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Neural networks and adaptive finite-time state observer-based preassigned-time fault-tolerant control of load following for a PWR-SMR under CRDM faults and sensor noises

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成果类型:
期刊论文
作者:
Liu, Hongliang;Song, Yingming;Xiao, Qizhen;Xu, Qiming
通讯作者:
Song, YM
作者机构:
[Xiao, Qizhen; Liu, Hongliang; Xu, Qiming] Univ South China, Sch Math & Phys, Hengyang 421001, Peoples R China.
[Song, Yingming] CNNC, Nucl Ind Coll, Beijing 102618, Peoples R China.
通讯机构:
[Song, YM ] C
CNNC, Nucl Ind Coll, Beijing 102618, Peoples R China.
语种:
英文
关键词:
Adaptive finite-time state observer;Preassigned-time stable controller;Control rod drive mechanism faults;Sensor noises;Small modular reactor
期刊:
Energy
ISSN:
0360-5442
年:
2025
卷:
323
页码:
135689
基金类别:
Hunan Provincial Natural Science Foundation [2024JJ5320]; Hunan Provincial Education Department Foundation [24B0421]
机构署名:
本校为第一机构
院系归属:
数理学院
摘要:
Load Following (L-F) control of Nuclear Power Plant (NPP) under actuator faults and measurement noises remains challenging both in theory and in practice. To solve this challenge, a globally preassigned-time stable fault-tolerant control strategy of rapid L-F for a Pressurized Water Reactor based Small Modular Reactors (PWR-SMR) under control rod drive mechanism (CRDM) faults and sensor noises is first proposed. From a practical standpoint, considering some states of PWR-SMR cannot be measured directly and the sensor noises in practice, a finite-time tracking differentiator and a nonlinear ada...

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