DescriptionAdditive manufacturing (or 3D-printing) processes such as fused filament fabrication of polymer constructs and laser based sintering and fusion of metal powder which can produce nearly fully dense parts with complex geometry by following layer-to-layer scanning strategies on feedstock material with pre-specified layer thickness find many applications in industry ranging from prototype fabrication to actual parts and components production.
In this thesis, we study the control schemes that can be developed in improving the extruded polymer consistency in form and temperature, and fused track quality in laser-based melting and fusion by using observable process variables and applying control on controllable variables. Specifically, system identification methods are used to obtain transfer function for Liquefier block in a fused filament fusion systems and simulations are conducted to introduce a suitable control strategy. The control strategy simulations for temperature control of Liquefier block takes in accounts the load to the system (filament feed rate) and a suitable feedback compensator is designed. The Lead-lead feedback compensator has proved to provide faster settling time and negligible steady state error. Also, an XY positioning system is considered for studying the trajectory control using feedback and iterative learning control schemes. The iterative learning control method is found to be very effective in reducing contour error during tracking of trajectories with sharp corners. The results obtained from these studies are expected to provide more information about the additive manufacturing process control which can be used for further validation of modelling studies or for industrial purposes.