Neural adaptive control for positioning fabric on a frictional surface

S. M. Shenoy, Christopher D. Rahn

Research output: Contribution to journalArticle

Abstract

This research focuses on real-time position control for draping fabric sliding on a high friction surface. Although fabrics are usually positioned on smooth surfaces with fixed fabric guides to simplify automated handling, a high friction work surface holds the fabric in place after positioning, allowing accurate assembly of multiple fabric parts without specialized jigs or fixtures. A neural adaptive controller with feedforward friction compensation provides asymptotic tracking for a spring mass model with friction. A test stand and an optical sensor are designed to facilitate real time position measurement and control. The neural adaptive controller demonstrates good position tracking and robustness to fabric property variations relative to open loop or PID control.

Original languageEnglish (US)
Pages (from-to)127-133
Number of pages7
JournalJournal of Manufacturing Science and Engineering, Transactions of the ASME
Volume121
Issue number1
DOIs
StatePublished - Jan 1 1999

Fingerprint

Friction
Position control
Real time control
Jigs
Position measurement
Controllers
Three term control systems
Optical sensors
Time measurement
Robustness (control systems)
Compensation and Redress

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Mechanical Engineering
  • Computer Science Applications
  • Industrial and Manufacturing Engineering

Cite this

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Neural adaptive control for positioning fabric on a frictional surface. / Shenoy, S. M.; Rahn, Christopher D.

In: Journal of Manufacturing Science and Engineering, Transactions of the ASME, Vol. 121, No. 1, 01.01.1999, p. 127-133.

Research output: Contribution to journalArticle

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