文章基本信息

标题：Successive Linearization based Stochastic Model Predictive Control for batch processes described by DAEs
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作者：Laxman Leema Atmaram ; Hariprasad Kodamana
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2020
卷号：53
期号：1
页码：380-385
DOI：10.1016/j.ifacol.2020.06.064
语种：English
出版社：Elsevier
摘要：This paper presents a formulation of Stochastic Model Predictive Control (SMPC) for control of batch processes modeled by nonlinear Differential algebraic Equations (DAEs). In presence of additive stochastic disturbances, states become stochastic variables and measurements are also corrupted with noise. Hence, to obtain refined state estimates we employ DAE-Extended Kalman Filter (EKF). Linear prediction model obtained by successive linearization is used in the SMPC formulation. Our proposed SMPC solves a chance constrained optimization problem in receding horizon window to calculate future control moves with pre-specified degree of constraint violation for trajectory tracking. Further, the probabilistic constraints are converted to hard constraints by accommodating necessary back-off. We present a simulation case study of batch transesterification reactor modeled by non-linear DAEs to validate the proposed SMPC framework.
关键词：Stochastic Model predictive control;Successive linearization;DAE-EKF;batch processes