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Evolving Through Steps: Double-Memory-Driven Anti-Forgetting Framework for Incremental Zero-Shot Fault Diagnosis

IEEE Transactions on Instrumentation and Measurement 2025年 74卷

作者： Zhao, Jiancheng Zhao, Chunhui Yue, Jiaqi Zhejiang University State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Hangzhou310027 China East China Jiaotong University School of Electrical and Automation Engineering Nanchang330013 China

Zero-shot fault diagnosis (ZSFD) can identify unseen faults by predicting fault attributes labeled by human experts. We recognize the need for ZSFD to handle continuous changes in practical industrial processes, that is, the model’s ability to update for newly collected fault categories and attributes while avoiding forgetting the diagnosis ability learned before. Therefore, the incremental ZSFD (IZSFD) paradigm is proposed, which incorporates category increment and attribute increment tasks for both conventional and generalized ZSFD (GZSFD) paradigms. For the category increment, the number of categories continuously increases due to new categories being collected or recognized. For the attribute increment, the number of attributes continuously increases as experts deepen their understanding of each category. To achieve IZSFD, we present a double-memory driven anti-forgetting framework (DM-AF) that aims to learn new fault categories and attributes. DM-AF accumulates knowledge from two perspectives: features and attribute prototypes. The feature memory is established through a generative model that employs designed anti-forgetting training strategies, addressing the accumulation of generation errors over multiple learning stages. The attribute prototype memory is established through the diagnosis model, and the proposed memory-driven prototype update strategy allows the update of the attribute prototype memory without requiring the storage of samples. The effectiveness of the proposed method is verified by a real hydraulic system and the Tennessee-Eastman benchmark. © 1963-2012 IEEE.

关键词： Zero-shot learning

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Insulators Defect Detection for Power Grid Based on Improved Yolov7 Algorithm 13

Insulators Defect Detection for Power Grid Based on Improved...

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13th International Conference on Intelligent control and Information Processing, ICICIP 2025

作者： Zhang, Zhiwei Zhuang, Yan Liang, Zhida Kong, Shuai Zhu, Shengyi School of Control Science and Engineering Dalian University of Technology Dalian China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Key Laboratory of Special Equipment Safety Testing Technology of Zhejiang Province Zhejiang Academy of Special Equipment Science Hangzhou China

ISBN: (纸本)9798331516147

High-current out-of-phase closed bus is an essential link in the transmission of electric energy and is widely used in thermal power stations, hydropower stations and nuclear power plants. Although these busbars have the advantages of excellent dustproof effect and strong magnetic shielding, they are susceptible to insulator aging and damage in long-term operation, posing a potential safety risk to the power grid. Due to the enclosed space inside the bus and the complexity of external maintenance tasks, manual inspection has problems such as inefficiency and low safety. In order to solve these problems, this paper proposes an improved detection algorithm based on Yolov7 for insulator defect detection in hydropower station scenarios. Because of the particularity of Yolov7 network structure and application scenarios, this paper proposes a Channel Feature Enhancement module to enhance the channel representation ability of the network. In addition, an Edge Feature Enhancement module is introduced to improve the boundary detection of insulators by enhancing the contrast between the target and the background. Considering the limitations of existing studies in specific scenarios and the scarcity of dataset, this paper constructs and accurately annotates an insulator defect detection dataset applied to hydropower station scenarios. Experimental results show that the improved-Yolov7-tiny algorithm in this paper achieves a balance between accuracy and inference speed. © 2025 IEEE.

关键词： Magnetic shielding

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Communication-efficient Distributed Learning for Nash Equilibrium of Aggregative Games over Time-varying Digraphs

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2025年

作者： Chen, Mingfei Wang, Dong Xu, Xiaopeng Yao, Wenli Zhu, Bingyang Dalian University of Technology Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education School of Control Science and Engineering China Northwestern Polytechnical University School of Automation Shaanxi Xi'an710129 China

Communication efficiency is a major challenge in learning the Nash equilibrium (NE) of aggregative games in a distributed manner. To address this problem, this paper focuses on designing a communication-efficient algorithm under unbalanced digraphs, where the cost function of each player is affected by its own actions and the average aggregation function. In particular, the considered games have no central node, and no player has direct access to the aggregation function. To estimate the aggregation function, an auxiliary variable is employed to estimate the right Perron eigenvector of the column-stochastic weight matrix, which extends the dynamic average consensus protocol to time-varying digraphs Additionally, players exchange information periodically and perform multi-step local updates with local information between two consecutive communications. By combining the above two strategies with the gradient descent method, a communication-efficient algorithm is proposed and achieves a linear convergence rate. Then the communication period selection method is provided to determine the best trade-off between local updates and information exchange under limited resources. Finally, numerical results demonstrate the effectiveness of the proposed algorithm. © 2020 IEEE.

