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第41届中国控制会议

作者： Qing Chang Shiqi Zheng Jiachun Sun Tao Song Liangguang Li School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

In this paper,we mainly study the global tracking problem for stochastic systems by the sampled data state feedback *** the condition of lower-triangular,the sampled data state feedback controller is constructed to make the states globally bounded,and the error between the system output and the reference signal is less than the specified allowable *** the same time stochastic phenomenon is considered in the nonlinear *** global tracking performance and stochastic stability are both achieved simultaneously.

关键词： Stochastic systems nonlinear systems state feedback sampled-data controllers

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Research on Energy Storage control Strategy Considering Economy 41

Research on Energy Storage Control Strategy Considering Econ...

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第41届中国控制会议

作者： Zihan Zhang Zhijian Fang Jie Cai Wenhe Peng School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

Energy storage system is generally used to ensure the stability and reliability of *** the system generally contains multiple energy storage units,and due to the process,material and other aspects of the limitation,the initial state of charge(SOC) of each energy storage unit cannot be guaranteed to be completely equal,which leads to the shortening of the life of energy storage unit,and affect the economic benefits of energy storage system ***,this paper analyzes the influence conditions between energy storage units according to the calculated formula of energy storage unit *** value of charge between energy storage systems is analyzed through the active power output of the system,and then the difference is obtained by comparing the value of charge of each energy storage unit with the average value of charge of each *** the iterative algorithm is used to update the state of each node,and the balance factor is introduced to gradually reduce the difference on the basis of droop control to optimize and control the output of these energy storage nodes to achieve SOC *** the economic benefits such as maintenance cost of energy storage system are ***,a working model of microgrid is established and the feasibility and economy of this method are verified by simulation.

关键词： Economy Micro grid Energy storage system Droop control SOC balance

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Stability Analysis for Delayed Neural Networks via a Relaxed Negative-Determination Quadratic Function Method 41

Stability Analysis for Delayed Neural Networks via a Relaxed...

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第41届中国控制会议

作者： Yu-Long Fan Ke-You Xie Xing-Chen Shangguan Hongzhang Wang Chuan-Ke Zhang School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

This paper presents an improved stability condition for neural networks with a time-varying ***,an improved Lyapunov-Krasovskii functional(LKF) is constructed by introducing the delay-product term and the augmented ***,a less conservative delay-dependent stability criterion for neural networks with a time-varying delay is established by utilizing the generalized reciprocally convex combination and a relaxed quadratic function ***,a numerical example is used to illustrate the merit and effectiveness of the proposed stability criterion.

关键词： Neural Networks Time-varying Delay Stability Analysis Reciprocally Convex Matrix Inequality NegativeDetermination Method

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A Task Assignment Scheme Designed for Online Urban Sensing Based on Sparse Mobile Crowdsensing

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IEEE Internet of Things Journal 2025年第11期12卷 17791-17806页

作者： Zeng, Hongjian Xiong, Yonghua She, Jinhua Yu, Anjun China University of Geosciences School of Automation Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Ministry of Education Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan430074 China Tokyo University of Technology School of Engineering Hachioji Tokyo192-0982 Japan Jiangxi Ganyue Expressway Co. Ltd Jiangxi Nanchang330000 China

Sparse Mobile Crowdsensing (SMCS) achieves urban-scale environmental sensing by assigning tasks to workers in specific subareas and inferring global data from the collected information. However, the effectiveness of SMCS is often limited because many studies overlook workers' mobility and data collection time during subarea selection, as well as the time constraints of the sensing cycle in task assignment. This may affect the task completion timeliness and data quality. To address these issues, we develop a subarea evaluation method based on deep reinforcement learning, considering both the temporal effectiveness of sensing tasks and the importance of subarea selection for data inference. Using the subarea evaluation values derived from this method, we establish an online urban sensing task assignment model which is subject to constraints of sensing cycle time and cost budget. This model aims to find the task assignment result that minimizes data inference error by maximizing the comprehensive utility value. Considering the characteristics of the task assignment model, we propose an evolutionary algorithm named OTA-EA, which is based on an improved genetic algorithm. Its enhanced evolutionary operators can avoid generating infeasible solutions while maintaining robust search and optimization performance. Lastly, we conduct experimental evaluations of these methods on the real-world datasets. The results demonstrate that our subarea evaluation method can significantly reduce the data inference error, and our evolutionary task assignment algorithm can achieve better task assignment results than the baseline algorithms. © 2014 IEEE.

