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2023 China Automation Congress, CAC 2023

作者： Man, Jingtao Zeng, Zhigang Xiao, Qiang Key Laboratory of Image Information Processing and Intelligent Control Ministry of Education of China Wuhan China

ISBN: (纸本)9798350303759

Spatial deployment of large-scale heterogeneous multi-agent systems (HMASs) over desired 2D or 3D curves is investigated in this paper. With assumption that HMASs consist of numerous first-order agents (FOAs) and second-order agents (SOAs) that could obtain local information of desired curves and their positions relative to their closest neighbors, the collective dynamics of large-scale HMASs are modeled as heterogeneous partial differential equations (PDEs). In particular, this paper introduces series-dependent topological weights between neighboring agents, which are more versatile and practical than constant topological weights commonly used in previous studies. A novel single-point control scheme is proposed, where an informed agent is situated between the last FOA and first SOA. This operation could not only ensure successful implementation of spatial deployment, but also guarantee well-posedness of the constructed heterogeneous error PDEs. By utilizing inequality techniques, sufficient conditions for exponential convergence of error system are derived. A numerical example is presented to demonstrate effectiveness of the proposed approaches. © 2023 IEEE.

关键词： Multi agent systems

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HScore: A Target Attention-based Filter Pruning with Visualizing the Area of Feature Map

HScore: A Target Attention-based Filter Pruning with Visuali...

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International Neural Network Society Workshop on Deep Learning Innovations and Applications, INNS DLIA 2023

作者： Zhang, Chenrui Zhuang, Chenyi Key Laboratory of System Control and Information Processing Shanghai Jiao Tong University Shanghai China

Neural network pruning plays an important role in the deployment on resource-constrained devices by reducing the scale of the network and the computational complexity. Different from existing pruning methods that only consider the amount of information filters contain, we think the distribution of information is more important to the model accuracy. Then we use visualization of feature map to consider the impact of the attention area on the network decision. In order to directly relate the attention area with confidence score, we propose HScore to use interpolation and normalization to visualize the attention area of feature map and calculate the confidence score by putting only the attention area into the model. The principle behind is that if the feature map focuses on an area which can achieve a higher classification confidence, then the corresponding channel is important to keep the accuracy of model. The confidence score of attention area represents the importance of the channel to the model and filters with smaller confidences would be pruned. The experiment results prove that HScore can prune more redundant filters while maintaining better accuracy. Notably, our method can reduce 68.6% parameters and 73.0% FLOPs of ResNet-110 even with 0.14% top-1 accuracy increase on CIFAR-10. With ResNet-50, we achieve a 55% FLOPs reduction with only a loss of 1.03% in the top-1 accuracy on LSVRC-2012, which has advanced the state-of-the-art. © 2023 The Authors. Published by Elsevier B.V.

关键词： Industry 4.0

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Weak signal detection method based on novel composite multistable stochastic resonance

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Chinese Physics B 2023年第5期32卷 178-187页

作者：焦尚彬高蕊薛琼婕史佳强 Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi’an University of TechnologyXi’an 710048China School of Electronic and Electrical Engineering Baoji University of Arts and SciencesBaoji 721016China

The weak signal detection method based on stochastic resonance is usually used to extract and identify the weak characteristic signal submerged in strong noise by using the noise energy transfer *** propose a novel composite multistable stochastic-resonance(NCMSR)model combining the Gaussian potential model and an improved bistable *** with the traditional multistable stochastic resonance method,all the parameters in the novel model have no symmetry,the output signal-to-noise ratio can be optimized and the output amplitude can be improved by adjusting the system *** model retains the advantages of continuity and constraint of the Gaussian potential model and the advantages of the improved bistable model without output saturation,the NCMSR model has a higher utilization of *** the output signal-to-noise ratio as the index,weak periodic signal is detected based on the NCMSR model in Gaussian noise andαnoise environment respectively,and the detection effect is *** application of NCMSR to the actual detection of bearing fault signals can realize the fault detection of bearing inner race and outer *** outstanding advantages of this method in weak signal detection are verified,which provides a theoretical basis for industrial practical applications.

