Title :
Application of Fuzzy Self-Adapting Kalman Filter in the Control System of an Eradicating Stump Robot
Author :
Du, Danfeng ; Ma Yan ; Guo, Xiurong ; Lu, Huaimin
Author_Institution :
Coll. of Traffic, Northeast Forestry Univ., Harbin, China
Abstract :
In this paper the structure and function of an eradicating stump robot is introduced. In order to eradicate efficiently a tree stump, RBF neural network based on fuzzy self-adapting Kalman filter is applied to control the manipulator motion. By programming with MATLAB and solidifying the program into a chip, the data obtained from the CCD and the sensors on line is processed so as to control the operation of eradicating stump automatically. The test shows that the automatic control system of neural network is effective and the stump eradicated by the robot is about 120 stump whose diameter is over 0.5 m per day, the efficiency of which is 25~30 times than that of a eradicating by hand.
Keywords :
adaptive Kalman filters; manipulators; motion control; neurocontrollers; radial basis function networks; self-adjusting systems; CCD cameras; MATLAB programming; RBF neural network; eradicating stump robot; manipulator motion control; online sensors; radial basis function network; self-adapting Kalman filter; Automatic control; Automatic programming; Control systems; Fuzzy control; Fuzzy neural networks; Fuzzy systems; Manipulators; Motion control; Neural networks; Robot sensing systems; Computer control; Fuzzy self-adapting Kalman filter; RBF neural network controller; Robot;
Conference_Titel :
Computational Intelligence and Design, 2009. ISCID '09. Second International Symposium on
Conference_Location :
Changsha
Print_ISBN :
978-0-7695-3865-5
DOI :
10.1109/ISCID.2009.237
