Title

Non‐Linear Learning Control Of Robot Manipulators Without Requiring Acceleration Measurement

Keywords

Iterative method; Learning control; Robust control; Trajectory control

Abstract

A new class of non‐linear learning control laws is introduced for a robot manipulator to track a given trajectory in performing a series of tasks. The learning control scheme is applicable to robots with both resolute and prismatic joints, requires only position and velocity feedback, and removes the acceleration measurement required by the existing results. It has been shown that under the proposed learning control the tracking errors are always guaranteed to be asymptotically stable with respect to the number of trials. The proposed control is robust in the sense that exact knowledge about the non‐linear dynamics is not required except for bounding functions on the magnitudes. In addition, the new learning scheme can be used without assumptions such as repeatability of robot motion, repeatability of tasks and resetting of initial tracking errors. Copyright © 1993 John Wiley & Sons, Ltd.

Publication Date

1-1-1993

Publication Title

International Journal of Adaptive Control and Signal Processing

Volume

7

Issue

2

Number of Pages

77-90

Document Type

Article

Identifier

scopus

Personal Identifier

scopus

DOI Link

https://doi.org/10.1002/acs.4480070202

Socpus ID

0027556769 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/0027556769

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