallel mechanisms including joint frictions[J]. China Mechanical Engineering, 2017, 28(4): 391-397, 403. DOI:10.3969/j.issn.1004-132X.2017.04.003. (in Chinese)
[9] Sailer S, Buchholz M, Dietmayer K. Driveaway and braking control of vehicle with manual transmission using a robotic driver[C]// Proceedings of the IEEE International Conference on Control Applications. Hyderabad, India, 2013: 235-240. DOI: 10.1109/CCA.2013.6662764.
[10] 陈刚, 张为公, 王良模. 电磁直驱驾驶机器人模糊神经网络车速控制方法及试验验证[J]. 科学通报, 2017, 62(30): 3514-3524. DOI:10.1360/N972017-00134.
Chen G, Zhang W G, Wang L M. Fuzzy-neural-network-based speed control method and experiment verification for electromagnetic direct drive robot driver[J]. Chinese Science Bulletin, 2017, 62(30): 3514-3524. DOI:10.1360/N972017-00134. (in Chinese)
[11] 姚伟, 张丹丹, 郭毓, 等. 一种改进的柔性关节机械臂分级滑模控制[J]. 东南大学学报(自然科学版), 2018, 48(2): 201-206. DOI:10.3969/j.issn.1001-0505.2018.02.002.
Yao W, Zhang D D, Guo Y,et al. Improved hierarchical sliding mode control for flexible-joint manipulator[J]. Journal of Southeast University(Natural Science Edition), 2018, 48(2): 201-206. DOI:10.3969/j.issn.1001-0505.2018.02.002. (in Chinese)
[12] 包达飞, 汤文成, 董亮. 带摩擦补偿的滚珠丝杠副进给系统自适应滑模控制[J]. 东南大学学报(自然科学版), 2015, 45(3): 455-460. DOI:10.3969/j.issn.1001-0505.2015.03.008.
Bao D F, Tang W C, Dong L. Adaptive sliding mode control of ball screw drives with friction compensation[J]. Journal of Southeast University(Natural Science Edition), 2015, 45(3): 455-460. DOI:10.3969/j.issn.1001-0505.2015.03.008. (in Chinese)
[13] 王丽梅, 李兵. 基于摩擦观测器的直接驱动XY平台轮廓控制器设计[J]. 电机与控制学报, 2013, 17(1): 31-36. DOI:10.3969/j.issn.1007-449X.2013.01.006.
Wang L M, Li B. Contour controller design for direct drive XY table based on friction observer[J].Electric Machines and Control, 2013, 17(1): 31-36. DOI:10.3969/j.issn.1007-449X.2013.01.006. (in Chinese)
[14] 国家环境保护总局. GB 18352.6—2016 轻型汽车污染物排放限值及测量方法(中国第六阶段)[S]. 北京: 中国标准出版社, 2016.
[15] 詹兴泉. 车用催化转化器评价技术及耐久实验方法间相关性研究[D]. 武汉:武汉理工大学, 2002.
  Zhan X Q. Research on evaluation technology and correlation between test methods of durability of catalytic converter for motor vehicle[D]. Wuhan: Wuhan University of Technology, 2002.(in Chinese)

备注/Memo

备注/Memo:
收稿日期: 2019-11-26.
作者简介: 陈刚(1981—),男,博士,副教授,gang0418@163.com.
基金项目: 国家自然科学基金资助项目(51675281)、中央高校基本科研业务费专项资金资助项目(30918011101)、江苏省“六大人才高峰”计划资助项目(2015-JXQC-003)、江苏省研究生科研与实践创新计划资助项目(KYCX19_0265).
引用本文: 陈刚,张介,李旭,等.无人驾驶机器人机械腿非线性模糊自适应反演滑模控制[J].东南大学学报(自然科学版),2020,50(3):570-579. DOI:10.3969/j.issn.1001-0505.2020.03.021.
更新日期/Last Update: 2020-05-20