Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/81415
Title: Fast valving control using radial-basis function neural network
Authors: Chen, Qi
Tan, Shaohua 
Han, Yingdao
Wang, Zonghong
Issue Date: 1995
Citation: Chen, Qi,Tan, Shaohua,Han, Yingdao,Wang, Zonghong (1995). Fast valving control using radial-basis function neural network. IEEE International Conference on Neural Networks - Conference Proceedings 5 : 2247-2251. ScholarBank@NUS Repository.
Abstract: Fast valving has long been seen as an effective and economic method to perform transient control in a power generation plant. Due to the inherent nonlinearities that exist in this operation, the fast valving controller designed in conventional way cannot deliver a satisfactory control. This paper introduces a new approach to control fast valving by using a RBF(radial-basis function) neural network. A controller construction scheme is proposed, in which a stable learning algorithm is embedded. Then the implementation issue is discussed. From the outcome of on-line test, we see that the controller constructed is effective and robust in many different fault situations.
Source Title: IEEE International Conference on Neural Networks - Conference Proceedings
URI: http://scholarbank.nus.edu.sg/handle/10635/81415
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

Google ScholarTM

Check


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.