Resin Transfer Molding (RTM) is an important process for manufacturing polymer composite parts. The RTM process involves injections of liquid resin into a closed mold containing fiber preform and subsequent curing.; Consistent mold filling is essential for producing defect-free RTM parts. However, this is often difficult to achieve due to variations in preform permeability, race tracking, and varying resin viscosity. These variations cause uncertainties that significantly affect the filling patterns and the Last Point to Fill (LPF) locations. One of the most serious defects is dry spot. Dry spot is a region that is not wetted by the resin in the final part. A common practice to eliminate the dry spot is to predict the LPF location and place an exit vent at that location. However, due to the aforementioned uncertainties, the LPF may not coincide with the preset exit vent and a dry spot may form.; The objective of this research is to develop adaptive control strategies for RTM by using numerical modeling to account for the aforementioned process uncertainties. A system model that describes the RTM filling process is developed. The system model is characterized by its non-linear time-varying parameters. Adaptive control techniques are applied to regulate the RTM filling pattern. Both direct and indirect adaptive controls are devised.; The performances of the controllers are evaluated in a tube mold and a thin-shell rectangular mold. For the tube mold, the emphasis is on non-isothermal filling control. The objective is to control the filling pattern to follow a predesigned pattern. Disturbances from the permeability variation and temperature are introduced. For the rectangular mold, the controllability of the LPF locations is evaluated under isothermal filling conditions. Effects of preform permeability and race tracking are considered. A wide range of permeability distributions and race-tracking factors is used in the example cases. Two different desired filling patterns are designed. Both direct and indirect adaptive control methodologies are used to regulate the LPF location so that it coincides with the preset exit vent location for various example cases. The results obtained show good performance during adaptive control.
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