In this paper, we develop an economically optimizing Nonlinear Model Predictive Controller (E-NMPC) for a complete spray drying plant with multiple stages. In the E-NMPC the initial state is estimated by an extended Kalman Filter (EKF) with noise covariances estimated by an autocovariance least squares method (ALS). We present a model for the spray drying plant and use this model for simulation as well as for prediction in the E-NMPC. The open-loop optimal control problem in the E-NMPC is solved using the single-shooting method combined with a quasi-Newton Sequential Quadratic programming (SQP) algorithm and the adjoint method for computation of gradients. We evaluate the economic performance when unmeasured disturbances are present. By simulation, we demonstrate that the E-NMPC improves the profit of spray drying by 17% compared to conventional PI control.
|Title of host publication||Preprints of the 9th International Symposium on Advanced Control of Chemical Processes|
|Publisher||International Federation of Automatic Control|
|Publication status||Published - 2015|
|Event||9th International Symposium on Advanced Control of Chemical Processes - Whistler, Canada|
Duration: 7 Jun 2015 → 10 Jun 2015
|Conference||9th International Symposium on Advanced Control of Chemical Processes|
|Period||07/06/2015 → 10/06/2015|
- Nonlinear Model Predictive Control
- Grey-box model
- Spray Drying
Petersen, L. N., Jørgensen, J. B., & Rawlings, J. B. (2015). Economic Optimization of Spray Dryer Operation using Nonlinear Model Predictive Control with State Estimation. In Preprints of the 9th International Symposium on Advanced Control of Chemical Processes (pp. 507-513). International Federation of Automatic Control.