关键词： Cost functions

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Predefined-time Attitude Tracking control for Liquid-filled Spacecraft Under Angular Velocity and Torque Constraints

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IEEE Transactions on Aerospace and Electronic Systems 2025年

作者： Zhang, Wei Guo, Yanning Ran, Guangtao Liu, Jian Wang, Bohui Harbin Institute of Technology Department of Control Science and Engineering Heilongjiang Harbin150001 China Southeast University School of Automation Nanjing210096 China Xi'an Jiaotong University School of Cyber Science and Engineering Xi'an710049 China

This paper addresses the attitude tracking control problem of liquid-filled spacecraft in the presence of angular velocity constraints and limited control torque. Significant challenges arise in spacecraft attitude control due to the increased nonlinearity and uncertainty in spacecraft dynamics resulting from large-amplitude liquid fuel slosh during attitude tracking missions. Firstly, the sloshing liquid in partially-filled tanks carried by the spacecraft is described by the Moving Pulsating Ball Model, and the interaction torque between rigid body and pulsating ball is equivalent to the internal disturbance. Secondly, a predefined-time disturbance observer is introduced to estimate the internal and external disturbance. After that, two sliding mode variables are designed to ensure that the angular velocity can track the desired value within a predefined time and satisfy the constraints. Furthermore, a predefined-time sliding mode attitude tracking controller is proposed, and a predefined-time auxiliary subsystem is proposed to deal with the torque constraint. Finally, the effectiveness of the proposed control algorithm is verified by numerical simulation. © 1965-2011 IEEE.

关键词： Fuel sloshing

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Active Fault Tolerant control for PEM Fuel Cells Under Cathode Flooding

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IEEE Transactions on Transportation Electrification 2025年第3期11卷 8043-8053页

作者： Chen, Jian Yan, Chizhou Kumar, Lalitesh Jin, Lei Li, Xinyu Southern University of Science and Technology School of Automation and Intelligent Manufacturing Shenzhen518055 China Zhejiang University School of Mechanical Engineering Hangzhou310058 China Zhejiang University College of Control Science and Engineering Hangzhou310027 China

Proper fault tolerant control is a key issue to extend the lifetime of proton exchange membrane fuel cells. This paper proposes a fault tolerant control algorithm to realize performance recovery under flooding. A water transfer model of the PEM fuel cells is established and verified, and a flooding fault indicator is developed for diagnosing the fault in real time. Thereafter, an active fault tolerant controller based on the water transfer model and the fault indicator is developed in order to recover the performance characteristics of the PEM fuel cells. Experimental results show that the proposed fault indicator can accurately identify the flooding, and the fault tolerant controller can effectively suppress the water management failure. Thereby improving the reliability of the PEM fuel cells. © 2015 IEEE.

关键词： Fault detection

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A Micromesh Multi-Scaled Features Extraction Network for Li-ion Batteries SOH Estimation

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IEEE Transactions on Vehicular Technology 2025年

作者： Wang, Min Chen, Yitian Guo, Dongxu Xu, Zhiwei University of Electronic Science and Technology of China School of Automation Engineering Chengdu611731 China Tsinghua University School of Vehicle and Mobility Beijing100084 China Shandong University Department of Control Science and Engineering Jinan250061 China

The great progress and wide application of electronic products and electric vehicles have entailed more stringent requirements for the reliability of lithium-ion batteries. The State of Health (SOH) serves as a significant indicator for evaluating the condition of such batteries. However existing methods are lack of refined modeling for sequences and unable to make precise estimation for SOH. In this paper, a micromesh multi-scaled features extraction network (MMFEN) is proposed for accurately estimating SOH. A refined representation block is developed for heterogeneous elaborate feature extraction. Then, a multi-head convolution attention block is constructed to capture multi-scaled efficient state information. To demonstrate the superiority of MMFEN, experiments are conducted on the NASA and CALCE data published online and a real-world electric vehicles (EVs) data set which is collected from existing battery management systems. Comparing with traditional methods, MMFEN achieves remarkable performance with average root mean square error of 1.21% and mean absolute percentage error of 0.99% on NASA samples, 2.78% and 2.71% on CALCE dataset, while 2.39% and 2.08% on EVs data set, respectively. © 1967-2012 IEEE.

关键词： Lithium-ion batteries

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Adaptive fuzzy security control of uncertain semi-Markov jump cyber-physical systems with stochastic perturbation

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Cyber-Physical Systems 2025年

作者： Xun, Tengteng Liu, Zhen Jiang, Baoping School of Automation Shandong Key Laboratory of Industrial Control Technology Qingdao University Qingdao China School of Electronic and Information Engineering Suzhou University of Science and Technology Suzhou China

