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Multi-Objective Cooperative Salvo Attack Against Group Target

Journal of systems Science & complexity 2018年第1期31卷 244-261页

作者： ZENG Jie DOU Lihua XIN Bin School of Automation State Key Laboratory of Intelligent Control and Decision of Complex SystemsBeijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of Technology

This paper proposes a solution for the problem of cooperative salvo attack of multiple cruise missiles against targets in a group. Synchronization of the arrival time of missiles to hit their common target, minimizing the time consumption of attack and maximizing the expected damage to group targets are taken into consideration simultaneously. These operational objectives result in a hierarchical mixed-variable optimization problem which includes two types of subproblems, namely the multi-objective missile-target assignment（MOMTA） problem at the upper level and the time-optimal coordinated path planning（TOCPP） problems at the lower level. In order to solve the challenging problem, a recently proposed coordinated path planning method is employed to solve the TOCPP problems to achieve the soonest salvo attack against each target. With the aim of finding a more competent solver for MOMTA, three state-of-the-art multi-objective optimization methods（MOMs）,namely NSGA-II, MOEA/D and DMOEA-εC, are adopted. Finally, a typical example is used to demonstrate the advantage of the proposed method. A simple rule-based method is also employed for comparison. Comparative results show that DMOEA-εC is the best choice among the three MOMs for solving the MOMTA problem. The combination of DMOEA-εC for MOMTA and the coordinated path planning method for TOCPP can generate obviously better salvo attack schemes than the rule-based method.

关键词： Coordinated path planning missile-target assignment multi-missile salvo attack multiobjective optimization

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DYNAMIC REDUNDANCY RESOLUTION FOR MOBILE MANIPULATORS USING POSITION FUZZY controlLER

DYNAMIC REDUNDANCY RESOLUTION FOR MOBILE MANIPULATORS USING ...

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6th International Multi-Conference on systems, Signals and Devices

作者： Boukattaya, M. Jallouli, M. Damak, T. Control of Industrial Process Unit Intelligent Control Design and Optimization of Complex Systems Unit Tunisia

ISBN: (纸本)9781424443451

In this paper, we present a dynamic redundancy resolution technique for mobile manipulators using a position fuzzy controller. First, the dynamic model of the mobile manipulator in feasible motion space is given. Next, a control algorithm is proposed which resolve the redundancy by decoupling the motion of the system into the end-effector motion in the task space and an internal motion in the null space and controls them in prioritized basis with priority given to the primary task. In order to achieve a good end-effector trajectory tracking, a position fuzzy controller is used to provide the torques needed to move the end-effector along the desired trajectory. Simulation results are given to illustrate the coordination of two subsystems in executing the desired trajectories.

关键词： mobile manipulators dynamic redundancy resolution fuzzy controller

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Multi-objective Evolutionary Algorithm Based Graph Neural Network Architecture Search 11th

Multi-objective Evolutionary Algorithm Based Graph Neural Ne...

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11th International Symposium on Computational Intelligence and Industrial Applications, ISCIIA 2024

作者： He, Lianyi Liu, Xiaobo Xiang, Hongbo Wang, Guangjun School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China Key Laboratory of Geological Survey and Evaluation of Ministry of Education China University of Geosciences Wuhan430074 China

ISBN: (纸本)9789819647521

Graph Neural Networks (GNN) has become a powerful graph data processing method, which has been widely used in node classification, link prediction, and other graph analysis tasks. Due to the diversity and complexity of graph structures and information propagation, as well as the handling of heterogeneous graphs, etc., the design of GNNs presents many challenges. The existing methods have high classification accuracy, but their structures are very complex. In this paper, a graph neural network architecture search framework named MO-GNN, which is based on multi-objective evolutionary algorithm is proposed. Furthermore, a weight sharing strategy MO-GNN-WS is proposed to reduce the resource consumption caused by weight training of different architectures. To verify the performance of the proposed algorithm, experiments on four popular graph datasets are used for transduction and induction tasks. The experimental results show that the MO-GNN-WS algorithm outperforms the most advanced neural network architecture search methods in terms of classification accuracy and resource consumption. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Data Sharing

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An intelligent control Scheme for Burn-Through Point to Carbon Efficiency optimization in Iron Ore Sintering Process

An Intelligent Control Scheme for Burn-Through Point to Carb...

