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IEEE Transactions on Artificial Intelligence 2023年第2期4卷 268-281页

作者： Tian, Ye Pan, Jingwen Yang, Shangshang Zhang, Xingyi He, Shuping Jin, Yaochu Anhui University Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education Institutes of Physical Science and Information Technology Hefei230601 China Hefei Comprehensive National Science Center Institute of Artificial Intelligence Hefei230088 China Anhui University School of Computer Science and Technology Hefei230601 China Anhui University Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Artificial Intelligence Hefei230601 China Anhui University Anhui Engineering Laboratory of Human-Robot Integration System and Intelligent Equipment School of Electrical Engineering and Automation Hefei230601 China Bielefeld University Faculty of Technology Bielefeld33619 Germany

The sparse adversarial attack has attracted increasing attention due to the merit of a low attack cost via changing a small number of pixels. However, the generated adversarial examples are easily detected in vision since the perturbation to each pixel is relatively large. To achieve imperceptible and sparse adversarial attacks, this article formulates a bi-objective constrained optimization problem, simultaneously minimizing the 0 and 2 distances to the original image, and proposes a dual-population-based constrained evolutionary algorithm to solve it. The proposed method solves the optimization problem by evolving two populations, where one population is responsible for finding feasible solutions (i.e., successful attacks) and the other one is to minimize both the 0 and 2 distances. Moreover, a population initialization strategy and two genetic operators are customized to accelerate the convergence speed. Experimental results indicate that the proposed method can achieve high success rates with low attack costs, and strikes a better balance between the 0 and 2 distances than state-of-the-art methods. © 2020 IEEE.

关键词： Evolutionary algorithms

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Wood Broken Defect Detection With 3D Laser Scanning

Wood Broken Defect Detection With 3D Laser Scanning

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2022 Chinese Automation Congress, CAC 2022

作者： Ai, Zhijie Lin, Ye Xu, Zhezhuang Zhu, Yuhang Wu, Lianxu Fuzhou University School of Electrical Engineering and Automation Key Laboratory of Industrial Automation Control Technology and Information Processing Education Department of Fujian Province Fuzhou350000 China

ISBN: (纸本)9781665465335

Wood broken defects, such as cracks, penetrating dead knots and wanes, will seriously weaken the strength of the wood and destroy the structral integrity of the wood. Therefore, these defects should be inspected and then cut during the production. Although vision-based detection methods have been proposed to detect wood defect regions, they can not detect the defects that change in depth. To solve this problem, this paper focuses on the defect detection by measuring depth difference through 3D laser data. First, the 3D laser data is preprocessed to remove the noise. Secondly, we construct a support profile by multiple mean filtering at the line-level. Next, the residual components are obtained by subtracting the support profile from the profile data and the defect is determined by comparing the residual components and the setting threshold. Finally, we perform merging and filtering operation to determine the final position of defects. The experimental results verify the effectiveness of the proposed method. © 2022 IEEE.

关键词： Defects

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Designing Cluster Consensus on Higher-Order Interaction Networks

Designing Cluster Consensus on Higher-Order Interaction Netw...

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IEEE Conference on Decision and control

作者： Haoyu Wei Lulu Pan Haibin Shao Dewei Li Wenbin Yu Shibei Xue Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai China

This paper examines the cluster consensus design problem on higher-order interaction networks. Specifically, the higher-order interaction mechanism is captured by matrix-weighted networks that allow the interdependency across the dimensions of the agents' states, and the matrix-valued weight matrices $A_{ij}\in \mathbb{R}^{d\times d}$ associated with specific edges are further assumed to share the same nullspace for design purposes. Under mild assumptions on network connectivity, we first examine the case that the nullspace of positive semi-definite edges is spanned by a nonzero vector $\boldsymbol{\xi}\in \mathbb{R}^{d}$ and show that the predictable cluster consensus can be achieved, which is eventually located in the 1-dimensional linear space determined by span $\{\boldsymbol{\xi}\}$ and the average of agents' initial states. Moreover, the transient state of agents in each cluster can also be explicitly characterized. Namely, the derivative of the average state of agents in each cluster is perpendicular to span $\{\boldsymbol{\xi}\}$ . To generalize the above results, we proceed to examine the case that the nullspace of positive semi-definite edges is spanned by more than one linearly independent $d$ -dimensional vector, in which case, analogous results can be obtained, and the explicit geometric interpretation is also provided.

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Optimizing Parameter Design with Frequency and Clock Drift Constraints in Microgrids∗ 63

Optimizing Parameter Design with Frequency and Clock Drift C...

