A gradient-based strategy for the one-layer RTO + MPC controller |
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| Affiliation: | 1. Departamento de Ingeniería de Sistemas y Automática, Universidad de Sevilla, Escuela Superior de Ingenieros, Camino de los Descubrimientos s/n, 41092 Sevilla, Spain;2. Institute of Technological Development for the Chemical Industry (INTEC), CONICET-Universidad Nacional del Litoral (UNL), Güemes 3450, 3000 Santa Fe, Argentina;3. Department of Chemical Engineering, University of São Paulo, Av. Prof. Luciano Gaulberto, trv 3 380, 61548 São Paulo, Brazil;1. National Research Council, IASI “Antonio Ruberti”, Via dei Taurini 19, 00185 Rome, Italy;2. University of Brescia, Department of Information Engineering, via Branze 38, 25123 Brescia, Italy;1. Division of Cardiology, Department of Medicine, Massachusetts General Hospital; Cardiac MR PET CT Program, Division of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA;2. Division of Sleep and Circadian Disorders, Department of Medicine, Brigham and Women''s Hospital and Harvard Medical School, Boston, Massachusetts, USA;3. Cardiovascular Division, Department of Medicine, Brigham and Women''s Hospital and Harvard Medical School, Boston, Massachusetts, USA;4. Division of Cardiovascular Medicine, University of California San Diego, San Diego, California, USA;5. Department of Radiology, Brigham and Women''s Hospital and Harvard Medical School, Boston, Massachusetts, USA;6. Pulmonary and Critical Care Division, University of California San Diego, San Diego, California, USA;1. Department of Informatics, Agrifood Campus of International Excellence ceiA3, CIESOL Research Center on Solar Energy, University of Almería, 04120 Almería, Spain;2. Department of Automatic Control, Lund University, Box 118, SE-22100 Lund, Sweden;1. Thermal Systems Laboratory, Department of Mechanical Engineering, Pontifical Catholic University of Parana, Nantes, France;2. Cerema, Dter Ouest, Nantes, France;3. LOCIE, UMR CNRS 5271, Université de Savoie, Chambéry, France;4. GEM, UMR CNRS, Ecole Centrale de Nantes, France |
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| Abstract: | In the process industries model predictive controllers (MPC) have the task of controlling the plant ensuring stability and constraints satisfaction, while an economic cost is minimized. Usually the economic objective is optimized by an upper level Real Time Optimizer (RTO) that passes the economically optimal setpoints to the MPC level. The drawback of this structure is the possible inconsistence/unreachability of those setpoints, due to the different models employed by the RTO and the MPC, as well as their different time scales. In this paper an MPC that explicitly integrates the RTO structure into the dynamic control layer is presented. To overcome the complexity of this one-layer formulation a gradient-based approximation is proposed, which provides a low-computational-cost suboptimal solution. |
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| Keywords: | Model predictive control Real time optimization Economic objectives Stability |
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