DocumentCode
129991
Title
ANFIS-based control strategy for a drilling and coring device in lunar exploration
Author
Chongbin Chen ; Qiquan Quan ; Shengyuan Jiang ; Zongquan Deng
Author_Institution
State Key Lab. of Robot. & Syst., Harbin Inst. of Technol., Harbin, China
fYear
2014
fDate
28-30 July 2014
Firstpage
188
Lastpage
193
Abstract
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.
Keywords
adaptive control; drilling (geotechnical); fuzzy neural nets; fuzzy reasoning; identification; lunar rocks; lunar surface; neurocontrollers; planetary rovers; ANFIS-based control strategy; Chang´e-3; China; adaptive neuro-fuzzy inference system based control strategy; automated control; automated lunar regolith sampling; complex drilling media; complex environment; drilling experimental test; drilling-and-coring device; identification ratio; indeterminable drilling environments; lander; longitudinal direction; lunar exploration; lunar regolith simulant; lunar rock simulant; lunar rover; lunar surface; network training; Drilling machines; Electron tubes; Force; Media; Moon; Rocks; Torque; Drilling and coring; Drilling parameters; Neuro-fuzzy inference system;
fLanguage
English
Publisher
ieee
Conference_Titel
Information and Automation (ICIA), 2014 IEEE International Conference on
Conference_Location
Hailar
Type
conf
DOI
10.1109/ICInfA.2014.6932650
Filename
6932650
Link To Document