Premium
Batch reactor control using a multiple model‐based controller design
Author(s) -
Krishnan Arun,
Kosanovich Karlene A.
Publication year - 1998
Publication title -
the canadian journal of chemical engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.404
H-Index - 67
eISSN - 1939-019X
pISSN - 0008-4034
DOI - 10.1002/cjce.5450760417
Subject(s) - control theory (sociology) , controller (irrigation) , nonlinear system , computer science , stability (learning theory) , batch reactor , control engineering , work (physics) , state space , state space representation , set (abstract data type) , control (management) , mathematics , engineering , algorithm , chemistry , mechanical engineering , biochemistry , statistics , quantum mechanics , machine learning , programming language , catalysis , physics , artificial intelligence , agronomy , biology
This work presents the development of a model‐based controller design called Multiple Model Predictive Control (MMPC) based on a set of linear, time‐varying, state space models to regulate batch processes according to multiple, pre‐specified reference profiles. Sufficient conditions for stability and boundedness of the dynamic evolution of the forced nonlinear system are provided. The performance of the MMPC design is demonstrated on a model of a batch reactor that represents the production of a polymer product.