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An intelligent active fault tolerant control strategy for pressurized water reactor: Addressing sensor faults.

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Title: An intelligent active fault tolerant control strategy for pressurized water reactor: Addressing sensor faults.
Authors: Kumar, Swetha R1 (AUTHOR) swetha.rkumar@vit.ac.in, Chinnasamy, Mogana Priya2 (AUTHOR), Devakumar, Jayaprasanth3 (AUTHOR)
Source: Progress in Nuclear Energy. Oct2025, Vol. 188, pN.PAG-N.PAG. 1p.
Subjects: Ant algorithms, Swarm intelligence, Sensor networks, Fault-tolerant control systems, Fault diagnosis
Abstract: Robust and reliable control strategies are essential for ensuring the safe and efficient operation of thermal energy systems, particularly in nuclear reactors. This paper proposes an intelligent active fault-tolerant control strategy to address sensor faults in pressurized water reactors. The proposed framework comprises three key components: a control mechanism, a fault detection and diagnosis unit, and a reconfiguration mechanism. A Proportional-Integral-Derivative controller, optimized using ant colony optimization, is implemented to regulate neutron density. The fault detection and diagnosis unit employ a recurrent neural network estimator to detect sensor faults by analyzing residuals. Upon fault detection, a reconfiguration module, which is also based on a recurrent neural network, predicts the true value of the faulty sensor using correlated measurements from other sensors. The prediction accuracy is quantified using the mean square error performance index. The effectiveness and practical applicability of the proposed strategy are demonstrated through simulation studies, including a representative drift fault scenario. • Intelligent Active Fault-Tolerant Control : Proposes a novel control strategy for handling sensor faults in pressurized water reactors (PWRs) to enhance safety and efficiency. • Ant Colony Optimized PID Controller : Implements an Ant Colony Optimization technique to tune a PID controller for effective neutron density regulation. • RNN-Based Fault Detection and Diagnosis (FDD) : Utilizes a Recurrent Neural Network (RNN) estimator to detect and diagnose sensor faults through residual generation. • Reconfiguration Mechanism : Develops an RNN-based reconfiguration block to predict true sensor values, compensating for faulty measurements. • Performance Evaluation : Assesses the system's performance using the mean square error (MSE) index and conducts a detailed study under a sensor drift fault scenario. • Robust Fault-Tolerant Operation : Demonstrates the potential of the proposed control system to ensure reliable operation of thermal energy systems even in the presence of sensor faults. [ABSTRACT FROM AUTHOR]
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Database: Engineering Source
Description
Abstract:Robust and reliable control strategies are essential for ensuring the safe and efficient operation of thermal energy systems, particularly in nuclear reactors. This paper proposes an intelligent active fault-tolerant control strategy to address sensor faults in pressurized water reactors. The proposed framework comprises three key components: a control mechanism, a fault detection and diagnosis unit, and a reconfiguration mechanism. A Proportional-Integral-Derivative controller, optimized using ant colony optimization, is implemented to regulate neutron density. The fault detection and diagnosis unit employ a recurrent neural network estimator to detect sensor faults by analyzing residuals. Upon fault detection, a reconfiguration module, which is also based on a recurrent neural network, predicts the true value of the faulty sensor using correlated measurements from other sensors. The prediction accuracy is quantified using the mean square error performance index. The effectiveness and practical applicability of the proposed strategy are demonstrated through simulation studies, including a representative drift fault scenario. • Intelligent Active Fault-Tolerant Control : Proposes a novel control strategy for handling sensor faults in pressurized water reactors (PWRs) to enhance safety and efficiency. • Ant Colony Optimized PID Controller : Implements an Ant Colony Optimization technique to tune a PID controller for effective neutron density regulation. • RNN-Based Fault Detection and Diagnosis (FDD) : Utilizes a Recurrent Neural Network (RNN) estimator to detect and diagnose sensor faults through residual generation. • Reconfiguration Mechanism : Develops an RNN-based reconfiguration block to predict true sensor values, compensating for faulty measurements. • Performance Evaluation : Assesses the system's performance using the mean square error (MSE) index and conducts a detailed study under a sensor drift fault scenario. • Robust Fault-Tolerant Operation : Demonstrates the potential of the proposed control system to ensure reliable operation of thermal energy systems even in the presence of sensor faults. [ABSTRACT FROM AUTHOR]
ISSN:01491970
DOI:10.1016/j.pnucene.2025.105900