Fuzzy gain scheduling of velocity PI controller with intelligent learning algorithm for reactor control = 원자로 제어를 위한 지적 학습 알고리듬을 가진 속도형 PI 제어기의 퍼지 이득 계획 기법 개발에 관한 연구

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In this research, we propose a fuzzy gain scheduler (FGS) with an intelligent learning algorithm for a reactor control. In the proposed algorithm, the gradient descent method is used in order to generate the rule bases of a fuzzy algorithm by learning. These rule bases are obtained by minimizing an objective function, which is called a performance cost function. The objective of the FGS with an intelligent learning algorithm is to generate adequate gains, which minimize the error of system. The proposed algorithm can reduce the time and efforts required for obtaining the fuzzy rules through the intelligent learning function. The evolutionary programming algorithm is modified and adopted as the method in order to find the optimal gains which are used as the initial gains of FGS with learning function. It is applied to reactor control of nuclear power plant (NPP), and the results are compared with those of a conventional PI controller with fixed gains. As a result, it is shown that the proposed algorithm is superior to the conventional PI controller.
Advisors
Seong, Poong-Hyunresearcher성풍현researcher
Description
한국과학기술원 : 원자력공학과,
Publisher
한국과학기술원
Issue Date
1997
Identifier
114537/325007 / 000953052
Language
eng
Description

학위논문(석사) - 한국과학기술원 : 원자력공학과, 1997.2, [ v, 46 p. ]

Keywords

지적 학습 알고리듬; 퍼지 이득 계획; 원자로 제어; Reactor control; Intelligent learning algorithm; Control; Fuzzy gain scheduliing

URI
http://hdl.handle.net/10203/49365
Link
http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=114537&flag=dissertation
Appears in Collection
NE-Theses_Master(석사논문)
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