Title
Trajectory tracking performance in task space of robot manipulators: an adaptive neural controller design
Abstract
An adaptive neural network control design for robot manipulators in task space coordinates is provided in this paper. This controller design and a direct adaptive control strategy (passivity-based controller) are simulated for the same trajectory, considering the presence of the friction torques and the influence of payload. Performances are evaluated according to behavior of position tracking, and to trajectory tracking accuracy. The adaptive neural network controller is developed based on a neural network modeling technique which neither requires the evaluation of inverse dynamical model nor the time-consuming training process, and does not require the inverse of the Jacobian matrix.
Year
DOI
Venue
2005
10.1109/IROS.2005.1545309
Intelligent Robots and Systems, 2005.
Keywords
Field
DocType
adaptive control,control system synthesis,manipulators,neurocontrollers,position control,torque control,tracking,adaptive neural network control design,friction torque,passivity-based controller,position tracking,robot manipulator,task space,trajectory tracking,Adaptive Control,Friction Torques,Neural Networks,Robot Manipulators,Task Space
Passivity,Control theory,Torque,Jacobian matrix and determinant,Computer science,Control theory,Control engineering,Adaptive control,Artificial neural network,Trajectory,Payload
Conference
ISBN
Citations 
PageRank 
0-7803-8912-3
1
0.37
References 
Authors
5
6