Model-based multi-parametric programming strategies towards the integration of design, control and operational optimization
File(s)
Author(s)
Diangelakis, Nikolaos
Type
Thesis or dissertation
Abstract
This thesis discusses recent advances towards the grand unification of process design, con- trol and operational optimization via multi-parametric programming techniques. First the PARametric Optimization and Control (PAROC) framework is presented together with a prototype implementation for the development of advanced receding horizon policies via multi-parametric programming and their closed-loop implementation. It is shown how state- of-the-art multi-parametric programming algorithms are utilized for the development of explicit optimization policies for a variety of problems (including control, estimation and scheduling) based on high-fidelity models and model approximation steps.
Two developments are presented towards the integration of design, control and opera- tional optimization within PAROC; (i) the integration of design and control and (ii) the integration of scheduling and control. For (i) we develop receding horizon optimization for- mulations where the design variables are simultaneously considered, resulting in explicit, design–dependent policies which are then included within a Mixed-Integer Dynamic Opti- mization (MIDO) algorithm minimizing operational and investment costs. For (ii), we de- velop scheduling strategies where the process dynamics and corresponding controller designs are simultaneously considered, resulting in explicit control–dependent scheduling schemes. Surrogate/approximate models are proposed to address the time–scale mismatch between the mid–term schedule and the short–term control optimization problem. Finally, the inte- gration of (i) and (ii) is shown within an overall dynamic optimization problem.
The developments are presented via a domestic cogeneration heat and power (CHP) system example and case studies of a tank, a continuously stirred tank reactor and a binary distillation column.
Two developments are presented towards the integration of design, control and opera- tional optimization within PAROC; (i) the integration of design and control and (ii) the integration of scheduling and control. For (i) we develop receding horizon optimization for- mulations where the design variables are simultaneously considered, resulting in explicit, design–dependent policies which are then included within a Mixed-Integer Dynamic Opti- mization (MIDO) algorithm minimizing operational and investment costs. For (ii), we de- velop scheduling strategies where the process dynamics and corresponding controller designs are simultaneously considered, resulting in explicit control–dependent scheduling schemes. Surrogate/approximate models are proposed to address the time–scale mismatch between the mid–term schedule and the short–term control optimization problem. Finally, the inte- gration of (i) and (ii) is shown within an overall dynamic optimization problem.
The developments are presented via a domestic cogeneration heat and power (CHP) system example and case studies of a tank, a continuously stirred tank reactor and a binary distillation column.
Version
Open Access
Date Issued
2016-12
Date Awarded
2017-07
Advisor
Pistikopoulos, Efstratios
Mantalaris, Sakis
Publisher Department
Chemical Engineering
Publisher Institution
Imperial College London
Qualification Level
Doctoral
Qualification Name
Doctor of Philosophy (PhD)