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

Volume

2

fYear

2009

fDate

12-14 Dec. 2009

Firstpage

364

Lastpage

367

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Intelligence and Design, 2009. ISCID '09. Second International Symposium on

Conference_Location

Changsha

Print_ISBN

978-0-7695-3865-5

Type

conf

DOI

10.1109/ISCID.2009.237

Filename

5368423