A Novel Fractional-Order PID Controller for Integrated Pressurized Water Reactor Based on Wavelet Kernel Neural Network Algorithm

A Novel Fractional-Order PID Controller for Integrated Pressurized Water Reactor Based on Wavelet Kernel Neural Network Algorithm

This paper presents a novel wavelet kernel neural network (WKNN) with wavelet kernel function. It is applicable in online learning with adaptive parameters and is applied on parameters tuning of fractional-order PID (FOPID) controller, which could handle time delay problem of the complex control sys...

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Main Authors: Yu-xin Zhao, Xue Du, Geng-lei Xia
Format: Article
Language:English
Published: Hindawi Limited 2014-01-01
Series:Mathematical Problems in Engineering
Online Access:http://dx.doi.org/10.1155/2014/312541
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spelling doaj-2ef7fa9f1d974ac283d179f66da567022020-11-24T22:55:27ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472014-01-01201410.1155/2014/312541312541A Novel Fractional-Order PID Controller for Integrated Pressurized Water Reactor Based on Wavelet Kernel Neural Network AlgorithmYu-xin Zhao0Xue Du1Geng-lei Xia2College of Automation, Harbin Engineering University, Harbin, Heilongjiang 150001, ChinaCollege of Automation, Harbin Engineering University, Harbin, Heilongjiang 150001, ChinaNational Defense Key Subject Laboratory of Nuclear Safety and Simulation Technology, Harbin Engineering University, Harbin, Heilongjiang 150001, ChinaThis paper presents a novel wavelet kernel neural network (WKNN) with wavelet kernel function. It is applicable in online learning with adaptive parameters and is applied on parameters tuning of fractional-order PID (FOPID) controller, which could handle time delay problem of the complex control system. Combining the wavelet function and the kernel function, the wavelet kernel function is adopted and validated the availability for neural network. Compared to the conservative wavelet neural network, the most innovative character of the WKNN is its rapid convergence and high precision in parameters updating process. Furthermore, the integrated pressurized water reactor (IPWR) system is established by RELAP5, and a novel control strategy combining WKNN and fuzzy logic rule is proposed for shortening controlling time and utilizing the experiential knowledge sufficiently. Finally, experiment results verify that the control strategy and controller proposed have the practicability and reliability in actual complicated system.http://dx.doi.org/10.1155/2014/312541
collection DOAJ
language English
format Article
sources DOAJ
author Yu-xin Zhao
Xue Du
Geng-lei Xia
spellingShingle Yu-xin Zhao
Xue Du
Geng-lei Xia
A Novel Fractional-Order PID Controller for Integrated Pressurized Water Reactor Based on Wavelet Kernel Neural Network Algorithm
Mathematical Problems in Engineering
author_facet Yu-xin Zhao
Xue Du
Geng-lei Xia
author_sort Yu-xin Zhao
title A Novel Fractional-Order PID Controller for Integrated Pressurized Water Reactor Based on Wavelet Kernel Neural Network Algorithm
title_short A Novel Fractional-Order PID Controller for Integrated Pressurized Water Reactor Based on Wavelet Kernel Neural Network Algorithm
title_full A Novel Fractional-Order PID Controller for Integrated Pressurized Water Reactor Based on Wavelet Kernel Neural Network Algorithm
title_fullStr A Novel Fractional-Order PID Controller for Integrated Pressurized Water Reactor Based on Wavelet Kernel Neural Network Algorithm
title_full_unstemmed A Novel Fractional-Order PID Controller for Integrated Pressurized Water Reactor Based on Wavelet Kernel Neural Network Algorithm
title_sort novel fractional-order pid controller for integrated pressurized water reactor based on wavelet kernel neural network algorithm
publisher Hindawi Limited
series Mathematical Problems in Engineering
issn 1024-123X
1563-5147
publishDate 2014-01-01
description This paper presents a novel wavelet kernel neural network (WKNN) with wavelet kernel function. It is applicable in online learning with adaptive parameters and is applied on parameters tuning of fractional-order PID (FOPID) controller, which could handle time delay problem of the complex control system. Combining the wavelet function and the kernel function, the wavelet kernel function is adopted and validated the availability for neural network. Compared to the conservative wavelet neural network, the most innovative character of the WKNN is its rapid convergence and high precision in parameters updating process. Furthermore, the integrated pressurized water reactor (IPWR) system is established by RELAP5, and a novel control strategy combining WKNN and fuzzy logic rule is proposed for shortening controlling time and utilizing the experiential knowledge sufficiently. Finally, experiment results verify that the control strategy and controller proposed have the practicability and reliability in actual complicated system.
url http://dx.doi.org/10.1155/2014/312541
work_keys_str_mv AT yuxinzhao anovelfractionalorderpidcontrollerforintegratedpressurizedwaterreactorbasedonwaveletkernelneuralnetworkalgorithm
AT xuedu anovelfractionalorderpidcontrollerforintegratedpressurizedwaterreactorbasedonwaveletkernelneuralnetworkalgorithm
AT gengleixia anovelfractionalorderpidcontrollerforintegratedpressurizedwaterreactorbasedonwaveletkernelneuralnetworkalgorithm
AT yuxinzhao novelfractionalorderpidcontrollerforintegratedpressurizedwaterreactorbasedonwaveletkernelneuralnetworkalgorithm
AT xuedu novelfractionalorderpidcontrollerforintegratedpressurizedwaterreactorbasedonwaveletkernelneuralnetworkalgorithm
AT gengleixia novelfractionalorderpidcontrollerforintegratedpressurizedwaterreactorbasedonwaveletkernelneuralnetworkalgorithm
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