关键词： weak signal detection composite multistable stochastic resonance bearing fault detection

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Attitude Stabilization control for Unmanned Aerial Vehicle with Robotic Arm Based on Fixed-Time Observer Active Disturbance Rejection control 3rd

Attitude Stabilization Control for Unmanned Aerial Vehicle w...

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3rd International Conference on Machine Learning, Cloud Computing and Intelligent Mining, MLCCIM 2024

作者： Mo, Fan Gu, Chaochen Wang, Kunkun Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China

ISBN: (纸本)9789819616930

To address the periodic disturbances introduced by the manipulator mounted on the drone, as well as the overall system parameter variations caused by the robotic arm carried by the Unmanned Aerial Vehicle (UAV), the fixed-time convergence observer (FTCO) is introduced to ADRC to enhance the dynamic characteristics, including overshoot and convergence speed. The Active Disturbance Rejection controller (ADRC) is employed as the fundamental controller for UAV systems while the FTCO is used to rapidly observe disturbances and compensate them to the controller, aiming to counteract interference. The UAV system is established to verify the effect of Fixed-Time Convergence Observer-Active Disturbance Rejection controller (FTCO-ADRC) when it is compared to conventional ADRC and PID controller. The simulation outcome reveals that the FTCO-ADRC perform better in convergence speed, overshoot and robustness. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Disturbance rejection

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Optimization of the Internet of Remote Things Data Acquisition Based on Satellite UAV Integrated Network

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China Communications 2023年第7期20卷 15-28页

作者： Yuanyuan Yao Dengyang Dong Sai Huang Chunyu Pan Shuo Chen Xuehua Li Key Laboratory of Information and Communication Systems Ministry of Information IndustryBeijing Information Science and Technology UniversityBeijing 100101China Key Laboratory of Modern Measurement&Control Technology Ministry of EducationBeijing Information Science and Technology UniversityBeijing 100101China Key Laboratory of Universal Wireless Communications Ministry of EducationBeijing University of Posts and TelecommunicationsBeijing 100876China

In order to achieve dependable and efficient data acquisition and transmission in the Internet of Remote Things(IoRT),we investigate the optimization scheme of IoRT data acquisition under the unmanned aerial vehicle(UAV)-low earth orbit(LEO)satellite integrated space-air-ground network,in which the UAV acquires data from massive Internet of Things(IoT)devices in special *** combine with the actual scenario,we consider two different data types,that is,delay-sensitive data and delay-tolerant data,the transmission mode is accordingly divided into two *** delay-sensitive data,the data will be transmitted via the LEO satellite relay to the data center(DC)in *** delay-tolerant data,the UAV will store and carry the data until the acquisition is completed,and then return to *** to nonconvexity and complexity of the formulated problem,a multi-dimensional optimization Rate Demand based Joint Optimization(RDJO)algorithm is *** algorithm first uses successive convex approximation(SCA)technology to solve the non-convexity,and then based on the block coordinate descent(BCD)method,the data acquisition efficiency is maximized by jointly optimizing UAV deployment,the bandwidth allocation of IoRT devices,and the transmission power of the ***,the proposed RDJO algorithm is compared with the conventional *** consequences demonstrate that the efficiency of IoRT data acquisition can be greatly improved by multi-parameter optimization of the bandwidth allocation,UAV deployment and the transmission power.

关键词： Internet of Remote Things dataacquisi-tion unmanned aerial vehicle LEO satellite

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Multi-Objective Team Personality Tourism Route Design Based on Fuzzy APACA 5

Multi-Objective Team Personality Tourism Route Design Based ...

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5th IEEE International Conference for Emerging Technology, INCET 2024

作者： Song, Xiaoling Peng, Huanhuan Key Laboratory of Intelligent Information Processing and Control of Chongqing Municipal Institutions of Higher Education Chongqing Three Gorges University India

