NDLI: Application of Evolutionary Learning in Wiener Neural Identification and Predictive Control of a Plug-Flow Tubular Reactor

Content Provider	IEEE Xplore Digital Library
Author	Arefi, M.M. Montazeri, A. Jahed-Motlagh, M.R. Poshtan, J.
Copyright Year	2007
Description	Author affiliation: Iran Univ. of Sci. & Technol., Tehran (Arefi, M.M.; Montazeri, A.)
Abstract	In this paper, identification and nonlinear model predictive control of highly nonlinear plug-flow tubular reactor based on Wiener model is studied. This process simulated in a rather realistic environment by HYSYS, and the obtained data is in connection with MATLAB for identification and control purpose. The process is identified with NN-Wiener identification method, and two linear and nonlinear model predictive controllers are applied with the ability of rejecting slowly varying unmeasured disturbance. Since the identification problem must be solved with a nonlinear optimization method, to attain the best possible model for prediction genetic algorithm is used. The Simulation results show that the obtained Wiener model has a good capability to predict the step response of the process. The results for control are also compared with a common PI controller for temperature control of tubular reactor. It is shown that the nonlinear controller has the fastest damped response in comparison with the other two controllers.
Starting Page	644
Ending Page	650
File Size	4157637
Page Count	7
File Format	PDF
ISBN	1424407834
ISSN	1553572X
DOI	10.1109/IECON.2007.4460273
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-11-05
Publisher Place	Taiwan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Predictive control Inductors Mathematical model Predictive models Neural networks Continuous-stirred tank reactor Optimal control Open loop systems Temperature control Inverse problems
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Real-time identification and control of a continuous stirred tank reactor with neural network

Neural net based model predictive control of a chaotic continuous solution polymerization reactor

Nonlinear Model Predictive Control of Chemical Processes with a Wiener Identification Approach

Temperature control for chemical reactor using adaptive neural network control strategy

Nonlinear internal model control and model predictive control using neural networks

Performance Evaluation of a Distributed MPC Strategy Applied to the Continuous Stirred Tank Reactor

Predictive Control Based on Neural Networks of The Chemical Process

Neurofuzzy model based l/sub /spl infin// predictive control of nonlinear CSTR system

Optimal control of nonlinear exothermic reactor

Application of Evolutionary Learning in Wiener Neural Identification and Predictive Control of a Plug-Flow Tubular Reactor

Similar Documents

Real-time identification and control of a continuous stirred tank reactor with neural network

Neural net based model predictive control of a chaotic continuous solution polymerization reactor

Nonlinear Model Predictive Control of Chemical Processes with a Wiener Identification Approach

Temperature control for chemical reactor using adaptive neural network control strategy

Nonlinear internal model control and model predictive control using neural networks

Performance Evaluation of a Distributed MPC Strategy Applied to the Continuous Stirred Tank Reactor

Predictive Control Based on Neural Networks of The Chemical Process

Neurofuzzy model based l/sub /spl infin// predictive control of nonlinear CSTR system

Optimal control of nonlinear exothermic reactor

Application of Evolutionary Learning in Wiener Neural Identification and Predictive Control of a Plug-Flow Tubular Reactor