Adaptive model-based predictive control for cross-phase cavity pressure control in injection molding

Abstract

Injection molding is a manufacturing process for the production of plastic parts. The traditional process control switches between an injection velocity control and a pressure control. If the switchover is not optimal, quality issues occur during production. Additionally, the setup of processes with the traditional process control requires a high setup effort. The objective of cross-phase process control strategies is to reduce both weaknesses by controlling only one process variable during molding. Disadvantages of available cross-phase control approaches are related to the use of multiple empirical models in the controller which have to be adapted manually to the used machine settings. This contribution proposes a novel adaptive cross-phase cavity pressure control concept based on only one nonlinear time-variant model for the entire process. The adaptive approach reduces the setup effort and compensates inaccuracies during modeling, thus avoiding the need to adjust the controller model when machine settings change. Herefore, the controller model is adapted to the time-varying process dynamics by use of an Unscented Kalman Filter which estimates all process states along with an additional lumped parameter. The time-variant model is then used in a Model-based Predictive Controller to track a given cavity pressure reference. For the adaptive concept to operate properly, the estimated parameter must be positive which is ensured by an introduced model tuning parameter (MTP) influencing the convergence behavior of the parameter estimation. The MTP allows not only to taylor the convergence behavior of the parameter estimation for safe operation and good performance but also to rapidly adapt the control topology for new processing conditions, e.g. different machines or part geometries. Tuning guidlines for the MTP are provided, resulting in a setup procedure of greatly reduced effort resulting in an easy-to-follow setup procedure. The controller concept is validated on two different industrial injection molding machines and for two different part geometries showing good reference tracking capabilities with a steady-state error ⩽4bar.