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第37届中国控制会议

作者： Sheng Du Min Wu Jinhua She School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems School of Engineering Tokyo University of Technology

The sintering process is an important step of preparing raw material for iron and steel smelting. It is a series of complex physico-chemical changes with high energy consumption, high pollution and large CO emissions. How to reduce carbon consumption while ensuring the quality and yield of sinter ore are the problems to be solved urgently. In this paper,An intelligent control scheme for burn-through point(BTP) to carbon efficiency optimization in iron ore sintering process is presented. The comprehensive coke ratio is employed as a measure of carbon efficiency;and the BTP, a measure of the stability of the sintering process. First, a model is established to predict the comprehensive coke ratio using a back propagation neural network, and the carbon efficiency is optimized using the particle swarm optimization algorithm. This yields an optimal strand velocity. Then, the control of the BTP is taken into consideration using an expert-fuzzy control strategy. This yields another strand velocity. Finally, these two kinds of strand velocity are integrated using the fuzzy satisfaction method to produce a control input for the strand velocity. It not only improves the carbon efficiency, but also ensures the stable running of the sintering process. Part of the strategy was tested in an actual plant, and the results show the effectiveness of the scheme.

关键词： Sintering process Carbon efficiency optimization Burn-through point intelligent control

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Adaptive-triggered H∞ sliding-mode optimal control for nonlinear input-limited systems

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Communications in Nonlinear Science and Numerical Simulation 2025年 149卷

作者： Zhang, Hongxu Wang, Honggui Department of Applied Mathematics Harbin University of Science and Technology Harbin150080 China Heilongjiang Provincial Key Laboratory of Optimization Control and Intelligent Analysis for Complex Systems Harbin University of Science and Technology Harbin150080 China

This paper concentrates on the H∞ sliding mode optimal control (SMOC) problem for nonlinear systems with mismatched interference and constrained input. Firstly, an adaptive-triggered strategy for the discontinuous control part is employed, which can suppress input interference and the separated matched disturbances. Also, the system trajectories are guaranteed to converge to the sliding manifold. Moreover, the adaptive-triggered strategy is optimized into self-triggered strategy with the aim to avoid the real-time measurement of triggered conditions, and the minimum time interval is obtained to prevent Zeno phenomenon. Subsequently, the optimal H∞ control problem of sliding motion turns into a two-person ZS game issue. To derive the solutions of event-trigger HJI equation, an adaptive dynamic programming (ADP) algorithm with critic-only structure is implemented to obtain the optimal control online. Furthermore, by utilizing the Lyapunov technique, the uniformly ultimately bounded (UUB) conditions about system state and the weight estimation error are obtained. At last, simulation outcomes are analyzed to validate the effectiveness of the control strategy. © 2025 Elsevier B.V.

关键词： Sliding mode control

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Fault Localization and State Estimation of Power Grid under Parallel Cyber-Physical Attacks

arXiv

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arXiv 2025年

作者： Ren, Junhao Zhao, Kai Zhang, Guangxiao Liu, Xinghua Zhai, Chao Xiao, Gaoxi School of Electrical and Electronic Engineering Nanyang Technological University Singapore639798 Singapore Institute of Catastrophe Risk Management Nanyang Technological University Singapore639798 Singapore Future Resilient Systems Singapore-ETH Centre Singapore138602 Singapore School of Electrical Engineering Xi’an University of Technology Xi’an710048 China Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems The Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

Parallel cyber-physical attacks (PCPA) refer to those attacks on power grids by disturbing/cutting off physical transmission lines and meanwhile blocking transmission of measurement data to dwarf or delay the system protection and recovery actions. Such fierce hostile attacks impose critical threats to the modern power grids when there is a fusion of power grids and telecommunication technologies. In this paper, we investigate the fault diagnosis problem of faulty transmission lines under a broader spectrum of PCPA for a linearized (or DC) power flow model. The physical attack mechanism of PCPA includes not only disconnection but also admittance value modification on transmission lines, for example, by invading distributed flexible AC transmission system (D-FACTS). To tackle the problem, we first recover the information of voltage phase angles within the attacked area. Using the information of voltage phase angle and power injection of buses, a graph attention network-based fault localization (GAT-FL) algorithm is proposed to find the locations of the physical attacks. By capitalizing on the feature extraction capability of the GAT on graph data, the fault localization algorithm outperforms the existing results when under cyber attacks, e.g., denial of service (DoS) attacks. A line state identification algorithm is then developed to identify the states of the transmission lines within the attacked area. Specifically, the algorithm restores the power injection of buses within the attacked area and then identities the state of all the transmission lines within the attacked area by solving a linear programming (LP) problem. Experimental simulations are conducted on IEEE 30/118 bus standard test cases to demonstrate the effectiveness of the proposed fault diagnosis algorithms. Copyright © 2025, The Authors. All rights reserved.

