Design of Nonlinear Model-Based Control Using Bifurcation Analysis for Solution Polymerizations Carried Out in Lumped-Distributed Reactors

被引:4
作者
Vega, Marcia P. [1 ]
Oliveira, Gabrielle F. M. [1 ]
Lima, Enrique L. [2 ]
Pinto, Jose Carlos [2 ]
机构
[1] Univ Fed Rural Rio de Janeiro, Dept Engn Quim, BR 465,Km 7, BR-23890000 Seropedica, RJ, Brazil
[2] Univ Fed Rio de Janeiro, COPPE, Programa Engn Quim, Cidade Univ,CP 68502, Rio De Janeiro, Brazil
关键词
bifurcation diagram; neural network; nonlinear model predictive control; polymerization; stability analyses; INTRINSIC-VISCOSITY; MOLECULAR-WEIGHT; IDENTIFICATION; REDUCTION; STABILITY; DYNAMICS;
D O I
10.1002/mren.201700028
中图分类号
TQ [化学工业];
学科分类号
0817 ;
摘要
In order to implement nonlinear control, nonlinear system identification must be performed, however, there are open questions concerning this field of process control, for example, experimental planning, model structure selection, parameter estimation, and validation. Therefore, the study of nonlinear model identification is a relevant unsolved problem that needs to be handled for nonlinear control synthesis. This paper presents the use of bifurcation theory, dynamic and stability analysis for nonlinear identification, and control of polymerization reactors. Peroxide-initiated styrene-solution polymerization reactors (lumped-distributed) are investigated: batch, continuous stirred-tank reactor (CSTR), and tubular reactors. Open and closed loop analyses are carried out using jacket temperature and weight average molecular weight setpoints as the bifurcation parameters. Phenomenological mathematical models, neural network nonlinear models, and an experimental data from a polymerization unit are employed for validating the proposed methodology in order to implement confident nonlinear controllers.
引用
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页数:11
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