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Neural Network-Based Adaptive Motion Control for a Mobile Robot with Unknown Longitudinal Slipping 预览

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摘要 When the mobile robot performs certain motion tasks in complex environment, wheel slipping inevitably occurs due to the wet or icy road and other reasons, thus directly influences the motion control accuracy. To address unknown wheel longitudinal slipping problem for mobile robot, a RBF neural network approach based on whole model approximation is presented. The real-time data acquisition of inertial measure unit(IMU), encoders and other sensors is employed to get the mobile robot’s position and orientation in the movement, which is applied to compensate the unknown bounds of the longitudinal slipping using the adaptive technique. Both the simulation and experimental results prove that the control scheme possesses good practical performance and realize the motion control with unknown longitudinal slipping.
机构地区 Automation School
出处 《中国机械工程学报:英文版》 SCIE EI CAS CSCD 2019年第4期26-34,共9页 Chinese Journal of Mechanical Engineering
基金 Supported by Scientific and Innovation Research Funds for the Beijing University of Posts and Telecommunications (Grant No. 2017RC22).
作者简介 Correspondence:Gang Wang,E-mail:wg58977@bupt.edu.cn.
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