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Time-optimal path tracking for robots under dynamics constraints based on convex optimization

Published online by Cambridge University Press:  15 April 2015

Qiang Zhang ,
Shurong Li ,
Jian-Xin Guo  and
Xiao-Shan Gao
Qiang Zhang
Affiliation:
Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China Department of Automation, China University of Petroleum (East China), Qingdao, China
Shurong Li
Affiliation:
Department of Automation, China University of Petroleum (East China), Qingdao, China
Jian-Xin Guo
Affiliation:
Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China
Xiao-Shan Gao*
Affiliation:
Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China
*
*Corresponding author. E-mail: xgao@mmrc.iss.ac.cn
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Summary

To fully utilize the dynamic performance of robotic manipulators and enforce minimum motion time in path tracking, the problem of minimum time path tracking for robotic manipulators under confined torque, change rate of the torque, and voltage of the DC motor is considered. The main contribution is the introduction of the concepts of virtual change rate of the torque and the virtual voltage, which are linear functions in the state and control variables and are shown to be very tight approximation to the real ones. As a result, the computationally challenging non-convex minimum time path tracking problem is reduced to a convex optimization problem which can be solved efficiently. It is also shown that introducing dynamics constraints can significantly improve the motion precision without costing much in motion time, especially in the case of high speed motion. Extensive simulations are presented to demonstrate the effectiveness of the proposed approach.

Keywords

Robotic manipulatorsMotor dynamicsPath trackingOptimal trajectoryOptimal controlConvex optimization

Information

Type
Articles
Information
Robotica , Volume 34 , Issue 9 , September 2016 , pp. 2116 - 2139
Copyright
Copyright © Cambridge University Press 2015 

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