TY - GEN
T1 - ANFIS-based control strategy for a drilling and coring device in lunar exploration
AU - Chen, Chongbin
AU - Quan, Qiquan
AU - Jiang, Shengyuan
AU - Deng, Zongquan
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2014/10/21
Y1 - 2014/10/21
N2 - The second step for lunar exploration of China has been completed already, the probe 'Chang'e-3' successfully landed on the moon, including a lander and a lunar rover. The third step of the project is to achieve automated sampling of lunar regolith through a drilling and coring device. On the moon, lunar regolith and lunar rock may be encountered randomly along the longitudinal direction. Due to the indeterminable drilling environments for the sampling device, the automated control becomes very crucial in the drilling process. This paper proposed an adaptive neuro-fuzzy inference system (ANFIS) based control strategy to tackle the complex drilling media beneath lunar surface. The network is trained through typical lunar regolith simulants and lunar rock simulants, with high identification ratio. A multi-layered drilling medium is built with lunar regolith simulant and lunar rock simulant for drilling experimental test. Experiments indicate that the ANFIS based control strategy can adapt to the complex environment well.
AB - The second step for lunar exploration of China has been completed already, the probe 'Chang'e-3' successfully landed on the moon, including a lander and a lunar rover. The third step of the project is to achieve automated sampling of lunar regolith through a drilling and coring device. On the moon, lunar regolith and lunar rock may be encountered randomly along the longitudinal direction. Due to the indeterminable drilling environments for the sampling device, the automated control becomes very crucial in the drilling process. This paper proposed an adaptive neuro-fuzzy inference system (ANFIS) based control strategy to tackle the complex drilling media beneath lunar surface. The network is trained through typical lunar regolith simulants and lunar rock simulants, with high identification ratio. A multi-layered drilling medium is built with lunar regolith simulant and lunar rock simulant for drilling experimental test. Experiments indicate that the ANFIS based control strategy can adapt to the complex environment well.
KW - Drilling and coring
KW - Drilling parameters
KW - Neuro-fuzzy inference system
UR - https://www.scopus.com/pages/publications/84914099150
U2 - 10.1109/ICInfA.2014.6932650
DO - 10.1109/ICInfA.2014.6932650
M3 - 会议稿件
AN - SCOPUS:84914099150
T3 - 2014 IEEE International Conference on Information and Automation, ICIA 2014
SP - 188
EP - 193
BT - 2014 IEEE International Conference on Information and Automation, ICIA 2014
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2014 IEEE International Conference on Information and Automation, ICIA 2014
Y2 - 28 July 2014 through 30 July 2014
ER -