Trajectory Tracking Control of Deep Sea Mining Vehicle Based on Iterative Learning Algorithm

DOI

10.2991/aetr-17.2018.9How to use a DOI?

Keywords

Deep-sea mining vehicle; Motion trajectory; Iterative learning

Abstract

In this paper, an open-loop and closed-loop iterative learning control algorithm based on iterative learning theory is proposed to study the working characteristics and control technology of deep-sea mining vehicles. In this method, the deviation of the heading angle and the trajectory deviation are taken as the feedback correction variables in each iteration, and the trajectory deviation of the desired trajectory is corrected continuously, so that the motion trajectory can be precisely controlled.

Copyright

© 2018, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Yun Liu
AU  - Shanshan Guo
PY  - 2018/03
DA  - 2018/03
TI  - Trajectory Tracking Control of Deep Sea Mining Vehicle Based on Iterative Learning Algorithm
BT  - Proceedings of the 2017 International Conference Advanced Engineering and Technology Research (AETR 2017)
PB  - Atlantis Press
SP  - 40
EP  - 45
SN  - 2352-5401
UR  - https://doi.org/10.2991/aetr-17.2018.9
DO  - 10.2991/aetr-17.2018.9
ID  - Liu2018/03
ER  -