Simultaneous Process Scheduling and Control: A Multiparametric Programming-Based Approach

被引：40
作者：
Burnak, Bans [1 ,2 ]
Katz, Justin [1 ,2 ]
Diangelakis, Nikolaos A. [1 ,2 ]
Pistikopoulos, Efstratios N. [1 ,2 ]
机构：
[1] Texas A&M Univ, Artie McFerrin Dept Chem Engn, College Stn, TX 77845 USA
[2] Texas A&M Univ, Texas A&M Energy Inst, College Stn, TX 77845 USA
来源：
INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH | 2018年 / 57卷 / 11期
基金：
美国国家科学基金会; 英国工程与自然科学研究理事会;
关键词：
INTEGER DYNAMIC OPTIMIZATION; CLOSED-LOOP IMPLEMENTATION; OPTIMAL GRADE TRANSITION; MODEL-BASED INTEGRATION; CHEMICAL-PROCESSES; PRODUCTION LINES; PROCESS SYSTEMS; PROCESS DESIGN; COMBINED HEAT; UNCERTAINTY;
D O I：
10.1021/acs.iecr.7b04457
中图分类号：
TQ [化学工业];
学科分类号：
0817 ;
摘要：
We present a systematic framework to derive model-based simultaneous strategies for the integration of scheduling and control via multiparametric programming. We develop offline maps of optimal scheduling actions accounting for the closed-loop dynamics of the process through a surrogate model formulation that incorporates the inherent behavior of the control scheme. The surrogate model is designed to translate the long-term scheduling decisions to time varying set points and operating modes in the time scale of the controller. The continuous and binary scheduling decisions are explicitly taken into account in the multiparametric model predictive controllers. We showcase the framework on a stand-alone three-product continuous stirred tank reactor, and two reactors operating in parallel.
引用
收藏
页码：3963 / 3976
页数：14
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