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IEEE Transactions on AgriFood Electronics 2025年第1期3卷 246-253页

作者： Wang, Xu Wang, Deyi He, Zhaoshui Lin, Zhijie Xie, Shengli Guangdong Mechanical and Electrical Polytechnic School of Electronics and Communication Guangzhou510550 China Guangdong University of Technology School of Automation Guangzhou510006 China Key Laboratory for IoT Intelligent Information Processing and System Integration of Ministry of Education Guangzhou510006 China Guangdong Provincial Key Laboratory of Intelligent Systems and Optimization Integration Guangzhou510006 China

Agriculture crop classification is helpful for agricultural production. However, it is challenging to classify crops from the agriculture image suffering from these problems: 1) Crops are often masked in complex backgrounds;2) There is high similarity between crop categories. To address these problems, an adaptive masking attention network (AMA-Net) is proposed for agriculture crop identification from natural images, where the adaptive masking (AM) module is developed to distinguish the crop from the complex background by selectively eliminating redundant information of feature maps, and the fair attention module is devised to identify similar crops between categories by modeling the fine-grained features. Experiments conducted on the benchmark show the effectiveness and superiority of the proposed AMA-Net, achieving the performance of 96.65%, 96.65%, 97.13%, and 96.72% on the accuracy, precision, recall, and F1-score, respectively, which is better than other state-of-the-art methods. © 2023 IEEE.

关键词： Crops Agriculture Accuracy Visualization Training Production Autonomous aerial vehicles Attention mechanisms Adaptive systems Support vector machines

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An Enhanced Particle Swarm Algorithm Based on Fitness Landscape Information 13

An Enhanced Particle Swarm Algorithm Based on Fitness Landsc...

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13th IEEE Congress on Evolutionary Computation, CEC 2024

作者： Diao, Zhenya Yu, Fei Guan, Jian Liu, Meitong School of Physics and Information Engineering Minnan Normal University Key Lab of Intelligent Optimization and Information Processing Zhangzhou36300 China School of Physics and Information Engineering Minnan Normal University Key Laboratory of Light Field Manipulation and System Integration Applications in Fujian Province Key Lab of Intelligent Optimization and Information Processing Zhangzhou36300 China

ISBN: (纸本)9798350308365

In the original Particle Swarm optimization (PSO), the selection of parameters significantly impacts the search capability of PSO. The paper introduces an innovative algorithm called Fitness Landscape-based PSO (FLPSO) to address the impact of parameter selection on the search capability of PSO. The algorithm focuses on acquiring fitness landscape information and analyzing the population state to intelligently select appropriate parameters in each generation. FLPSO defines four primary states: exploration, exploitation, convergence, and escaping state. In the convergence state, an elite learning strategy is incorporated to help the algorithm escape potential local optima by targeting the global best particle. To validate the efficacy of FLPSO, the paper conducted experiments on 30 different characteristic test functions from CEC2017. FLPSO was compared with six existing algorithms: PSO, PSO-TVAC, APSO, AWPSO, RPSO and ASRPPSO. The experimental results showed significant improvements in FLPSO, providing promising evidence for its effectiveness. © 2024 IEEE.

关键词： Particle swarm optimization (PSO)

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Solo Adaptation for Distributed Synchronization With Application to Event-Triggered Linear Multi-Agent systems

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IEEE Transactions on Automatic Control 2025年第6期70卷 4225-4232页

作者： Chen, Ci Zheng, Zhiyang Lewis, Frank L. Xie, Kan Xie, Shengli Guangdong University of Technology Guangdong Provincial Key Laboratory of Intelligent Systems and Optimization Integration Key Laboratory of Intelligent Information Processing and System Integration of IoT Ministry of Education School of Automation Guangzhou510006 China Guangdong University of Technology School of Automation Guangdong Guangzhou510006 China The University of Texas at Arlington UTA Research Institute Fort Worth76118 United States Guangdong University of Technology 111 Center for Intelligent Batch Manufacturing Based on IoT Technology School of Automation Guangzhou China Guangdong University of Technology Key Laboratory of Intelligent Detection and The Internet of Things in Manufacturing Ministry of Education School of Automation Guangzhou510006 China

We study a solo adaptation-based protocol design problem for distributed synchronization of event-triggered linear multi-agent systems (MAS) over general directed graphs. We show that a solo adaptive gain, a locally static control gain matrix, and a distributed state measurement are sufficient for obtaining adaptive distributed synchronization of linear MAS over directed graphs without any prior knowledge of the global communication network. We then extend the solo adaptation structure to formulate an event-triggered synchronization control protocol. The main feature of our result is that the time for triggering a subsequent event is now computed using the distributed event-triggered state measurement, rather than the continuous-time state measurement. © 1963-2012 IEEE.

