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contributor authorG. A. Larsen
contributor authorA. Donmez
contributor authorS. Cetinkunt
date accessioned2017-05-08T23:46:47Z
date available2017-05-08T23:46:47Z
date copyrightSeptember, 1995
date issued1995
identifier issn0022-0434
identifier otherJDSMAA-26216#415_1.pdf
identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/115060
description abstractPrecision requirements in ultra-precision machining are often given in the order of micrometers or sub-micrometers. Machining at these levels requires precise control of the position and speed of the machine tool axes. Furthermore, in machining of brittle materials, extremely low feed rates of the machine tool axes are required. At these low feed rates there is a large and erratic friction characteristic in the drive system which standard PID controllers are unable to deal with. In order to achieve the desired accuracies, friction must be accurately compensated in the real-time servo control algorithm. A learning controller based on the CMAC algorithm is studied for this task.
publisherThe American Society of Mechanical Engineers (ASME)
titleCMAC Neural Network Control for High Precision Motion Control in the Presence of Large Friction
typeJournal Paper
journal volume117
journal issue3
journal titleJournal of Dynamic Systems, Measurement, and Control
identifier doi10.1115/1.2799133
journal fristpage415
journal lastpage420
identifier eissn1528-9028
keywordsFriction
keywordsMotion control
keywordsAccuracy
keywordsArtificial neural networks
keywordsMachining
keywordsMachine tools
keywordsControl equipment
keywordsAlgorithms
keywordsServomechanisms AND Brittleness
treeJournal of Dynamic Systems, Measurement, and Control:;1995:;volume( 117 ):;issue: 003
contenttypeFulltext


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