关键词： Genetic algorithms

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Distributed Tracking control of Nonlinear Multi-agent systems Against False Data Injection Attacks 41

Distributed Tracking Control of Nonlinear Multi-agent System...

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第41届中国控制会议

作者： Yanhui Zhang Jian Sun Gang Wang Yong Xu the School of Automation and the Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology the Beijing Institute of Technology Chongqing Innovation Center IEEE

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

In this paper,the distributed resilient tracking control problem is investigated for nonlinear multi-agent systems with false data injection(FDI) attacks and unknown *** FDI attacks are considered in communication network between ***,the neighbor's information received by the agent may be wrong due to the attacks,which will affect tracking consensus ***,the approximate property of fuzzy logic systems are utilized to estimate unknown nonlinear *** backstepping framework,we design a distributed resilient control scheme under asymmetric *** asymmetric saturation nonlinearity,an auxiliary system is constructed to simplify designed progress of the *** on Lyapunov stability theory,it is proved that all signals in the closed-loop system are semi-globally uniformly bounded,and the followers' outputs are driven to a neighborhood near the output of ***,simulation results are presented to illustrate the effectiveness of the proposed method.

关键词： Adaptive resilient control nonlinear MASs FDI attacks asymmetric saturation

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Hybrid Group Consensus of Multi-agent systems with Time-delays and Additive Noises 41

Hybrid Group Consensus of Multi-agent Systems with Time-dela...

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第41届中国控制会议

作者： Chuanjian Li Xiaofeng Zong School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

The hybrid group consensus of multi-agent systems that consist of two groups in environments with time-delays and additive noises is studied in this *** hybrid group consensus implies that the agents in one group achieve strong consensus and the agents in another group achieve weak consensus.A new type of control protocol is proposed to achieve the following hybrid group consensus behavior:the agents in the first group and in the second group achieve strong consensus and weak consensus,*** sufficient conditions are obtained for the hybrid group consensus problem in both mean square and almost sure ***,a simulation example is given to illustrate the feasibility of the theoretical results.

关键词： multi-agent system hybrid group consensus time-delays additive noises

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Real-time Semantic Segmentation for Aggregating Long-Range Information and Region Understanding 41

Real-time Semantic Segmentation for Aggregating Long-Range I...

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第41届中国控制会议

作者： Yifan Chen Liping Yan Yuanqing Xia Bo Xiao Key Laboratory of Intelligent Control and Decision of Complex Systems School of AutomationBeijing Institute of Technology School of Artificial Intelligence Beijing University of Posts and Telecommunications

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

With the improvement of hardware performance,semantic segmentation based on convolutional neural network has achieved wide concern for its' advantage of high ***,in practical application scenarios,such as autonomous driving,what we care about is not only the segmentation accuracy,but also the ability of the model to process information in real-time on edge *** this paper,a lightweight and efficient real-time semantic segmentation network was proposed,which is based on a two-way structure,aggregates detailed spatial information and high-level semantic information,integrates long-range dependencies and region-level *** proposed algorithm achieves good *** conducted experiments based on an NVIDIA Geforce RTX 2080 SUPER graphics card and achieved 73.8% accuracy on Cityscapes dataset with a speed of 211 FPS,and 72.8% accuracy on Camvid dataset.

关键词： Semantic Segmentation Real-time Semantic Segmentation Deep Learning Bilateral Neural Network

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Optimizing Polynomial-Time Solutions to a Network Weighted Vertex Cover Game

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IEEE/CAA Journal of Automatica Sinica 2023年第2期10卷 512-523页

