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Process Design and Control Optimization: A Simultaneous Approach by Multi-Parametric Programming
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DOI：10.1002/aic.15825.png)
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Abstract
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We present a framework for the application of design and control optimization via multi-parametric programming through four case studies. We develop design dependent multi-parametric model predictive controllers that are able to provide the optimal control actions as functions of the system state and the design of the process at hand, via our recently introduced PAROC framework (Pistikopoulos et al, Chem Eng Sci. 2015;136:115-138). The process and the design dependent explicit controllers undergo a mixed integer dynamic optimization (MIDO) step for the determination of the optimal design. The result of the MIDO is the optimal design of the process under optimal operation. We demonstrate the framework through case studies of a tank, a continuously stirred tank reactor, a binary distillation column and a residential cogeneration unit. (c) 2017 American Institute of Chemical Engineers
Keywords:
multi-parametric programming
design and control integration
model predictive control
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