Adaptive Neural Network Position/force Control of Robot Manipulators with Model Uncertainties*

Author

Wei, Li-Xin ; Yang, Li ; Wang, Hong-rui

Author_Institution

Inst. of Electr. Eng., Yanshan Univ., Qinhuangdao

Volume

3

fYear

2005

Firstpage

1825

Lastpage

1830

Abstract

In this paper, adaptive neural network position/force control of robot manipulators with model uncertainties is considered. The controller combines a neural network modeling technique with self-tuning fuzzy control which describes the relationship between force and position/velocity error. And robust control can be easily incorporated to suppress the neural network modeling errors and the bounded disturbances. Simulation results based on 2-DOF robot show the effectiveness of this approach

Keywords

adaptive control; force control; fuzzy control; manipulators; neurocontrollers; position control; robust control; self-adjusting systems; uncertain systems; velocity control; 2-DOF robot; adaptive neural network position control; force control; force error; model uncertainties; position error; robot manipulators; robust control; self-tuning fuzzy control; velocity error; Adaptive control; Adaptive systems; Error correction; Force control; Manipulators; Neural networks; Programmable control; Robots; Uncertainty; Velocity control; adaptive neural network control; robot manipulators; self-tuning fuzzy control;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks and Brain, 2005. ICNN&B '05. International Conference on

Conference_Location

Beijing

Print_ISBN

0-7803-9422-4

Type

conf

DOI

10.1109/ICNNB.2005.1614981

Filename

1614981