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The Pistikopoulos Research Group is organizing a workshop on Multi-parametric Optimization and Control at the 12th IFAC Symposium on Dynamics and Control of Process Systems, including Biosystems (DYCOPS 2019), held in Florianópolis, Brazil, on 23-26 April, 2019. The workshop will be held on Tuesday, April 23, 2019.
The Pistikopoulos Research Group is organizing a workshop on Multi-parametric Optimization and Control at the 12th IFAC Symposium on Dynamics and Control of Process Systems, including Biosystems (DYCOPS 2019), held in Florianópolis, Brazil, on 23-26 April, 2019. The workshop will be held on Tuesday, April 23, 2019.
Workshop Description
Workshop Description
Model based multi-parametric optimization provides a complete map of solutions of an optimization problem as a function of, unknown but bounded, parameters in the model, in a computationally efficient manner, without exhaustively enumerating the entire parameter space. In a Model-based Predictive Control (MPC) framework, multi-parametric optimization can be used to obtain the governing control laws – the optimal control variables as an explicit function of the state variables. The main advantage of this approach is that it reduces the repetitive on-line control and optimization to simple function evaluations, which can be implemented on simple computational hardware, such as a microchip, thereby opening avenues for many applications in chemical, energy, automotive, and biomedical equipment, devices and systems.
Model based multi-parametric optimization provides a complete map of solutions of an optimization problem as a function of, unknown but bounded, parameters in the model, in a computationally efficient manner, without exhaustively enumerating the entire parameter space. In a Model-based Predictive Control (MPC) framework, multi-parametric optimization can be used to obtain the governing control laws – the optimal control variables as an explicit function of the state variables. The main advantage of this approach is that it reduces the repetitive on-line control and optimization to simple function evaluations, which can be implemented on simple computational hardware, such as a microchip, thereby opening avenues for many applications in chemical, energy, automotive, and biomedical equipment, devices and systems.
In this half-day workshop, we will first provide a historical progress report of the key developments in multi-parametric optimization and control. We will then describe PAROC, a systematic framework and prototype software system which allows for the representation, modelling and solution of integrated design, operation and advanced control problems. Its main features include: (i) a high-fidelity dynamic model representation, also involving global sensitivity analysis, parameter estimation and mixed integer dynamic optimization capabilities; (ii) a suite/toolbox of model approximation methods; (iii) a host of multi-parametric programming solvers (POP parametric Optimization] for mixed continuous/integer problems; (iv) a state-space modelling representation capability for scheduling and control problems; and (v) an advanced control toolkit for multi-parametric/explicit MPC and receding horizon estimation/scheduling problems. Algorithms that enable the integration capabilities for design, scheduling and control are presented along with applications in sustainable energy systems, smart manufacturing and process intensification.
In this half-day workshop, we will first provide a historical progress report of the key developments in multi-parametric optimization and control. We will then describe PAROC, a systematic framework and prototype software system which allows for the representation, modelling and solution of integrated design, operation and advanced control problems. Its main features include: (i) a high-fidelity dynamic model representation, also involving global sensitivity analysis, parameter estimation and mixed integer dynamic optimization capabilities; (ii) a suite/toolbox of model approximation methods; (iii) a host of multi-parametric programming solvers (POP parametric Optimization] for mixed continuous/integer problems; (iv) a state-space modelling representation capability for scheduling and control problems; and (v) an advanced control toolkit for multi-parametric/explicit MPC and receding horizon estimation/scheduling problems. Algorithms that enable the integration capabilities for design, scheduling and control are presented along with applications in sustainable energy systems, smart manufacturing and process intensification.
Instructors
Instructors
Detailed Program (4h)
Detailed Program (4h)
08:00-09:00 Introduction to multi-parametric optimization and explicit model predictive control – An Overview
08:00-09:00 Introduction to multi-parametric optimization and explicit model predictive control – An Overview
09:00-10:00 Parametric OPtimization (POP) Toolbox (http://parametric.tamu.edu/POP/) – Hands on demonstration
09:00-10:00 Parametric OPtimization (POP) Toolbox (http://parametric.tamu.edu/POP/) – Hands on demonstration
10:00-10:15 Coffee Break
10:00-10:15 Coffee Break
10:15-11:15 The PARametric Optimization & Control (PAROC) Framework and Software Prototype (http://paroc.tamu.edu/)
10:15-11:15 The PARametric Optimization & Control (PAROC) Framework and Software Prototype (http://paroc.tamu.edu/)
11:15-12:30 Hands on demonstration of PAROC on specific applications and example problems
11:15-12:30 Hands on demonstration of PAROC on specific applications and example problems
A copy with selected chapters of the forthcoming book “Pistikopoulos, E. N., Diangelakis, N. A., Oberdieck, R. Multi-parametric Optimization and Control, Wiley-VCH” will be provided.
A copy with selected chapters of the forthcoming book “Pistikopoulos, E. N., Diangelakis, N. A., Oberdieck, R. Multi-parametric Optimization and Control, Wiley-VCH” will be provided.
Selected References
Selected References
1. Oberdieck, R., Diangelakis, N. A., Papathanasiou, M. M., Nascu, I., Pistikopoulos, E. N. POP–Parametric OPtimization Toolbox. Industrial & Engineering Chemistry Research, 2016, 55(33), 8979-8991.
1. Oberdieck, R., Diangelakis, N. A., Papathanasiou, M. M., Nascu, I., Pistikopoulos, E. N. POP–Parametric OPtimization Toolbox. Industrial & Engineering Chemistry Research, 2016, 55(33), 8979-8991.
2. Pistikopoulos, E. N., Diangelakis, N. A., Oberdieck, R., Papathanasiou, M. M., Nascu, I., Sun, M. PAROC–An integrated framework and software platform for the optimisation and advanced model-based control of process systems. Chemical Engineering Science, 2015, 136, 115-138.
2. Pistikopoulos, E. N., Diangelakis, N. A., Oberdieck, R., Papathanasiou, M. M., Nascu, I., Sun, M. PAROC–An integrated framework and software platform for the optimisation and advanced model-based control of process systems. Chemical Engineering Science, 2015, 136, 115-138.
3. Papathanasiou, M. M., Avraamidou, S., Steinebach, F., Oberdieck, R., Mueller-Spaeth, T., Morbidelli, M., Mantalaris, A., Pistikopoulos, E. N. Advanced control strategies for the multicolumn countercurrent solvent gradient purification process. AIChE Journal, 2016, 62(7), 2341-2357.
3. Papathanasiou, M. M., Avraamidou, S., Steinebach, F., Oberdieck, R., Mueller-Spaeth, T., Morbidelli, M., Mantalaris, A., Pistikopoulos, E. N. Advanced control strategies for the multicolumn countercurrent solvent gradient purification process. AIChE Journal, 2016, 62(7), 2341-2357.
4. Diangelakis, N. A., Burnak, B., Katz, J., Pistikopoulos, E. N. Process design and control optimization: A simultaneous approach by multi‐parametric programming. AIChE Journal, 2017, 63(11), 4827-4846.
4. Diangelakis, N. A., Burnak, B., Katz, J., Pistikopoulos, E. N. Process design and control optimization: A simultaneous approach by multi‐parametric programming. AIChE Journal, 2017, 63(11), 4827-4846.
More Information
More Information
DYCOPS2019 - Workshop.pdfContact
Contact
Please feel free to contact us by sending an e-mail at ipappas@tamu.edu.
Please feel free to contact us by sending an e-mail at ipappas@tamu.edu.
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