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Heterogeneous Multi-Agent Task Allocation Based on Graph-Based Convolutional Assignment Neural Network

IEEE Internet of Things Journal 2025年第11期12卷 17281-17299页

作者： Ma, Ziyuan Gong, Huajun Xiong, Jun Wang, Xinhua Nanjing University of Aeronautics and Astronautics Flight Control Laboratory the College of Automation Engineering Nanjing China Nanjing University of Posts and Telecommunications Nanjing China

Task allocation in complex multi-agent systems involves assigning tasks to agents with varying capabilities to optimize overall performance. The challenge lies in selecting the most suitable agent for each task, considering the agents' heterogeneity and the intricate relationships between tasks. Traditional methods often fail to capture this complexity. To address these limitations, we propose the graph multi-agent task allocation neural network (GMATANN), a novel approach utilizing a graph attention mechanism. GMATANN models the interactions between agents and tasks through a task-agent graph, where both agents and tasks are represented as nodes, and their associations are depicted as edges. The graph attention mechanism is crucial for capturing the key relationships and ensuring effective information flow between nodes. By learning attention weights, the network automatically identifies which agents are best suited for specific tasks. We employ a neural network framework based on this attention mechanism to train and evaluate the method. Simulation experiments demonstrate the effectiveness of GMATANN, achieving a task allocation accuracy of 92.3% and a reliability of 94.2%, outperforming traditional approaches. This innovative method offers a new strategy for complex task allocation in multi-agent systems, providing an adaptive solution that selects suitable agents for diverse tasks, thereby enhancing system efficiency. © 2025 IEEE.

关键词： Graph neural networks

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A Recursive System Identification With Non-Uniform Temporal Feedback Under Coprime Collaborative Sensing

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ASME Letters in Dynamic Systems and control 2023年第2期3卷 021010页

作者： Ouyang, Jinhua Chen, Xu Mechatronics Automation and Control Systems Laboratory Department of Mechanical Engineering University of Washington SeattleWA98195 United States Mechatronics Automation and Control Systems Laboratory Department of Mechanical Engineering University of Washington SeattleWA98195 United States

We present a system identification method based on recursive least-squares (RLS) and coprime collaborative sensing, which can recover system dynamics from non-uniform temporal data. Focusing on systems with fast input sampling and slow output sampling, we use a polynomial transformation to reparameterize the system model and create an auxiliary model that can be identified from the non-uniform data. We show the identifiability of the auxiliary model using a Diophantine equation approach. Numerical examples demonstrate successful system reconstruction and the ability to capture fast system response with limited temporal feedback. Copyright © 2023 by ASME.

关键词： Feedback

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Distributed Fault Tolerant control of Multi-Agent System Based on LSTM Trajectory Prediction Model Under Intermittent Communication Faults

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Journal of Dynamic Systems, Measurement and control 2025年第4期147卷 041005页

作者： Wang, Yingying Qi, Ruiyun Jiang, Bin State Key Laboratory of Mechanics and Control for Aerospace Structures College of Automation Engineering Nanjing University of Aeronautics and Astronautics Jiangsu Nanjing210016 China

This paper proposes a novel trajectory prediction based fault-tolerant control method for multi-agent systems under intermittent communication faults. Agents affected by intermittent communication faults are unable to communicate with neighbors or obtain reference tracking information for a period of time. To address this issue, we first employ a trajectory prediction model trained using long short term memory neural network to predict the expected trajectory in the event of intermittent communication faults. Subsequently, a distributed controller based on fixed-time theory is designed to track the predicted values. Compared with the existing fault-tolerant control methods, the proposed strategy achieves smaller consensus errors and a longer tolerable intermittent inter-ruption interval. Moreover, it demonstrates the capability to predict the actual expected trajectory trends of agents during large-angle maneuvers. Finally, the effectiveness of the fault-tolerant control strategy is verified by simulation. Copyright © 2025 by ASME.

关键词： Long short-term memory

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Adaptive control of a Flexible Manipulator With Unknown Hysteresis and Intermittent Actuator Faults

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IEEE/CAA Journal of Automatica Sinica 2025年第1期12卷 148-158页

作者： Shouyan Chen Weitian He Zhijia Zhao Yun Feng Zhijie Liu Keum-Shik Hong School of Mechanical and Electrical Engineering Guangzhou University the School of Control Science and Engineering Shandong University IEEE the College of Electrical and Information Engineering Hunan University the National Engineering Research Center for Robot Visual Perception and Control Technology Hunan University the School of Intelligence Science and Technology University of Science and Technology Beijing (USTB) the Institute for Future the School of AutomationQingdao University the School of Mechanical Engineering Pusan National University

In this study, we consider a single-link flexible manipulator in the presence of an unknown Bouc-Wen type of hysteresis and intermittent actuator faults. First, an inverse hysteresis dynamics model is introduced, and then the control input is divided into an expected input and an error compensator. Second,a novel adaptive neural network-based control scheme is proposed to cancel the unknown input hysteresis. Subsequently,by modifying the adaptive laws and local control laws, a fault-tolerant control strategy is applied to address uncertain intermittent actuator faults in a flexible manipulator system. Through the direct Lyapunov theory, the proposed scheme allows the state errors to asymptotically converge to a specified interval. Finally,the effectiveness of the proposed scheme is verified through numerical simulations and experiments.

