A Comparison Study of MIMO Water Wall Model with Linear, MFNN and ESN Models
- Authors
- Moon, Un-Chul; Lim, Jaewoo; Lee, Kwang Y.
- Issue Date
- Mar-2016
- Publisher
- KOREAN INST ELECTR ENG
- Keywords
- Water wall model; Power plant modelling; Power plant identification; Linearization; Multilayer feed-forward neural network; Echo state network
- Citation
- JOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY, v.11, no.2, pp 265 - 273
- Pages
- 9
- Journal Title
- JOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY
- Volume
- 11
- Number
- 2
- Start Page
- 265
- End Page
- 273
- URI
- https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/7192
- DOI
- 10.5370/JEET.2016.11.2.265
- ISSN
- 1975-0102
2093-7423
- Abstract
- A water wall system is one of the most important components of a boiler in a thermal power plant, and it is a nonlinear Multi-Input and Multi-Output (MIMO) system, with 6 inputs and 3 outputs. Three models are developed and comp for the controller design, including a linear model, a multilayer feed-forward neural network (MFNN) model and an Echo State Network (ESN) model. First, the linear model is developed by linearizing a given nonlinear model and is analyzed as a function of the operating point. Second, the MFNN and the ESN are developed by using training data from the nonlinear model. The, three models are validated using Matlab with nonlinear input-output data that was not used during training.
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Collections - College of ICT Engineering > School of Electrical and Electronics Engineering > 1. Journal Articles
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