关键词： Continuous time systems

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A Fast Generation Algorithm of Communication Topology for Three-dimensional Optimally Persistent Formation 33

A Fast Generation Algorithm of Communication Topology for Th...

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第33届中国控制与决策会议

作者： Guoqiang Wang Qianwei Lv Xiaoduo Li Xin Cao He Luo School of Management Hefei University of Technology Key Laboratory of Process Optimization and Intelligent Decision-Making Ministry of Education Engineering Research Center for Intelligent Decision-making & Information Systems Technologies Ministry of Education Key Laboratory of Urban ITS Technology Optimization and Integration Ministry of Public Security of China

ISBN: (纸本)9781665431293

To solve the communication topology generation problem of three-dimensional optimally persistent formation with leader constraint,a fast generation algorithm based on minimum cost arborescence,arc addition and path reverse operation is *** with the existing algorithms,this algorithm has a shorter calculation ***,the simulation results further verify the correctness and effectiveness of the algorithm.

关键词： Communication topology Leader constraint Three-dimensional optimal persistent formation Minimum cost arborescence Arc addition Path reverse operation

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Forming Circle Formations of Multi-agent systems Under Actuator Faults 5th

Forming Circle Formations of Multi-agent Systems Under Actu...

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5th Chinese Conference on Swarm Intelligence and Cooperative Control, CCSICC 2021

作者： Liu, Jiajun Ru, Xinfeng Xia, Weiguo Wang, Chen China National Aeronautical Radio Electronic Research Institute and National Key Laboratory of Science and Technology on Avionics System Integration Shanghai China Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education and School of Control Science and Engineering Dalian University of Technology Dalian China National Engineering Research Center of Software Engineering and the State Key Laboratory of Turbulence and Complex Systems Intelligent Biomimetic Design Lab College of Engineering Peking University Beijing China

ISBN: (纸本)9789811939976

A distributed fault-tolerant formation control law is designed in this paper for multi-agent systems under external disturbances and actuator faults including time-varying loss of effectiveness faults. The initial position of each agent is already on a circle and the control purpose is to form a desired formation on this circle. Based on this local information, a distributed adaptive formation control law is designed by employing the congelation of variables method to deal with time-varying actuator faults. Finally, a simulation example is given to verify the effectiveness of the adaptive fault-tolerant control design method. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Multi agent systems

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Hierarchy-based extended CBBA for multi-robot task assignment

Hierarchy-based extended CBBA for multi-robot task assignmen...

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2022 Chinese Automation Congress, CAC 2022

作者： Liu, Jiajun Xia, Weiguo Li, Fuqiang Wang, Peng China National Aeronautical Radio Electronic Research Institute National Key Laboratory of Science and Technology on Avionics System Integration China Dalian University of Technology Key Lab. of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education School of Control Science and Engineering China

ISBN: (纸本)9781665465335

This paper studies the task assignment problem of a multi-robot system with complex constraints including the robot speed limit, the task execution time window constraints, the arrival time, the trip cost, and different priorities of the tasks. A new bidding function is then designed for each robot. Based on the k-means algorithm, a hierarchy-based extended consensus-based bundle algorithm (CBBA) is proposed to find the optimal solution for the task allocation problem. Finally, simulation examples are presented to show the feasibility of the proposed algorithm and comparisons with existing algorithms show that the proposed algorithm can reduce the task assignment time with guaranteed reward values. © 2022 IEEE.

关键词： Multipurpose robots

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An Enhanced Particle Swarm Algorithm Based on Fitness Landscape Information

An Enhanced Particle Swarm Algorithm Based on Fitness Landsc...

