A neural network approach for robust dynamical control of robot manipulators

Author

Tunali, E. Turhan

Author_Institution

Sch. of Appl. Sci., Nanyang Technol. Univ., Singapore

fYear

1993

fDate

3-6 May 1993

Firstpage

2450

Abstract

A new algorithm for adaptive dynamical control of robot manipulators is proposed. It utilizes a reduced order parameterization together with a computed torque control policy. The teaching signal correlates the total torque with the feedback error. The algorithm was simulated for a three revolute joint robot and various factors such as noisy joint velocity measurements, weaker control, persistency of excitation and choice of learning constants are examined. Implementation issues for parallel processing are discussed

Keywords

adaptive control; manipulator dynamics; neurocontrollers; robust control; torque control; adaptive dynamical control; feedback error; learning constants; neural network approach; noisy joint velocity measurements; parallel processing; reduced order parameterization; robot manipulators; robust dynamical control; three revolute joint robot; torque control policy; total torque; Adaptive control; Education; Heuristic algorithms; Manipulator dynamics; Neural networks; Neurofeedback; Programmable control; Robot control; Robust control; Torque control;

fLanguage

English

Publisher

ieee

Conference_Titel

Circuits and Systems, 1993., ISCAS '93, 1993 IEEE International Symposium on

Conference_Location

Chicago, IL

Print_ISBN

0-7803-1281-3

Type

conf

DOI

10.1109/ISCAS.1993.394260

Filename

394260