A novel adaptive secure control strategy is proposed for uncertain stochastic semi-Markov jump cyber-physical systems utilizing fuzzy sliding mode control (FSMC) technology, where the studied plants are affected by actuator attacks (AAs), actuator failures (AFs), stochastic perturbations and unknown transition rates. This strategy not only constrains the state trajectory to the constructed sliding mode surface (SMS) during limited period, but also ensures that the uncertain system operates with control requirements against unknown AAs and AFs, and the stochastic stability condition is derived by integrating SMS reachability with stochastic control theory. Finally, simulation results exhibit the feasibility of the proposed algorithm. © 2025 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Markov processes

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Low-Complexity Cooperative Payload Transportation for Nonholonomic Mobile Robots Under Scalable Constraints

arXiv

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arXiv 2025年

作者： Guan, Renhe Wang, Yuanzhe Liu, Tao Wang, Yan Mechanical Electrical Engineering and Automation Harbin Institute of Technology Shenzhen Shenzhen China School of Control Science and Engineering Shandong University Shandong Jinan China School of Automation and Intelligent Manufacturing Southern University of Science and Technology Shenzhen518055 China

Cooperative transportation, a key aspect of logistics cyber-physical systems (CPS), is typically approached using distributed control and optimization-based methods. The distributed control methods consume less time, but poorly handle and extend to multiple constraints. Instead, optimization-based methods handle constraints effectively, but they are usually centralized, time-consuming and thus not easily scalable to numerous robots. To overcome drawbacks of both, we propose a novel cooperative transportation method for nonholonomic mobile robots by improving conventional formation control, which is distributed, has a low time-complexity and accommodates scalable constraints. The proposed control-based method is testified on a cable-suspended payload and divided into two parts, including robot trajectory generation and trajectory tracking. Unlike most time-consuming trajectory generation methods, ours can generate trajectories with only constant time-complexity, needless of global maps. As for trajectory tracking, our control-based method not only scales easily to multiple constraints as those optimization-based methods, but reduces their time-complexity from polynomial to linear. Simulations and experiments can verify the feasibility of our method. © 2025, CC BY.

关键词： Mobile robots

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Finite-Horizon Discrete-Time Optimal control for Nonlinear Systems under State and control Constraints

arXiv

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arXiv 2025年

作者： Lv, Chuanzhi Li, Hongdan Zhang, Huanshui College of Electrical Engineering and Automation Shandong University of Science and Technology Qingdao266590 China The School of Control Science and Engineering Shandong University Shandong Jinan250061 China

This paper addresses the optimal control problem of finite-horizon discrete-time nonlinear systems under state and control constraints. A novel numerical algorithm based on optimal control theory is proposed to achieve superior computational efficiency, with the novelty lying in establishing a unified framework that integrates all aspects of algorithm design through the solution of forward and backward difference equations (FBDEs). Firstly, the state and control constraints are transformed using an augmented Lagrangian method (ALM), thereby decomposing the original optimal control problem into several optimization subproblems. These subproblems are then reformulated as new optimal control problem, which are solved through the corresponding FBDEs, resulting in an algorithm with superlinear convergence rate. Furthermore, the gradient and Hessian matrix are computed by iteratively solving FBDEs, thereby accelerating the optimization process. The gradient is obtained through the standard Hamiltonian, while the Hessian matrix is derived by constructing a novel Hamiltonian specifically designed for second-order optimization, transforming each row into an iterative solution of a new set of FBDEs. Finally, the effectiveness of the algorithm is validated through simulation results in automatic guided vehicles (AGV) trajectory tracking control. © 2025, CC BY.

关键词： Iterative methods

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Indoor Height Estimation Method for Scissor Lift Based on Sensor Information Fusion 25

Indoor Height Estimation Method for Scissor Lift Based on Se...

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Proceedings of the 2025 3rd International Conference on Communication Networks and Machine Learning

作者： Xinhui Song Yuzhe Li Qinmin Yang Bo Fan School of Engineering Huzhou University Huzhou Zhejiang China College of Control Science and Engineering Zhejiang University Hangzhou Zhejiang China School of Automation Science and Engineering Xi'an Jiaotong University Xi'an Shaanxi China

ISBN: (纸本)9798400713231

Accurate height information is crucial for enhancing the safety and operability of scissor lift in indoor operations. To address issues such as outlier interference, integral drift, and barometric pressure perturbation in existing single-sensor height measurement methods, this paper proposes a height estimation algorithm that fuses accelerometer and barometer data. The dynamic threshold outlier rejection mechanism is developed using jerk analysis combined with the improved Interquartile Range (IQR) outlier detection algorithm, reducing high-frequency noise interference in the accelerometer. The Finite State Machine (FSM)-based adaptive Kalman filter identifies the motion state and dynamically adjusts drift compensation, enhancing the algorithm's stability. An Extended Kalman Filtering (EKF) fusion model is developed to construct an observation equation using the barometer's absolute height measurement and the accelerometer's relative displacement. The height estimation error is kept within 0.14mby leveraging the complementary characteristics of both sensors, providing a high-precision height reference for scissor lift in indoor operations. This method has broad application potential in indoor positioning and navigation.

关键词： Extended Kalman Filtering

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