文献类型：期刊文献

英文题名：High-precision position predictive control of mobile robot based on LSTM algorithm

作者：Du, Guangshuo[1]; Liu, Haitao[1,2]; Tian, Xuehong[1]

机构：[1] Guangdong Ocean University, School of Mechanical and Power Engineering, Zhanjiang, 524088, China; [2] Southern Marine Science and Engineering Guangdong Laboratory [Zhanjiang], Zhanjiang, 524000, China

年份：2020

起止页码：3798

外文期刊名：Proceedings - 2020 Chinese Automation Congress, CAC 2020

收录：EI(收录号：20210809955787)

基金：This work was upheld by the Natural Science Foundation of Guangdong Province in China [grant number 2018A0303130076].

语种：英文

外文关键词：Position control - Mobile robots - Learning algorithms - Iterative methods

外文摘要：In this paper, a high precision position predictive control of mobile robot is proposed based on LSTM (Long short term memory) deep learning neural network algorithm. The structure-based error back-propagation algorithm and iterative learning are introduced to make the actual predicted position of mobile robot better approximate the expected position, and obtain satisfied performances. Due to the unique ability of LSTM algorithm to memorize the information far away from the current time, the current position can be better predicted by processing the trajectory information of the mobile robot which is far away from the current time, and make the predicted value closer to the real value. The simulation demonstrates that the proposed method has the excellent predictive control performance. ? 2020 IEEE.