DocumentCode :
2044733
Title :
A quadrotor helicopter control system based on Brain-computer interface
Author :
Yu Song ; Junjie Liu ; Qiang Gao ; Min Liu
Author_Institution :
Tianjin Key Lab. For Control Theor. & Applic. in Complicated Syst., Tianjin Univ. of Technol., Tianjin, China
fYear :
2015
fDate :
2-5 Aug. 2015
Firstpage :
1478
Lastpage :
1483
Abstract :
This paper explores a novel controlling method for quadrotor helicopter, which enables the user to control it by his mind. We propose the use of non-invasive Brain-computer Interface to control the attitude of the quadrotor helicopter. The electroencephalography (EEG) signal is collected by the Emotiv EPOC, which has fourteen saline sensors. In our tests, the BCI only takes into account the detection of three trained mind events (think left hand, think right hand and think both hands). A Linear Quadratic Regulator (LQR) position controller is designed for the quadrotor helicopter system. Therefore, three kinds of EEG signals correspond to the three attitude of quadrotor helicopter (yaw, pitch and roll). Ten subjects were invited to attend the experiments. The experimental results showed that the average control accuracy was 56.3% and the average transmission rate was 9.8 bits/min.
Keywords :
aircraft control; attitude control; brain-computer interfaces; control engineering computing; control system synthesis; electroencephalography; helicopters; linear quadratic control; position control; EEG signal; Emotiv EPOC; LQR position controller design; attitude control; average control accuracy; average transmission rate; electroencephalography signal; linear quadratic regulator position controller; noninvasive brain-computer interface; quadrotor helicopter control system; saline sensor; Bit rate; Control systems; Electrodes; Electroencephalography; Helicopters; Mathematical model; Software; BCI; EEG; LQR; Quadrotor helicopter;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Mechatronics and Automation (ICMA), 2015 IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4799-7097-1
Type :
conf
DOI :
10.1109/ICMA.2015.7237703
Filename :
7237703
Link To Document :
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