Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor | Multi-disciplinary Studies | en_US |
| dc.contributor | Department of Electrical Engineering | en_US |
| dc.creator | Mo, Kwok-wai Edmond | - |
| dc.identifier.uri | https://theses.lib.polyu.edu.hk/handle/200/3333 | - |
| dc.language | English | en_US |
| dc.publisher | Hong Kong Polytechnic University | - |
| dc.rights | All rights reserved | en_US |
| dc.title | Identification of boiler using artificial neural network | en_US |
| dcterms.abstract | This report presents the application of artificial neural networks in modeling the dynamic behavior of three major operation parameters of a 350 MW radiant reheat, controlled circulation drum boiler. Major parameters include main steam pressure, drum level and excess air level. Neural network is designed base on converting their linear transfer function to discrete time model, and the model is trained using three different algorithm including Backpropagation, Levenberg Marquardt and Linear Least Square Algorithm. Evaluation and validation of the models are performed by predicting the dynamic behavior using different sets of actual plant data. The result indicated that the neural network model is shown to be capable of providing accurate predictions. Further, based on performance among three training algorithms which indicated that Levenberg Marquardt algorithm shows the fastest convergence time, a Neural Network Controller is built by applying the algorithm with Internal Mode Control (IMC) strategy, and controllability of the controller is examined and the controlled response indicated Neural Network could be applied in both system identification as well as in control engineering. | en_US |
| dcterms.alternative | System identification of boiler using artificial neural network | - |
| dcterms.extent | iv, 72, [3] leaves : ill. ; 30 cm | en_US |
| dcterms.isPartOf | PolyU Electronic Theses | en_US |
| dcterms.issued | 1998 | en_US |
| dcterms.educationalLevel | All Master | en_US |
| dcterms.educationalLevel | M.Sc. | en_US |
| dcterms.LCSH | Boilers | en_US |
| dcterms.LCSH | System identification | en_US |
| dcterms.LCSH | Neural networks (Computer science) | en_US |
| dcterms.LCSH | Hong Kong Polytechnic University -- Dissertations | en_US |
| dcterms.accessRights | restricted access | en_US |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| b14418678.pdf | For All Users (off-campus access for PolyU Staff & Students only) | 2.6 MB | Adobe PDF | View/Open |
Copyright Undertaking
As a bona fide Library user, I declare that:
- I will abide by the rules and legal ordinances governing copyright regarding the use of the Database.
- I will use the Database for the purpose of my research or private study only and not for circulation or further reproduction or any other purpose.
- I agree to indemnify and hold the University harmless from and against any loss, damage, cost, liability or expenses arising from copyright infringement or unauthorized usage.
By downloading any item(s) listed above, you acknowledge that you have read and understood the copyright undertaking as stated above, and agree to be bound by all of its terms.
Please use this identifier to cite or link to this item:
https://theses.lib.polyu.edu.hk/handle/200/3333