ISBN: (纸本)9798350361155

In order to solve the challenge of multi-objective team personalized tourism route design, in view of the shortcomings of the existing divide and conquer algorithms, this study proposes an innovative personalized tourism route design method based on fuzzy APACA. This new scheme uses the principles of gradient descent theory to accurately identify and locate key influencing factors, and accordingly carries out a sensible classification of indicators to reduce possible interference. At the same time, by using the unique mechanism of fuzzy APACA, this scheme cleverly constructs the design strategy of tourism routes. The empirical results show that this scheme shows a significant improvement compared with the traditional divide and conquer algorithm in terms of key performance indicators such as the accuracy of personalized tourism route design and the processing efficiency of key factors, showing its obvious strong advantages. In the multi-objective team, the personalized tourism route design plays a crucial role, which can accurately predict and optimize the growth trend and output results of the multi-objective team's personalized tourism route design. However, in the face of complex simulation tasks, traditional divide-and-conquer algorithms show some inherent shortcomings, especially when dealing with multi-level challenges, their performance is often unsatisfactory. To overcome this, this study introduces a new idea of fuzzy APACA optimization for the design of personalized tourism routes, and accurately controls the influencing parameters through gradient descent theory, which is used as the road map for index allocation, and then uses fuzzy APACA to innovate and construct a system scheme. The test results clearly point out that in the context of the evaluation criteria, the new scheme has been significantly optimized in terms of accuracy and processing speed for a variety of challenges, showing stronger performance superiority. Therefore, in the design of multi-

关键词： Design

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Turbulent drag reduction by sector-shaped counter-flow dielectric barrier discharge plasma actuator

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Chinese Physics B 2025年第2期34卷 362-370页

作者： Borui Zheng Shaojie Qi Minghao Yu Jianbo Zhang Linwu Wang Dongliang Bian School of Automation and Information Engineering Xi’an University of TechnologyXi’an 710048China School of Mechanical and Precision Instrument Engineering Xi’an University of TechnologyXi’an 710048China Science and Technology on Plasma Dynamics Laboratory Air Force Engineering UniversityXi’an 710038China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi’an 710048China Shaanxi University Key Laboratory of Photonic Power Devices and Discharge Regulation Xi’an 710048China

The primary objective in aircraft transportation is to minimize turbulent drag, thereby conserving energy and reducing emissions. We propose a sector-shaped counter-flow dielectric barrier discharge plasma actuator, which leverages jet synthesis for drag reduction. A drag control experiment was conducted in a low-speed wind tunnel with a controlled flow velocity of 9.6 m/s(Re = 1.445 × 10^(4)). This study investigated the effects of varying pulse frequencies and actuation voltages on the turbulent boundary layer. Using a hot-wire measurement system, we analyzed the pulsating and time-averaged velocity distributions within the boundary layer to evaluate the streamwise turbulent drag reduction. The results show that the local TDR decreases as the pulse frequency increases, reaching a maximum reduction of approximately 20.97% at a pulse frequency of 50 Hz. In addition, as the actuation voltage increases, the friction coefficient decreases, increasing the drag reduction rate. The maximum drag reduction of approximately 33.34% is achieved at an actuation voltage of 10 kV.

关键词： plasma flow control turbulent boundary layer turbulent drag reduction

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Optimization of Tiered Pricing Strategy for Smart Grid Considering Clean Energy

Optimization of Tiered Pricing Strategy for Smart Grid Consi...

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2024 China Automation Congress, CAC 2024

作者： Wang, Xiaocheng Li, ZeLong Sun, Pengjiao Han, Qiaoni Tianjin Key Laboratory of Wireless Mobile Communications and Power Transmission College of Electronic and Communication Engineering Tianjin Normal University Key Laboratory of System Control and Information Processing Ministry of Education Shanghai Jiao Tong University China School of Electrical and Information Engineering Tianjin University Key Laboratory of System Control and Information Processing Ministry of Education Shanghai Jiao Tong University China

ISBN: (纸本)9798350368604

With the rapid development of new energy technology, it has become a trend to combine wind and solar power generation into the smart grid. In this paper, wind power generation and photovoltaic power generation are introduced into the smart grid, and taking into account the consumption capacity of consumers at different levels, a tiered pricing scheme considering the uncertainty of wind and solar energy is proposed. Firstly, we establish probability density functions of power generation for wind power generation and photovoltaic power generation respectively to express the uncertainty of wind energy and solar energy. To meet the energy demand of consumers at all levels, we present the energy demand model of consumers after considering their electricity demand and temperature influence. Then, we formulate the optimal pricing problem for the electricity market under the framework of tiered pricing, so as to make the energy market get satisfactory income while meeting the energy demand of consumers. Finally, we use the particle swarm optimization algorithm to determine the optimal pricing strategy of the energy market. The simulation results show that when meeting the energy demand of consumers in different temperature conditions, the optimal pricing can be found that meets the satisfactory income of the energy market. © 2024 IEEE.

