RBF-based event-triggered fixed-time stable and chattering-free controller for load following of the pressurized water reactor

Hongliang Liu, Wenjie Zeng, Jinsen Xie and Run Luo

Energy, 2024, vol. 307, issue C

Abstract: Preventing chattering phenomenon in load following control of the Pressurized Water Reactor (PWR) is still a main challenge. This article focuses on the chattering-free and rapid load following control strategy for PWR. Firstly, by proposing a newly adaptive updated law, the Radial Basis Function Neural Networks (RBFNNs) is employed to compensate the unmeasured states of relative delayed neutron precursor density, average fuel temperature and uncertain disturbances simultaneously online. On this basis, a fixed-time stable controller including saturation function is constructed to guarantee that the actual output power (OP) of nuclear reactor can follow the desired power (DP) within a fixed-time and the chattering phenomenon is alleviated. Additionally, to save the limited network resource and reduce the cost of computation, an event-triggered mechanism is constructed. Based on it, a chattering-free fixed-time stable controller is structured to ensure that the actual reactivity of control rod (ARCR) converges to the desired control rod reactivity (DCRR) within a fixed-time, meanwhile, it can eliminate Zeno phenomenon during the control process. Finally, the effectiveness and feasibility of the theoretical results are demonstrated through simulation examples.

Keywords: RBF neural networks; Chattering-free fixed-time stable; Event-triggered mechanism; Load following of PWR (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:307:y:2024:i:c:s0360544224024198

DOI: 10.1016/j.energy.2024.132645

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