The modeling and controller design of an angular servo robot based on the RBF neural network adaptive control

Author

Zeyan Hu ; Xiaoguang Zhou ; Shimin Wei

Author_Institution

Autom. Sch., Beijing Univ. of Posts & Telecommun., Beijing, China

fYear

2014

fDate

10-12 Aug. 2014

Firstpage

319

Lastpage

323

Abstract

The structure and control system of the angular servo robot have been proposed in this paper. The main parts of the robot are the body and motion platform. When the robot turns round, the motion platform could keep balance and without an interference from the turning. According to the structure of the robot, Lagrange theorem is chosen to establish the dynamic model through the analysis of kinetic and potential energy. Then the controller based on the RBF neural network adaptive controller is designed. It is simulated by the Matlab software in order to ensure the effectiveness and reasonableness. After the simulation, we could sure the controller is reasonable and effective. The system could achieve the desired objectives after a very short time.

Keywords

adaptive control; approximation theory; control system synthesis; mechanical stability; mobile robots; motion control; neurocontrollers; radial basis function networks; robot dynamics; servomotors; Lagrange theorem; Matlab software; RBF neural network adaptive control; angular servo robot; body platform; control system; controller design; dynamic model; kinetic energy analysis; motion platform; potential energy analysis; Adaptation models; Equations; Kinetic energy; Mathematical model; Robot kinematics; Servomotors; Lagrange model; RBF neural network; adaptive control; angular servo;

fLanguage

English

Publisher

ieee

Conference_Titel

Advanced Mechatronic Systems (ICAMechS), 2014 International Conference on

Conference_Location

Kumamoto

Type

conf

DOI

10.1109/ICAMechS.2014.6911564

Filename

6911564