Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/13421
Title: Modeling, simulation and control of periodic reactor systems
Authors: SUKUMAR BALAJI
Keywords: Modeling, Periodic Systems, Scaling Analysis, Repetitive Control, Methane Combustion
Issue Date: 13-Nov-2007
Source: SUKUMAR BALAJI (2007-11-13). Modeling, simulation and control of periodic reactor systems. ScholarBank@NUS Repository.
Abstract: Fugitive methane emissions are generally combusted before being vented into the atmosphere. Special types of autothermal reactors like Reverse Flow Reactors (RFR), Multi Port Switching Reactors (MPSR) are eminently suited for this purpose. However, their operation and control can be quite complex and challenging. The focus of this research has been in developing suitable operational and control strategies for such systems with a view to make the periodic reactor systems attractive for industrial production. A two dimensional heterogeneous model deduced from first principles has been solved using the Multiphysics Modeling software COMSOL (using Finite Element Method). Using the proposed model equations, the performance of RFR and MPSR were compared. Based on this observation, a new reactor configuration has been proposed which is shown to be efficient even under drastically changing operating conditions. Extensive studies on the amount of useful heat that can be removed from the system without losing the sustainability or damaging the catalyst have also been accomplished. This concept of finding benefits from waste is surely a more attractive option from industrial view point. Theoretical studies (Scaling Analysis) on the model equations have also been carried out to provide additional insights into the RFR operation. As the complexity of the system demanded advanced control strategies for enhanced performance, a novel Repetitive Model Predictive Control (RMPC) strategy, that combines the basic concepts of Iterative Learning Control (ILC) and Repetitive Control (RC) alongwith the concepts of Model Predictive Control (MPC) is proposed and successfully tested for such systems.
URI: http://scholarbank.nus.edu.sg/handle/10635/13421
Appears in Collections:Ph.D Theses (Open)

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