Integrated process design, scheduling, and control using multiparametric programming Academic Article

abstract

• 2019 Elsevier Ltd A unified theory and framework for the integration of process design, control, and scheduling based on a single high fidelity model is presented. The framework features (i) a mixed-integer dynamic optimization (MIDO) formulation with design, scheduling, and control considerations, and (ii) a multiparametric optimization strategy for the derivation of offline/explicit maps of optimal receding horizon policies. Explicit model predictive control schemes are developed as a function of design and scheduling decisions, and similarly design dependent scheduling policies are derived accounting for the closed-loop dynamics. Inherent multi-scale gap issues are addressed by an offline design dependent surrogate model. The proposed framwork is illustrated by two example problems, a system of two continuous stirred tank reactor, and a small residential combined heat and power (CHP) network.

authors

• Pistikopoulos, Stratos

published proceedings

• COMPUTERS & CHEMICAL ENGINEERING

author list (cited authors)

• Burnak, B., Diangelakis, N. A., Katz, J., & Pistikopoulos, E. N.

citation count

• 40

complete list of authors

• Burnak, Baris||Diangelakis, Nikolaos A||Katz, Justin||Pistikopoulos, Efstratios N

publication date

• June 2019

publisher

• Elsevier  Publisher

published in

• Computers and Chemical Engineering  Journal

keywords

• Enterprise-wide Optimization
• Integration
• Model Predictive Control
• Multi-parametric Programming
• Process Design
• Process Scheduling

Digital Object Identifier (DOI)

• 10.1016/j.compchemeng.2019.03.004

start page

• 164

end page

• 184

volume

• 125