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漂浮基空间机器人自适应RBF网络终端滑模控制 被引量:2

ADAPTIVE RBF BASED TERMINAL SLIDING MODE CONTROL OF FREE-FLOATING SPACE ROBOTS
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摘要 主要研究漂浮基空间机器人对工作空间连续轨迹跟踪控制问题.针对系统动力学模型中非线性项未知,以及参数不确定性和外界扰动无法估计的情况,提出了基于自适应RBF网络终端滑模控制方法.该方法结合了非线性滑动流形与径向基函数特性,利用自适应RBF网络在线学习系统中的不确定性,使得无需精确的动力学模型亦能保证系统在有限时间内快速稳定.根据Lyapunov方法设计的自适应增益保证闭环控制系统具有全局稳定性,并且有效抑制抖振现象.针对6关节空间机器人的轨迹跟踪控制仿真表明,提出的自适应RBF网络终端滑模控制方法能够基于不完整动力学模型实现高精度轨迹跟踪,且误差在有限时间内快速收敛,系统抖振也得到了有效抑制. Continuous trajectory tracking control in task space of free-floating space robots was investigated. An adaptive RBF based terminal sliding mode control method was proposed for a dynamics model with unknown nonlinear terms, parametric uncertainties and unbounded external disturbances. The proposed method combinesthe properties of a nonlinear sliding manifold with that of a radial basis function, where the adaptive RBF network is used to estimate the unknown parts of the system on line, such that rapid convergence of control errors in finite time are guaranteed without the exact dynamics mode of the system. The adaptive updating laws were designed according to Lyapunov approach, which make the closed-loop control system globally stable and eliminate chattering problems. A six-link free-floating space robot was employed to validate the proposed method. The simulation results show that the adaptive RBF based terminal sliding mode control method provides high precision performances without the exact dynamics model. Meanwhile, the chattering problems were eliminated effectively.
出处 《动力学与控制学报》 2014年第4期341-347,共7页 Journal of Dynamics and Control
基金 校基础预研资助项目(JC13-01-08)~~
关键词 漂浮基空间机器人 自适应RBF网络 终端滑模 free-floating space robots, adaptive RBF network, terminal sliding mode
作者简介 通讯作者E-mail:mengyuhe_nudt@163.com
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  • 1丛佩超,孙兆伟.单臂式空间机械臂捕捉空间目标问题研究[J].动力学与控制学报,2009,7(1):45-49. 被引量:2
  • 2Nanos K, Papadopoulos E. On the use of free-floating space robots in the presence of angular momentum. Intel Serv Robotics, 2011,4(1 ) : 3 - 15.
  • 3郭益深,陈力.漂浮基柔性空间机械臂姿态与关节协调运动的Terminal滑模控制[J].动力学与控制学报,2009,7(2):158-163. 被引量:5
  • 4陈力,刘延柱.参数不确定空间机械臂系统的增广自适应控制[J].航空学报,2000,21(2):150-154. 被引量:17
  • 5Xu W, Liang B, Xu Y. Survey of modeling, planning, and ground verification of space robotic systems. Acta Astronau- tica, 2011, 68(11) : 1629 - 1649.
  • 6Moosavian S A A, Papadopoulos E. Free-flying robots in space: An overview of dynamics modeling, planning and control. Robotica, 2007, 25 (5) : 537 - 547.
  • 7Khaloozadeh H, Homaeinejad M R. Real-time regulated sliding mode controller design of multiple manipulator space free-flying robot. Journal of Mechanical Science and Tech- nology, 2010, 24(6) : 1337 - 1351.
  • 8Arisoy A, Bayrakceken M K, Basturk S. High order slidingmode control of a space robot manipulator. Istanbul: Inter- national Conference on Recent Advances in Space Technol- ogies, 2011:833 - 838.
  • 9Bayramoglu H, Komurcugil H. Nonsingular decoupled ter- minal sliding-mode control for a class of fourth-order non- linear systems. Communications in Nonlinear Science and Numerical Simulation, 2013, 18 (9) : 2527 - 2539.
  • 10丁世宏,李世华.有限时间控制问题综述[J].控制与决策,2011,26(2):161-169. 被引量:87

二级参考文献50

共引文献107

同被引文献27

  • 1闫文辉,彭勇,张绍槐.旋转导向钻井工具的研制原理[J].石油学报,2005,26(5):94-97. 被引量:55
  • 2FENG Yong, YU Xinghuo, MAN Zhihong. Non-singular terminal sliding mode control of rigid manipulators [ J ]. Automatica,2002,38 (12) :2159-2167.
  • 3FEI Juntao, YANG Yuzheng, WU Dan. Robust RBF neural network control with adaptive sliding mode compensator for MEMS gyroscope [ J ]. IEEE College of Computer and Information, 2013 (6) :499 -504.
  • 4WANG Lianyong, CHAI Tianyou, ZHAI Lianfei. Neural- network-based terminal sliding-mode control of robotic ma- nipulators including actuator dynamics[ J]. IEEE Transac- tions on Industrial Electronics ,2009,56 (9) :3296-3304.
  • 5HUANG Deshuang, DU Jixiang. A constructive hybrid structure optimization methodology for radial basis proba- bilistic neural networks [ J ]. IEEE Transactions on Neural Networks / a Publication of the IEEE Neural Networks Council ,2008,19 (12) :2099-2115.
  • 6HUANG Guangbin, CHEN Lei, Slew C K. Universal ap- proximation using incremental constructive feedforward networks with random hidden nodes [ J ]. IEEE Transac- tions on Neural Networks / a Publication of the IEEE Neu- ral Networks Council,2006,17 (4) :879-892.
  • 7Mohammad A, Hamid D. Robust PID control of cable-driv- en robots with elastic cables. In: Proceeding of the 2013 RSI/ISM International Conference on Robotics and Meeha- tronics, Tehran, Iran. IEEE, 2013:331 ~ 336.
  • 8Dallej T, Gouttefarde M, Andreff N, et al. Towards vision- based control of cable-driven parallel robots. In: Proceed- ing of the 2011 IEEE/RSJ International Conference on In- telligent Robots and Systems, San Francisco, CA, USA. IEEE, 2011:2855 - 2860.
  • 9ONERA. SACSO, suspension active pour essais en soufflerie. http: //www. onera, fr/dcsd/sacso/index, php. 2008,12,5.
  • 10Xiao Y W, Lin Q, Zheng Y Q, et al. Model aerodynamic tests with a wire-driven parallel suspension system in low- speed wind tunnel. Chinese Journal of Aeronautics, 2010,4 (23) : 393 ~ 400.

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