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Congress on Evolutionary Computation

作者： Zhenya Diao Fei Yu Jian Guan Meitong Liu Key Lab of Intelligent Optimization and Information Processing School of Physics and Information Engineering Minnan Normal University Zhangzhou China Key Laboratory of Light Field Manipulation and System Integration Applications in Fujian Province Key Lab of Intelligent Optimization and Information Processing School of Physics and Information Engineering Minnan Normal University Zhangzhou China

ISBN: (数字)9798350308365

ISBN: (纸本)9798350308372

关键词： Sociology Particle swarm optimization Statistics Convergence

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Control of Vehicle Trajectory Tracking Under Extreme Conditions Based on ILQR

Control of Vehicle Trajectory Tracking Under Extreme Conditi...

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Electronic Technology and Information Science (ICETIS), International Conference on

作者： Jiandong Xing Zhihong Song Mengyue Cheng Qiwen Gou Xuesong Bai Siqi Chen School of Transportation Science and Engineering Beihang University Beijing China Hefei Innovation Research Institute Beihang University Hefei China Anhui Keli Information Industry Co. Ltd Hefei China Key Laboratory of Urban ITS Technology Optimization and Integration Ministry of Public Security Hefei China

ISBN: (数字)9798350388343

ISBN: (纸本)9798350388350

Vehicle maneuvers resembling drifting offer a significantly expanded range of motion, particularly valuable in extreme collision avoidance scenarios. However, existing control algorithms fall short in fulfilling the demands of trajectory tracking tasks under such extreme conditions. This paper introduces a novel ILQR controller capable of guiding vehicles through maneuvers akin to drifting, particularly in highly demanding collision avoidance scenarios. To address stability constraint issues within the controller, we integrate the Projected Newton method with ILQR theory to resolve state constraint problems within the QP framework. Additionally, input constraint issues are addressed through the utilization of hyperbolic cosine functions. Ultimately, experimental results demonstrate the vehicle's proficiency in accurately tracking collision avoidance trajectories.

关键词： Regulators Trajectory tracking Stability analysis Tires Planning Trajectory Collision avoidance

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A method for dividing roadside unit alliances with cooperative vehicle infrastructure system 3

A method for dividing roadside unit alliances with cooperati...

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3rd International Conference on Electronics Technology and Artificial Intelligence, ETAI 2024

作者： Chen, Siqi Hao, Ying Wei, Jing Xing, Jiandong Wang, Jixiang Beihang University 37 Xueyuan Road Haidian District Beijing100191 China Hefei Innovation Research Institute Beihang University West of the intersection between Wenzhong Road and Weiwu Road Xinzhan District Hefei230013 China Anhui Keli Information Industry Co. Ltd. 628 Huangshan Road Shushan District Hefei230000 China Key Laboratory of Urban ITS Technology Optimization and Integration Ministry of Public Security 628 Huangshan Road Shushan District Hefei230000 China North China University of Technology 5 Jinyuanzhuang Road Shijingshan District Beijing100144 China

ISBN: (纸本)9781510683143

With cooperative vehicle infrastructure system, information exchange can occur between vehicles and road side units(RSU), and there is potential for the improvement of communication benefits brought about by vehicle road collaboration to be explored. This article reduces the cost of roadside unit information dissemination through vehicle to vehicle(V2V) communication. The roadside units participating in the cooperation each distribute a portion of the message, while the vehicles exchange information during aggregation, thereby achieving information sharing. However, cooperation between roadside units can also lead to increased costs. To address this issue, this article establishes a collaborative vehicle road communication scenario and proposes a core network side alliance partitioning method based on message passing neural network (MPNN). The effectiveness of the algorithm is verified through simulation. © 2024 SPIE.

关键词： Deep reinforcement learning

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Hierarchy-based extended CBBA for multi-robot task assignment

Hierarchy-based extended CBBA for multi-robot task assignmen...

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Chinese Automation Congress (CAC)

作者： Jiajun Liu Weiguo Xia Fuqiang Li Peng Wang China National Aeronautical Radio Electronic Research Institute and National Key Laboratory of Science and Technology on Avionics System Integration China Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education and School of Control Science and Engineering Dalian University of Technology China

关键词： Costs Automation Heuristic algorithms Numerical simulation Time factors Resource management Multi-robot systems

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