Dynamic Modeling and Optimal Control of Batch Reactors, Based on Structure Approaching Hybrid Neural Networks
Authors:
- 31 March 2011
- journal article
- research article
- Published by American Chemical Society (ACS) in Industrial & Engineering Chemistry Research
- Vol. 50 (10) , 6174-6186
Abstract
No abstract availableKeywords
This publication has 20 references indexed in Scilit:
- Integration of SQP and PSO for optimal planning of harmonic filtersExpert Systems with Applications, 2010
- Dynamic modeling of batch polymerization reactors via the hybrid neural-network rate-function approachChemical Engineering Journal, 2007
- On-line dynamic optimization and control strategy for improving the performance of batch reactorsChemical Engineering and Processing - Process Intensification, 2005
- Hybrid neural network—prior knowledge model in temperature control of a semi-batch polymerization processChemical Engineering and Processing - Process Intensification, 2004
- Optimal control of a fed-batch bioreactor based upon an augmented recurrent neural network modelNeurocomputing, 2002
- Optimization of Batch Polymerization Reactors Using Neural-Network Rate-Function ModelsIndustrial & Engineering Chemistry Research, 2002
- Prediction of polymer quality in batch polymerisation reactors using robust neural networksChemical Engineering Journal, 1998
- Neural modelling of chemical plant using MLP and B-spline networksControl Engineering Practice, 1997
- Modeling chemical processes using prior knowledge and neural networksAIChE Journal, 1994
- Temperature control of exothermic batch reactors using generic model controlIndustrial & Engineering Chemistry Research, 1989