关键词： Clean energy

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Infrared Dim Small Target Detection Algorithm Based on Adaptive Attention Transformer Network

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Journal of Shanghai Jiaotong University (Science) 2025年 1-13页

作者： Ding, Leqi Xia, Yilin Wang, Biyun Cai, Yunze Department of Automation Shanghai Jiao Tong UniversityKey Laboratory of System Control and Information Processing of Ministry of Education Shanghai200240 China National Key Laboratory of Air-based Information Perception and Fusion Henan Luoyang471009 China Shanghai Institute of Aerospace Control Technology Infrared Detection Technology R & D Center of China Aerospace Science and Technology Corporation Shanghai201109 China

This paper presents a novel algorithm for detecting infrared dim small targets in complex backgrounds by integrating both global and local feature information. The proposed method employs an adaptive attention transformer network which addresses challenges associated with computational complexity and information redundancy in traditional self-attention mechanisms. A global context aggregation module is designed to address the loss of small target features in high-level feature maps. This module compensates for spatial distribution information during the multi-scale feature fusion process, ensuring the preservation of target features. Comparison experiments were conducted on two datasets, NUAA-SIRST and IRSTD-1k. The proposed algorithm achieved 0.784 for mIoU and 0.878 for F-measure on NUAA-SIRST, 0.632 for mIoU and 0.807 for F-measure on IRST-1k, all of which are the highest values. The proposed algorithm shows a significant improvement over other existing detection algorithms, demonstrating its capability to accurately extract both local and global features of targets with high recall rates and low false alarm rates across various scenarios. The ablation study results highlight the significant improvements contributed by the key modules to the proposed algorithm. (Figure presented.) © Shanghai Jiao Tong University 2025.

关键词： A adaptive attention global context aggregation module infrared dim small target detection TP391.4 Transformer network

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Electromagnetic metamaterial agent

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Light(Science & Applications) 2025年第1期14卷 118-130页

作者： Shengguo Hu Mingyi Li Jiawen Xu Hongrui Zhang Shanghang Zhang Tie Jun Cui Philipp del Hougne Lianlin Li State Key Laboratory of Advanced Optical Communication Systems and Networks School of ElectronicsPeking UniversityBeijing100871China National Key Laboratory for Multimedia Information Processing School of Computer SciencePeking UniversityBeijing100871China State Key Laboratory of Millimeter Waves Southeast UniversityNanjing210096China Pazhou Laboratory(Huangpu) GuangzhouGuangdong510555China Univ Rennes CNRSIETR-UMR 6164F-35000RennesFrance

Metamaterials have revolutionized wave control;in the last two decades,they evolved from passive devices via programmable devices to sensor-endowed self-adaptive devices realizing a user-specified *** deep-learning techniques play an increasingly important role in metamaterial inverse design,measurement post-processing and end-to-end optimization,their role is ultimately still limited to approximating specific mathematical relations;the metamaterial is still limited to serving as proxy of a human operator,realizing a predefined ***,we propose and experimentally prototype a paradigm shift toward a metamaterial agent(coined metaAgent)endowed with reasoning and cognitive capabilities enabling the autonomous planning and successful execution of diverse long-horizon tasks,including electromagnetic(EM)field manipulations and interactions with robots and *** recently released foundation models,metaAgent reasons in high-level natural language,acting upon diverse prompts from an evolving complex ***,metaAgent's cerebrum performs high-level task planning in natural language via a multi-agent discussion mechanism,where agents are domain experts in sensing,planning,grounding,and *** response to live environmental feedback within a real-world setting emulating an ambient-assisted living context(including human requests in natural language),our metaAgent prototype self-organizes a hierarchy of EM manipulation tasks in conjunction with commanding a *** masters foundational EM manipulation skills related to wireless communications and sensing,and it memorizes and learns from past experience based on human feedback.

关键词： agent prompt reasoning

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