PD control of robot with velocity estimation and uncertainties compensation

Author

Yu, Wen ; Li, XiaoOu

Author_Institution

Departamento de Control Automatico, CINVESTAV-IPN, Mexico

Volume

2

fYear

2001

fDate

2001

Firstpage

1162

Abstract

In this paper the normal PD control of the two-link robot is modified in following two ways: (1) A high-gain observer is applied to estimate the joint velocities; (2) The RBF neural networks are used to compensate the gravity and friction. The new PD control may overcome the two drawbacks of the normal PD control. The main contributions of this paper are: a new proof of high-gain observer gives a direct relation between observer gain and observer error. Based on Lyapunov-like analysis, we prove the stability of the closed-loop system if the weights of RBF have certain learning rides and the observer is faster enough

Keywords

Lyapunov methods; closed loop systems; compensation; control system analysis; manipulators; observers; position measurement; radial basis function networks; stability; two-term control; uncertain systems; Lyapunov-like analysis; PD control; RBF neural networks; closed-loop system stability; friction compensation; gravity compensation; high-gain observer; industrial manipulators; joint velocity estimation; two-link robot; uncertainties compensation; Friction; Gravity; Network servers; Neural networks; PD control; Pollution measurement; Position measurement; Robotics and automation; Robots; Uncertainty;

fLanguage

English

Publisher

ieee

Conference_Titel

Decision and Control, 2001. Proceedings of the 40th IEEE Conference on

Conference_Location

Orlando, FL

Print_ISBN

0-7803-7061-9

Type

conf

DOI

10.1109/.2001.981042

Filename

981042