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63rd IEEE Conference on Decision and control, CDC 2024

作者： Yu, Chang Lu, Xiaoqing Wuhan University of Science and Technology School of Information Science and Engineering Wuhan430081 China Huazhong University of Science and Technology Ministry of Education Key Laboratory of Image Processing and Intelligent Control Wuhan430074 China Wuhan University School of Electrical Engineering and Automation Wuhan430000 China

ISBN: (纸本)9798350316339

Microgrids subjected to secondary cooperative control encounter significant challenges, including operational constraints and clock drifts, adversely affecting their stability and efficiency. This paper provides conditions that assure optimal microgrid performance in both transient and steady-state scenarios, focusing on the effects of clock drifts and fluctuations in load. Furthermore, we introduce a novel approach for designing secondary control parameters, specifically engineered to minimize steady-state discrepancies attributable to clock drifts while ensuring adherence to standards for transient operations. Comprehensive experimental validations corroborate the effectiveness of our proposed solutions. © 2024 IEEE.

关键词： Microgrids

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Framework for Designing Assessment Indicator system of Command and control systems Based on Task Element Flowchart

Framework for Designing Assessment Indicator System of Comma...

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International Conference on Big Data and information Analytics (BigDIA)

作者： Yufan Zhao Chao Jiang Yuehan Wang Yuanyuan Wang Haifeng Liu Key Laboratory of Information System and Technology Beijing Institute of Control and Electronic Technology Beijing China

We propose a framework for designing an effectiveness assessment indicator system for command and control systems. This framework encompasses three key parts: the design of task element flowcharts, iterative optimization of indicators, and check of indicator completeness. Introducing the task element flowcharts and the physical mapping of indicators, a dual-layer iterative optimization guiding approach to indicator system design is provided. This method mitigates the complexity associated with indicator system design, enhancing design efficiency. The indicator system built using this approach shows advantages of non-redundancy, non-repetition, quantifiability, and high completeness. Concurrently, comparing supporting data leads to construct a high-trust assessment algorithm and generate the scientifically comprehensive data collection requirements.

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Effect of Positive Temperature Coefficient Materials on the AC Breakdown Strength and Dielectric Properties of Epoxy Composites 4th

Effect of Positive Temperature Coefficient Materials on the ...

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4th International Symposium on Insulation and Discharge Computation for Power Equipment, IDCOMPU 2023

作者： Teng, Chenyuan Li, Shuo Zhou, Yuanxiang Zhang, Ling Zhang, Yunxiao Huang, Meng College of Information Engineering Zhejiang University of Technology Hangzhou310023 China State Key Laboratory of Control and Simulation of Power Systems and Generation Equipment Department of Electrical Engineering Tsinghua University Beijing100084 China State Key Laboratory of Alternate Electrical Power System With Renewable Energy Sources North China Electric Power University Beijing102206 China

ISBN: (纸本)9789819974122

In operation, the negative temperature coefficient (NTC) electrical resistivity characteristics of polymeric insulating materials causes DC electric field distortion within power equipment insulation and lead to the failure. The doping of positive temperature coefficient (PTC) ceramic particles can suppress the NTC characteristics of the composites, but the electrical properties under AC voltages are unrevealed. In this paper, epoxy composites (0–20 wt%) doped with polydopamine-coated PTC particles were prepared, whose AC breakdown strength and dielectric properties were tested. The results shows that the decrease of AC dielectric strength is smaller than that under DC voltages after the doping PTC particles, and the coating of polydopamine can enhance the AC dielectric strength. As the doping content increases, the dielectric constant and tanδ of the epoxy composites increases, and the maximum increase of dielectric loss power is about 2% of the loss power caused by the current-carrying conductor. The research provides a theoretical basis for the optimization of the insulating performance of the equipment under the AC-DC composite voltages. © Beijing Paike Culture Commu. Co., Ltd 2024.

关键词： Epoxy resins

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Edge-assisted Prediction and Predictive control for Flexible Platooning under Mixed Traffic Flow

Edge-assisted Prediction and Predictive Control for Flexible...

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IEEE Conference on Vehicular Technology (VTC)

作者： Fengkun Gao Bo Yang Jiahang Li Cailian Chen Xinping Guan Department of Automation Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai P. R. China

The uncertainty of human-driven vehicles (HDVs) has a significant impact on the movement of connected and automated vehicles (CAVs), especially on the CAV platoon. In this regard, the future trajectory information of the preceding HDV is essential for CAV platoon to develop a safe and smooth speed control strategy. However, constrained by computation and energy resources, on-board unit can not provide accurate predictions, which results in inefficient control strategy and even safety issues. Hence, we propose an edge-assisted prediction and a flexible cooperative adaptive cruise control (CACC) strategy in this paper. The challenges mainly lie in the design of coordination mechanism and control strategy. Considering the inaccuracy of prediction, an error-aware communication trigger scheme is first designed to decide whether to request the roadside unit (RSU) for performing accurate prediction with the aid of mobile edge computing (MEC). Further, a novel flexible tracking policy is proposed to deal with prediction error, which is integrated with model predictive control method to determine control inputs. Simulations based on real data, collected in Shanghai, China, demonstrate that our proposed method can significantly improve driving safety and speed smoothness.

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A Classification and Recognition Model of Distributed Resources Based on Feature Extraction

A Classification and Recognition Model of Distributed Resour...

