文章基本信息

标题：Closed-loop Formulation for Nonlinear Dynamic Real-time Optimization * * This work is sponsored by the McMaster Advanced Control Consortium (MACC) and the Ministry of Higher Education (MOHE), Malaysia
本地全文：下载
作者：Mohammad Zamry Jamaludin ; Christopher L.E. Swartz
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2016
卷号：49
期号：7
页码：406-411
DOI：10.1016/j.ifacol.2016.07.376
语种：English
出版社：Elsevier
摘要：Dynamic real-time optimization (DRTO) is a higher level online strategy that exploits plant economic potential by making appropriate adjustments to the lower level controller set-point trajectories. In this work, we propose a closed-loop formulation for a nonlinear DRTO calculation in the form of a bilevel programming problem. A nonlinear differential algebraic equation (DAE) system that describes the process dynamic behavior is utilized with an embedded constrained predictive control (MPC) optimization subproblem to generate the approximate closed-loop response dynamics at the primary economic optimization layer. The bilevel DRTO problem is reformulated as a single-level mathematical program with complementarity constraints (MPCC) by replacing the MPC optimization subproblem by its Karush-Kuhn-Tucker (KKT) optimality conditions. We investigate the economics and control performance of the proposed strategy based on a polymer grade transition case study in the presence of plant-model mismatch and a disturbance, and a comparison is made with the application of a linear DRTO prediction model.
关键词：real-time optimizationeconomic optimizationmodel predictive controlcomplementarity constraintsback-off mechanism