Back-Stepping and Neural Network Control of a Mobile Robot for Curved Weld Seam Tracking

This paper proposes a back-stepping and neural network hybrid control method for mobile platform and slider of mobile robot used in shipbuilding welding. The kinematics model of the robot is built firstly, and then a motion controller is designed based on the model and back-stepping method. Stabilit...

Full description

Saved in:
Bibliographic Details
Published inProcedia engineering Vol. 15; pp. 38 - 44
Main Authors Yanfeng, Gao, Hua, Zhang, Yanhui, Ye
Format Journal Article
LanguageEnglish
Published Elsevier Ltd 2011
Subjects
Back-stepping
Mobile robot
Neural Network
Weld seam tracking
Back-stepping
Weld seam tracking
Neural Network
Mobile robot
Online AccessGet full text

Cover

More Information
Summary:This paper proposes a back-stepping and neural network hybrid control method for mobile platform and slider of mobile robot used in shipbuilding welding. The kinematics model of the robot is built firstly, and then a motion controller is designed based on the model and back-stepping method. Stability of the controller is proved through use of Liapunov theory. For improving the tracking precision and anti-interference performance of the controller, a neural network is designed to identify the kinematical model of the robot and to adjust the control coefficients in real time based on the tracking errors. The simulation and experiments have been done to verify the effectiveness of the proposed controllers.
ISSN:1877-7058
1877-7058
DOI:10.1016/j.proeng.2011.08.009