Neural adaptive control for positioning fabric on a frictional surface

This research focuses on real-time position control for draping fabric slid ing 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, all owing accurate assembly of multiple fabric parts without specialized jigs o r fixtures. A neural adaptive controller with feedforward friction compensa tion provides asymptotic tracking for a spring mass model with friction. A test stand and an optical sensor are designed to facilitate real time posit ion measurement and control. The neural adaptive controller demonstrates go od position tracking and robustness to fabric properly variations relative to open loop or PID control.