关键词： Adaptive control flexible manipulator intermittent actuator faults inverse hysteresis dynamics vibration control

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Broad-Learning-System-Based Model-Free Adaptive Predictive control for Nonlinear MASs Under DoS Attacks

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IEEE/CAA Journal of Automatica Sinica 2025年第2期12卷 381-393页

作者： Hongxing Xiong Guangdeng Chen Hongru Ren Hongyi Li the School of Automation Guangdong-Hong Kong Joint Laboratory for Intelligent Decision and Cooperative Control Guangdong University of Technology Guangdong Provincial Key Laboratory for Intelligent Decision and Cooperative Control Guangdong University of Technology the College of Electronic and Information Engineering Southwest University IEEE

In this paper, the containment control problem in nonlinear multi-agent systems(NMASs) under denial-of-service(DoS) attacks is addressed. Firstly, a prediction model is obtained using the broad learning technique to train historical data generated by the system offline without DoS attacks. Secondly, the dynamic linearization method is used to obtain the equivalent linearization model of NMASs. Then, a novel model-free adaptive predictive control(MFAPC) framework based on historical and online data generated by the system is proposed, which combines the trained prediction model with the model-free adaptive control method. The development of the MFAPC method motivates a much simpler robust predictive control solution that is convenient to use in the case of DoS attacks. Meanwhile, the MFAPC algorithm provides a unified predictive framework for solving consensus tracking and containment control problems. The boundedness of the containment error can be proven by using the contraction mapping principle and the mathematical induction method. Finally, the proposed MFAPC is assessed through comparative experiments.

关键词： Broad learning technique denial-of-service (DoS) model-free adaptive predictive control (MFAPC) nonlinear multi-agent systems (NMASs)

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Nonlinear stress analysis of aero-engine pipeline based on semi-analytical method

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Applied Mathematics and Mechanics(English Edition) 2025年第3期46卷 521-538页

作者： Weijiao CHEN Xiaochi QU Ruixin ZHANG Xumin GUO Hui MA Bangchun WEN School of Mechanical Engineering and Automation Northeastern UniversityShenyang 110819China Key Laboratory of Vibration and Control of Aero-Propulsion Systems Ministry of Education of China Northeastern UniversityShenyang 110819China

Fatigue failure caused by vibration is the most common type of pipeline *** core of this research is to obtain the nonlinear dynamic stress of a pipeline system accurately and efficiently,a topic that needs to be explored in the existing *** shell theory can better simulate the circumferential stress distribution,and thus the Mindlin-Reissner shell theory is used to model the *** this paper,the continuous pipeline system is combined with clamps through modal expansion for the first time,which realizes the coupling problem between a shell and a *** the Bouc-Wen model is used to simulate the nonlinear external force generated by a clamp,the nonlinear coupling characteristics of the system are effectively ***,the dynamic equation of the clamp-pipeline system is established according to the Lagrange energy *** on the resonance frequency and stress amplitude obtained from the experiment,the nonlinear parameters of the clamp are identified with the semi-analytical method(SAM)and particle swarm optimization(PSO)*** study provides a theoretical basis for the clamp-pipeline system and an efficient and universal solution for stress prediction and analysis of pipelines in engineering.

关键词： pipeline modeling stress analysis nonlinear-clamp support nonlinear vibration

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Observer design and interval estimation of time-delay discrete-time linear systems with external disturbance and measurement noise

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control Theory and Technology 2024年第1期22卷 69-80页

作者： Junqi Yang Jianhao Xie Feiyang Liu School of Electrical Engineering and Automation Henan Key Laboratory of Intelligent Detection and Control of Coal Mine EquipmentHenan Polytechnic UniversityJiaozuo454003HenanChina

For a class of time-delay discrete-time linear systems with external disturbance and measurement noise, the interval estimation problems of state and measurement noise are investigated in this paper. First, the system state together with the time-delay term and measurement noise is augmented as a new state, and a singular system is then constructed. Subsequently, a kind of decoupling technique is employed to eliminate the effect of external disturbance, and an observer is designed to simultaneously estimate the system state and measurement noise. Based on the estimated state and measurement noise, the interval estimations of system state and measurement noise are obtained by reachability analysis technique. Finally, the effectiveness of the proposed method is verified by a four-tank liquid level system.