作者： Jie Chen Kaiyi Luo Changbing Tang Zhao Zhang Xiang Li the Adaptive Networks and Control Laboratory Department of Electronic EngineeringFudan UniversityShanghai 200433China the College of Mathematics and Computer Science Zhejiang Normal UniversityJinhua 321004 Yuxi Middle School Taizhou 317399China IEEE the College of Physics and Electronics Information Engineering Zhejiang Normal UniversityJinhua 321004China the College of Mathematics and Computer Science Zhejiang Normal UniversityJinhua 321004China the Adaptive Networks and Control Laboratory Department of Electronic EngineeringFudan UniversityShanghai 200433 the Institute of Complex Networks and Intelligent Systems Shanghai Research Institute for Intelligent Autonomous SystemsTongji UniversityShanghai 201210China

Weighted vertex cover(WVC)is one of the most important combinatorial optimization *** this paper,we provide a new game optimization to achieve efficiency and time of solutions for the WVC problem of weighted *** first model the WVC problem as a general game on weighted *** the framework of a game,we newly define several cover states to describe the WVC ***,we reveal the relationship among these cover states of the weighted network and the strict Nash equilibriums(SNEs)of the ***,we propose a game-based asynchronous algorithm(GAA),which can theoretically guarantee that all cover states of vertices converging in an SNE with polynomial ***,we improve the GAA by adding 2-hop and 3-hop adjustment mechanisms,termed the improved game-based asynchronous algorithm(IGAA),in which we prove that it can obtain a better solution to the WVC problem than using a the ***,numerical simulations demonstrate that the proposed IGAA can obtain a better approximate solution in promising computation time compared with the existing representative algorithms.

关键词： Game-based asynchronous algorithm(GAA) game optimization polynomial time strict Nash equilibrium(SNE) weighted vertex cover(WVC)

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Pipeline Anomaly Detection Based on KPCA and Cosine Distance Prototypical Network 26

Pipeline Anomaly Detection Based on KPCA and Cosine Distance...

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26th International Conference on Industrial Technology, ICIT 2025

作者： Yi, Kang Liu, Xin Hu, Wenkai Li, Yupeng 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

ISBN: (纸本)9798331521950

Accurately and promptly detecting the pipeline anomaly is crucial to the safe operation of pipeline systems, while a difficulty lies in that many existing methods require massive data for training models. However, pipelines are running under normal state for the most of the time, and labeled pipeline anomaly data is usually scarce. Among the commonly used sensors, vibration sensors are widely utilized in pipeline detection because of their advantages such as easy installation and high sensitivity. However, the vibration signal shows non-stationary characteristics when anomalies occur, and are contaminated by noises, making it difficult to represent the actual state with features extracted from either the time or frequency domain. Accordingly, this paper proposes a pipeline anomaly detection method based on the KPCA (kernel principal component analysis) and cosine distance prototypical network. First, features are extracted from original signals;then, the feature dimension is reduced by KPCA;last, the cosine distance is introduced to the prototypical network for anomaly detection. The effectiveness of the proposed method is demonstrated by case studies involving experimental data. © 2025 IEEE.

关键词： Frequency domain analysis

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Pore extraction method of rock thin section based on Attention U-Net

Pore extraction method of rock thin section based on Attenti...

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International Conference on Emerging Electronic and Automation Technology 2022, ICEEAT 2022

作者： Li, Mingjiang Zhang, Pan Hai, Tao School of Computer and Information Qiannan Normal University for Nationalities Duyun Guizhou558000 China School of Computer Sciences Baoji University of Arts and Sciences 721007 China Laboratory of Complex Systems and Intelligent Optimization of Guizhou Duyun Guizhou558000 China

This paper proposes a solution to the shortcomings of traditional segmentation methods. The labeling method uses the incomplete labeling method in weakly supervised labeling to simplify labeling and combines transfer learning to initialize the weight of the network in advance. According to the above ideas, an end-to-end deep learning model is trained. The fine rock particles have a greater segmentation impact, and in addition to that, when compared with the popular deep learning semantic segmentation approaches, they also have a significant improvement. The next phase is to continue improving the network by optimizing the parameters, with the number of network layers and the total number of parameters remaining unaltered. This requirement must be satisfied before moving on to the next stage. The capability of generalization enhances the impact of segmentation on particles as well as their accuracy. Experiments show that this method is significantly better than the traditional method for segmenting rock flakes with manual operation and has better results in the segmentation and extraction of fine particles compared with the mainstream convolutional neural network. © Published under licence by IOP Publishing Ltd.

关键词： Semantics

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