Estimation, Control and Optimization of Curing in Thick-Sectioned Composite Parts

A nonlinear model-based control method is proposed and validated for controlling, estimating and optimizing the cure in composite parts. During the cure, the exothermic reaction causes temperature gradients through the thickness that can lead to a nonuniform cure and high residual stress. A predictive control and optimization approach is proposed to ensure that temperature gradients are kept within acceptable limits and the cure state is fairly uniform, regardless of the part thickness. A reduced order process model is derived and used to formulate a dynamic inversion controller. A nonlinear observer is constructed to estimate the unknown temperature and cure states within the composite. An on-line optimizer determines the maximum allowable heating rate. The optimizer is run at discrete intervals throughout the process to account for process and part variability. The control, estimation and optimization algorithms were validated through a series of simulations and experiments of composite parts cured in a press. Parts that were cured with the proposed control method were compared with parts cured following a manufacturer’s recommended cure cycle. The results demonstrate the success of the proposed control method in achieving uniform temperature and cure, and in decreasing the residual stress, without increasing cycle time.