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Neural Network Based Multi Stage Modelling of Chylla Haase Polymerization Reactor
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Vasanthi Damodaran
Veröffentlicht/Copyright:
27. September 2012
Abstract
An accurate semi batch process model should be a nonlinear dynamic model. Neural networks are suitable for modelling nonlinear dynamics and can be used for developing empirical models of semi batch processes. Multi stage neural network based modelling of the polymerization reactor described by Chylla and Haase, is illustrated in this paper. The process is divided into three regions namely heat up period, feed period and hold period and neural model is developed for each stage. This method of multi stage modelling captures the dynamics of the process accurately for the semi batch process. At different stages respective neural model is active based on the period of operation.
Published Online: 2012-9-27
©2012 Walter de Gruyter GmbH & Co. KG, Berlin/Boston
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Artikel in diesem Heft
- Article
- Optimization of Pumping Schedules Using the Genealogical Decision Tree Approach
- Response Surface Modeling and Optimization of Immobilized Candida antarctica Lipase-Catalyzed Production of Dicarboxylic Acid Ester
- Search for Optimum Operating Conditions for a Water Purification Process Integrated to a Heat Transformer with Energy Recycling using Artificial Neural Network Inverse Solved by Genetic and Particle Swarm Algorithms
- Generic Mathematical Model for PSA Process
- A Combined Computational Fluid Dynamics and Artificial Neural Networks Model for Distillation Point Efficiency
- Multi-level Reactor Optimisation in the Conceptual Design of Processes with Heterogeneous Catalytic Reactors
- ANN and ANFIS Models for COP Prediction of a Water Purification Process Integrated to a Heat Transformer with Energy Recycling
- Adsorption of Cadmium on Gel Combustion Derived Nano ZnO
- Smith Predictor Based Parallel Cascade Control Strategy for Unstable Processes with Application to a Continuous Bioreactor
- Application of box-behnken design to the extraction of flavonoid fraction of Schizophyllum commune and the empirical kinetic study
- Sewage Sludge to Energy - A Simulation Study
- A Modified Kennard-Stone Algorithm for Optimal Division of Data for Developing Artificial Neural Network Models
- Particle swarm optimization technique for the optimal design of shell and tube heat exchangers
- Neural Network Based Multi Stage Modelling of Chylla Haase Polymerization Reactor
