Fuzzy-neuro Position/Force Control of Robot Manipulators with Uncertainties

Author

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

Author_Institution

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

Volume

2

fYear

2005

Firstpage

1004

Lastpage

1008

Abstract

In this paper, a new robust robot force tracking impedance control scheme that has the capability to track a specified desired force and to compensate for uncertainties in environment stiffness as well as in robot dynamic model is proposed. The uncertainties in robot dynamics are compensated by a radial basis function network (RBFN) controller, and a fuzzy tuning mechanism is developed to generate the impedance model which describes the relationship between force and position/velocity error. Simulation studies based on a two-DOF robot manipulator are carried out and the results show that highly robust position/force tracking can be achieved in the presence of large uncertainties

Keywords

force control; fuzzy control; manipulator dynamics; neurocontrollers; position control; radial basis function networks; robust control; uncertain systems; fuzzy tuning mechanism; fuzzy-neuro force control; fuzzy-neuro position control; radial basis function network controller; robot dynamic model; robot manipulators; robust robot force tracking impedance control; Error correction; Force control; Fuzzy control; Impedance; Manipulator dynamics; Radial basis function networks; Robots; Robust control; Uncertainty; Velocity 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.2005.1614788

Filename

1614788