Towards the integration of process design, control and scheduling: Are we getting closer?
•Integration of design, scheduling and control.•Framework for the development and closed loop validation of advanced receding horizon policies.•Dynamic optimization via gPROMS with embedded multi-parametric receding horizon policies.•Advanced multi-parametric model predictive control schemes.•State-...
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| Vydáno v: | Computers & chemical engineering Ročník 91; s. 85 - 92 |
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| Médium: | Journal Article |
| Jazyk: | angličtina |
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Elsevier Ltd
01.08.2016
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| ISSN: | 0098-1354, 1873-4375 |
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| Abstract | •Integration of design, scheduling and control.•Framework for the development and closed loop validation of advanced receding horizon policies.•Dynamic optimization via gPROMS with embedded multi-parametric receding horizon policies.•Advanced multi-parametric model predictive control schemes.•State-space scheduling representation and multi-parametric optimization solution.
The integration of design and control, control and scheduling and design, control and scheduling, all have been core PSE challenges. While significant progress has been achieved over the years, it is fair to say that at the moment there is not a generally accepted methodology and/or “protocol” for such an integration – it is also interesting to note that currently, there is not a commercially available software [or even in a prototype form] system to fully support such an activity.
Here, we present the foundations for such an integrated framework and especially a software platform that enables such integration based on research developments over the last 25 years. In particular, we describe PAROC, a prototype software system which allows for the representation, modeling and solution of integrated design, scheduling and 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 for mixed continuous/integer problems; (iv) a state-space modeling representation capability for scheduling and control problems; and (v) an advanced toolkit for multi-parametric/explicit Model Predictive Control and moving horizon reactive scheduling problems. Algorithms that enable the integration capabilities of the systems for design, scheduling and control are presented on a case of a series of cogeneration units. |
|---|---|
| AbstractList | •Integration of design, scheduling and control.•Framework for the development and closed loop validation of advanced receding horizon policies.•Dynamic optimization via gPROMS with embedded multi-parametric receding horizon policies.•Advanced multi-parametric model predictive control schemes.•State-space scheduling representation and multi-parametric optimization solution.
The integration of design and control, control and scheduling and design, control and scheduling, all have been core PSE challenges. While significant progress has been achieved over the years, it is fair to say that at the moment there is not a generally accepted methodology and/or “protocol” for such an integration – it is also interesting to note that currently, there is not a commercially available software [or even in a prototype form] system to fully support such an activity.
Here, we present the foundations for such an integrated framework and especially a software platform that enables such integration based on research developments over the last 25 years. In particular, we describe PAROC, a prototype software system which allows for the representation, modeling and solution of integrated design, scheduling and 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 for mixed continuous/integer problems; (iv) a state-space modeling representation capability for scheduling and control problems; and (v) an advanced toolkit for multi-parametric/explicit Model Predictive Control and moving horizon reactive scheduling problems. Algorithms that enable the integration capabilities of the systems for design, scheduling and control are presented on a case of a series of cogeneration units. The integration of design and control, control and scheduling and design, control and scheduling, all have been core PSE challenges. While significant progress has been achieved over the years, it is fair to say that at the moment there is not a generally accepted methodology and/or "protocol" for such an integration - it is also interesting to note that currently, there is not a commercially available software [or even in a prototype form] system to fully support such an activity. Here, we present the foundations for such an integrated framework and especially a software platform that enables such integration based on research developments over the last 25 years. In particular, we describe PAROC, a prototype software system which allows for the representation, modeling and solution of integrated design, scheduling and 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 for mixed continuous/integer problems; (iv) a state-space modeling representation capability for scheduling and control problems; and (v) an advanced toolkit for multi-parametric/explicit Model Predictive Control and moving horizon reactive scheduling problems. Algorithms that enable the integration capabilities of the systems for design, scheduling and control are presented on a case of a series of cogeneration units. |
| Author | Diangelakis, Nikolaos A. Pistikopoulos, Efstratios N. |
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| Keywords | Control Integration Multi-parametric receding horizon policies Optimal scheduling Design optimization |
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