关键词： Interval estimation Time-delay system Observer design Reachability analysis

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A Bio-inspired Mutual-hook Strategy for the Soft Finger to Improve Load-bearing Capacity and Grasping Stability

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Journal of Bionic engineering 2024年第3期21卷 1290-1304页

作者： Jie Huang Lingjie Gai Xiaofeng Zong Yunquan Li School of Automation China University of GeosciencesWuhan430074China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex System Wuhan430074China The Shien-Ming Wu School of Intelligent Engineering South China University of TechnologyGuangzhou510641China

Soft grippers have great potential applications in daily life,since they can compliantly grasp soft and delicate ***,the highly elastic fingers of most soft grippers are prone to separate from each other while grasping objects due to their low stiffness,thus reducing the grasping stability and load-bearing *** tackle this problem,inspired from the venus flytrap plant,this work proposes a mutual-hook mechanism to restrain the separation and improve the grasping performance of soft *** novel soft gripper design consists of three modules,a soft finger-cot,two Soft Hook Actuators(SHAs)and two sliding ***,the soft finger-cot covers on the soft finger,increasing the contact area with the target object,two SHAs are fixed to the left and right sides of the finger-cot,and the sliding mechanisms are designed to make SHAs stretch *** demonstrate that the proposed design can restrain the separation of soft fingers substantially,and the soft fingers with the finger-cots can grasp objects three times heavier than the soft fingers without the proposed *** proposed design can provide invaluable insights for soft fingers to restrain the separation while grasping,thus improving the grasping stability and the load-bearing capacity.

关键词： Soft robotics Soft bionic finger-cot Soft hook actuator Grasping stability Load-bearing capacity

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A Feature Weighted Mixed Naive Bayes Model for Monitoring Anomalies in the Fan System of a Thermal Power Plant

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IEEE/CAA Journal of Automatica Sinica 2022年第4期9卷 719-727页

作者： Min Wang Li Sheng Donghua Zhou Maoyin Chen IEEE the Department of Automation Tsinghua University the College of Control Science and Engineering China University of Petroleum(East China) the College of Electrical Engineering and Automation Shandong University of Science and Technology

With the increasing intelligence and integration,a great number of two-valued variables(generally stored in the form of 0 or 1)often exist in large-scale industrial ***,these variables cannot be effectively handled by traditional monitoring methods such as linear discriminant analysis(LDA),principal component analysis(PCA)and partial least square(PLS)***,a mixed hidden naive Bayesian model(MHNBM)is developed for the first time to utilize both two-valued and continuous variables for abnormality *** the MHNBM is effective,it still has some shortcomings that need to be *** the MHNBM,the variables with greater correlation to other variables have greater weights,which can not guarantee greater weights are assigned to the more discriminating *** addition,the conditional P(x j|x j′,y=k)probability must be computed based on historical *** the training data is scarce,the conditional probability between continuous variables tends to be uniformly distributed,which affects the performance of *** a novel feature weighted mixed naive Bayes model(FWMNBM)is developed to overcome the above *** the FWMNBM,the variables that are more correlated to the class have greater weights,which makes the more discriminating variables contribute more to the *** the same time,FWMNBM does not have to calculate the conditional probability between variables,thus it is less restricted by the number of training data *** with the MHNBM,the FWMNBM has better performance,and its effectiveness is validated through numerical cases of a simulation example and a practical case of the Zhoushan thermal power plant(ZTPP),China.

关键词： Abnormality monitoring continuous variables feature weighted mixed naive Bayes model(FWMNBM) two-valued variables thermal power plant

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Linear active disturbance rejection control of fighter aircraft based on MADDPG algorithm

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International Journal of Systems, control and Communications 2025年第2期16卷 152-172页

作者： Lin, Yetong Ji, Yuehui Song, Yu Liu, Junjie Tianjin Key Laboratory for Control Theory and Applications in Complicated Industry Systems School of Electrical Engineering and Automation Tianjin University of Technology Tianjin300384 China

To address nonlinearity, strong coupling, and disturbances in fighter aircraft attitude control, this paper proposes an intelligent control method based on multi-agent deep deterministic policy gradient (MADDPG) and linear active disturbance rejection control (LADRC). A three-channel LADRC controller estimates and compensates for disturbances, uncertainties, and coupling terms in real time. To overcome the dimensionality curse in multi-parameter optimization, an independent DDPG controller is assigned to each channel, ensuring cooperative control via reward sharing and enhancing dynamic response and disturbance rejection. Additionally, long short-term memory (LSTM) and self-attention mechanisms are integrated into the policy and value networks to improve representation and decision-making. A piecewise combined reward function mitigates sparse rewards. Simulations show that, compared to MADQN-based and traditional LADRC methods, the proposed approach achieves superior control performance and significantly reduces manual parameter tuning efforts. Copyright © 2025 Inderscience Enterprises Ltd.

关键词： Disturbance rejection

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