Title :
Neural network control system for a tracked robot
Author :
Kuzmina, Tatiana ; Dubrovskiy, Grigoriy
Author_Institution :
Control Syst. Dept., St. Petersburg Electrotech. Univ. LETI, St. Petersburg, Russia
Abstract :
In this paper the designing of a tracked robot´s neural network control system is considered. The control system embodies a black line following algorithm, which is using two infrared reflector sensors for black line recognition. The neural network regulator is designed in Matlab/Simulink using the Real-Time Windows Target Toolbox. With the purpose of the neural network regulator training, course passage results of the robot with a fuzzy regulator are used.
Keywords :
control system synthesis; fuzzy control; infrared detectors; mobile robots; neurocontrollers; object recognition; path planning; tracked vehicles; Matlab; Simulink; black line following algorithm; black line recognition; infrared reflector sensors; neural network regulator; neural network regulator training; time window target toolbox; tracked robot neural network control system; MATLAB; Robots; Servomotors; Shape; neural network; tracked robot;
Conference_Titel :
Young Researchers in Electrical and Electronic Engineering Conference (EIConRusNW), 2015 IEEE NW Russia
Conference_Location :
St. Petersburg
Print_ISBN :
978-1-4799-7305-7
DOI :
10.1109/EIConRusNW.2015.7102268
