Structural network modeling and control of rigid body robots

Author

Ge, S.S. ; Hang, C.C.

Author_Institution

Dept. of Electr. Eng., Nat. Univ. of Singapore, Singapore

Volume

14

Issue

5

fYear

1998

fDate

10/1/1998 12:00:00 AM

Firstpage

823

Lastpage

827

Abstract

In this paper, two new parametric network models of robots are presented based on the systems´ own functions. The complete dynamics of robots are given in a ready-to-used format which is constructed by finite dimensional static parametric networks for the inertia matrix and the potential energy (or the gravitational forces). As a result, dynamic models of robots can be automatically generated by software once given the number of degrees of freedom (DOF) and the sequence of the joint types, without knowing other parameters such as the lengths and the twist angles of the links. An existing adaptive controller is used as an example to show that some of the controllers can be easily modified such that adaptive controllers can be automatically generated. It is shown that all the closed-loop signals are bounded and tracking error goes to zero

Keywords

adaptive control; closed loop systems; control system synthesis; manipulator dynamics; multidimensional systems; adaptive controller; closed-loop signals; finite dimensional static parametric networks; gravitational forces; inertia matrix; parametric network models; potential energy; rigid body robot control; robot dynamics; structural network modeling; tracking error; twist angles; Adaptive control; Automatic control; Automatic generation control; Neural networks; Potential energy; Programmable control; Robotics and automation; Robots; Sliding mode control; Torque control;

fLanguage

English

Journal_Title

Robotics and Automation, IEEE Transactions on

Publisher

ieee

ISSN

1042-296X

Type

jour

DOI

10.1109/70.720358

Filename

720358