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2023 IEEE International Conference on Energy Technologies for Future Grids, ETFG 2023

作者： Zhu, Yu Yang, Le Yang, Xizai Lu, Jiaxin Wang, Yuqing Wang, Fei State Grid Shaanxi Electric Power Co. Ltd. Information and Communication Company Information and Communication Technology R & D Center Xi'an710048 China State Key Laboratory of Power System Operation and Control Tsinghua University Beijing100084 China

ISBN: (纸本)9781665471640

The extensive integration of distributed resources such as distributed photovoltaic system and electric vehicles enhances the uncertainty of the load side greatly. Corresponding demand response strategies can be developed for different distributed resource types and characteristics of households' load, which is of great significance for new energy consumption and stable operation of the power system. However, only the net load power of households can be obtained through smart meters instead of the distributed resource types of households. Based on this, a distributed resource classification and identification model based on feature extraction is proposed in this paper, and effectively solves the problems of low accuracy and strong data dependence of existing recognition methods. Firstly, a generalized weather class generation algorithm based on clustering and voting is established, which is used to determine the weather class of each day to provide a basis for the following feature extraction. Then, based on the typical net load profiles under different generalized weather classes, a two-stage feature extraction and a classification identification model based on integrated learning algorithms are established to identify whether a user contains DPVS and EV, respectively. Finally, based on the category labels of each user for each stage, the final classification of the category to which the user belongs is carried out. Simulation experiments show that the recognition model built using the typical features extracted in the paper has good recognition accuracy. © 2023 IEEE.

关键词： classification and recognition Distributed photovoltaics system electric vehicles ensemble learning feature extraction

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Event-Triggered Distributed Multitarget Tracking With Unknown Clutter Rate and Detection Profile

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IEEE Transactions on Aerospace and Electronic systems 2025年

作者： Zheng, Litao Yang, Feng Shi, Lihong Guo, Zhengyu Cai, Yunze Shanghai Jiao Tong University Department of Automation Shanghai200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China Northwestern Polytechnical University School of Automation Xi'an710129 China Key Lab of Information Fusion Technology Ministry of Education of China Xi'an710129 China National Key Laboratary of Air-based Information Perceptian and Fusion Luoyang China State Key Laboratory of Submarine Geoscience Shanghai201913 China

This paper addresses communication bandwidth reduction and energy efficiency enhancement of a peer-to-peer sensor network for distributed multitarget tracking under unknown clutter rate and detection profile. We propose an event-triggered distributed bootstrap cardinalized probability hypothesis density (CPHD) filter, where the local filter consists of an estimator that estimates the clutter and detection parameters, and a tracker that estimates the number and states of targets. Specifically, the proposed approach enforces each sensor to broadcast its local posterior density only when it has high estimation quality and significant information gain, wherein the former is determined by the outputs of the local estimator and tracker, while the latter is measured via the Jensen-Shannondivergence. Then, we develop a modified weighted arithmetic average fusion method to separately fuse the cardinality distributions and intensity functions, in which the fusion weights are constructed based on estimation qualities and triggering thresholds, which is incorporated into the distributed flooding scheme for distributed averaging. Additionally, the Gaussian mixture implementations of the proposed event-triggered distributed bootstrap CPHD filter are given, where only Gaussian components with high weights are applied, thus reducing the effect of false alarms and, consequently, achieving a partial consensus across the network. Finally, the effectiveness of the proposed algorithm is validated through simulation experiments. © 1965-2011 IEEE.

关键词： Gaussian distribution

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Securing Mobile Robotic Networks Against Replacement Attack

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IEEE Transactions on Automatic control 2025年第7期70卷 4424-4438页

作者： Li, Yushan He, Jianping Chen, Cailian Guan, Xinping Cai, Lin Shanghai Jiao Tong University Dept. of Automation China Ministry of Education of China The Key Laboratory of System Control and Information Processing China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240 China University of Victoria Dept. of Electrical and Computer Engineering BC Canada

The security of mobile robotic networks (MRNs) has been an active research topic in recent years. This paper aims to secure the ubiquitous formation control of MRNs against the replacement attack, where an external robot can replace a formation robot by compromising the communication and physically interfering with the victim simultaneously. To counter this advanced attack, the novel idea of this work is to leverage the physical proximity of the formation shape and the interaction topology among robots for defense design. First, from the physical proximity perspective, we propose the convex neighbor polygon (CNP) to capture the geometric characteristic of the formation robots, and design a CNP-based security mechanism for the robots during the replacement attack. Then, from the interaction perspective, we introduce the indirect controllability to characterize the possibility that the attacker leverages the interaction between robots to deactivate the CNP mechanism, and establish the conditions regarding the topology structure and the attack input to counter the replacement. Finally, based on the obtained conditions, we demonstrate how to design the initiatory topology among the formation robots to enhance the defense performance. Comparative simulations verify the effectiveness of the proposed method. © 1963-2012 IEEE.

关键词： Topology

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