Robust Nonlinear Model Predictive Control for Infrared Drying of Automotive Coatings Available to Purchase

In this paper, a scheme for estimation and control of moisture content in infrared (IR) drying of paints/coatings is proposed. To deal with the infinite-dimensional nature of the process model associated with the moisture diffusion in the coating film, POD-Galerkin method is first applied for model reduction. Then, an unscented Kalman filter (UKF) is devised for distributed moisture content estimation and nonlinear model predictive control (NMPC) system is designed for tracking a desired average moisture content profile with optimized energy needs. To enhance the control performance in the presence of potential modeling uncertainties, a robust design is also included in the proposed NMPC scheme. The effectiveness of this approach is demonstrated via simulated applications to IR drying of automotive waterborne coatings.