Predictive control of sheet- and film-forming processes

A constrained infinite-horizon model-predictive controller is advocated to improve product properties from sheet- and film-forming processes by feedback control; the proposed model structure captures the main characteristics of the process, including the scanning sensor and large time delay. Model parameters are identified from process data, and symmetry is enforced to improve the parameter estimates. The film thickness is estimated from sparse measurements using a periodic Kalman filter. The covariances of the estimates are used to evaluate scanning patterns. Integrating disturbance models are used to achieve offset free control. Detectability conditions are presented for both models to ensure that the disturbances can be estimated from the measurement. Once the state of the film is reconstructed adequately from the measurement, a control strategy can be implemented to improve film properties. One important control contribution is to enable the controller to handle hard constraints on the actuators without clipping the controller output signal. The target-tracking problem is discussed, and the uniqueness of the steady-state solution is established. By simulations an output disturbance model is compared with a measured input disturbance model.