Abstract
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.
Original language | English |
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Title of host publication | Preprints of the 9th International Symposium on Advanced Control of Chemical Processes |
Publisher | International Federation of Automatic Control |
Publication date | 2015 |
Pages | 507-513 |
Publication status | Published - 2015 |
Event | 9th International Symposium on Advanced Control of Chemical Processes - Whistler, Canada Duration: 7 Jun 2015 → 10 Jun 2015 http://adchem2015.org/ |
Conference
Conference | 9th International Symposium on Advanced Control of Chemical Processes |
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Country/Territory | Canada |
City | Whistler |
Period | 07/06/2015 → 10/06/2015 |
Internet address |
Keywords
- Nonlinear Model Predictive Control
- Optimization
- Grey-box model
- Spray Drying