关键词： Cyber attacks

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GCN-Transformer Autoencoder with Knowledge Distillation for Unsupervised Video Anomaly Detection

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Journal of Advanced Computational Intelligence and intelligent Informatics 2025年第3期29卷 659-667页

作者： Yan, Mingchao Xiong, Yonghua She, Jinhua School of Automation China University of Geosciences No.388 Lumo Road Hongshan District Hubei Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems No.388 Lumo Road Hongshan District Hubei Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education No.388 Lumo Road Hongshan District Hubei Wuhan430074 China School of Engineering Tokyo University of Technology 1404-1 Katakura Hachioji Tokyo192-0982 Japan

Video anomaly detection is crucial in intelligent surveillance, yet the scarcity and diversity of abnormal events pose significant challenges for supervised methods. This paper presents an unsupervised framework that integrates graph attention networks (GATs) and Transformer architectures, combining masked autoencoders (MAEs) with self-distillation training. GATs are utilized to model spatial and inter-frame relationships, while Transformers capture long-range temporal dependencies, overcoming the limitations of traditional MAE and self-distillation approaches. The model employs a two-stage training process: first, a lightweight MAE combined with a GAT-Transformer fusion constructs a knowledge distillation module;second, the student autoencoder is optimized by integrating a graph convolutional autoencoder and a classification head to identify synthetic anomalies. We evaluate the proposed method on three representative datasets—ShanghaiTech Campus, UBnormal, and UCSD Ped2—and achieve promising results. © Fuji Technology Press Ltd.

关键词： Network coding

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Recursive estimation with compensation strategies under random access protocol and deception attacks

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IEEE Transactions on Signal Processing 2025年

作者： Li, Jiaxing Caballero-Aguila, Raquel Hu, Jun Linares-Perez, Josefa Harbin University of Science and Technology Department of Applied Mathematics Harbin150080 China University of Jaén Department of Statistics and Operations Research Jaén23071 Spain Harbin University of Science and Technology Heilongjiang Provincial Key Laboratory of Optimization Control and Intelligent Analysis for Complex Systems Harbin150080 China Harbin University of Science and Technology School of Automation Harbin150080 China University of Granada Department of Statistics and Operations Research Granada18071 Spain

In this paper, recursive least-squares linear estimation algorithms are proposed for stochastic systems influenced by uniform quantization, random access protocol (RAP) and deception attacks. With the purpose of enhancing communication efficiency and reducing unnecessary data collisions, RAP is adopted to schedule data signal transmissions that are also subject to deception attacks. In order to alleviate the side effect of missing information caused by RAP, three compensation strategies (zero-input, zero-order hold and prediction-compensation) are utilized. By resorting to an innovation method, covariance-based filters are designed and then fixed-point smoothers are obtained in light of available observations. Finally, a simulation experiment with comparisons is employed to demonstrate the effectiveness of the developed recursive estimation schemes, where the influence of attack probabilities on estimation accuracy is evaluated. © 1991-2012 IEEE.

关键词： Least squares approximations

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Trajectory reshaping based guidance with impact time and angle constraints

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Chinese Journal of Aeronautics 2016年第4期29卷 984-994页

作者： Zhao Yao Sheng Yongzhi Liu Xiangdong School of Automation Beijing Institute of Technology Key Laboratory for Intelligent Control and Decision of Complex Systems Beijing Institute of Technology

This study presents a novel impact time and angle constrained guidance law for homing missiles. The guidance law is first developed with the prior-assumption of a stationary target, which is followed by the practical extension to a maneuvering target scenario. To derive the closed-form guidance law, the trajectory reshaping technique is utilized and it results in defining a specific polynomial function with two unknown coefficients. These coefficients are determined to satisfy the impact time and angle constraints as well as the zero miss distance. Furthermore, the proposed guidance law has three additional guidance gains as design parameters which make it possible to adjust the guided trajectory according to the operational conditions and missile's capability. Numerical simulations are presented to validate the effectiveness of the proposed guidance law. (C) 2016 Chinese Society of Aeronautics and Astronautics. Production and hosting by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license.

关键词： Guidance Homing missiles Impact angle Impact time Trajectory reshaping

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A Facial Expression Emotion Recognition Based Human-robot Interaction System

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IEEE/CAA Journal of Automatica Sinica 2017年第4期4卷 668-676页

作者： Zhentao Liu Min Wu Weihua Cao Luefeng Chen Jianping Xu Ri Zhang Mengtian Zhou Junwei Mao School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems IEEE

A facial expression emotion recognition based human-robot interaction(FEER-HRI) system is proposed, for which a four-layer system framework is designed. The FEERHRI system enables the robots not only to recognize human emotions, but also to generate facial expression for adapting to human emotions. A facial emotion recognition method based on2D-Gabor, uniform local binary pattern(LBP) operator, and multiclass extreme learning machine(ELM) classifier is presented,which is applied to real-time facial expression recognition for robots. Facial expressions of robots are represented by simple cartoon symbols and displayed by a LED screen equipped in the robots, which can be easily understood by human. Four scenarios,i.e., guiding, entertainment, home service and scene simulation are performed in the human-robot interaction experiment, in which smooth communication is realized by facial expression recognition of humans and facial expression generation of robots within 2 seconds. As a few prospective applications, the FEERHRI system can be applied in home service, smart home, safe driving, and so on.

关键词： Emotion generation facial expression emotion recognition(FEER) human-robot interaction(HRI) system design

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