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49th Annual Conference of the IEEE Industrial Electronics Society, IECON 2023

作者： Xu, Changyi Huo, Mingyu Zhang, Xiaokang School of Control Science and Engineering Dalian University of Technology Dalian China School of Mechatronic Engineering and Automation Shanghai University Shanghai China

ISBN: (纸本)9798350331820

As a benchmark of the aviation industry, JT9D aero engine is a general object to study the new algorithms. controlling the low pressure shaft speed is of great significance to the output power of JT9D. But the traditional PID controller often has overshoot. This kind of 'vibration' is a challenge to the various parts of the sophisticated aero engine. Solving this control problem with the help of reinforcement learning algorithms has become a new research direction. The basic framework of reinforcement learning is to explore a strategy that maximizes the expected reward through the continuous interaction between Agent and Environment. But in the interacting process, the behavior of Agent may be dangerous, especially when the interactive Environment is a complex or sophisticated system, such as aero engine. In order to solve the above problem, inspired by the inheritance and development of knowledge in human society, this paper proposes a reinforcement learning algorithm with giants teaching mechanism. To examine the effectiveness, this paper takes the JT9D aero engine as the Environment to verify the effect on the speed control of the low pressure shaft. And the experiments of Proportion Integral Differential(PID) and Soft Actor-Critic(SAC) algorithms are also studied as a comparison. Experimental results show that our algorithm is more effective in limiting low pressure shaft speed overshoot and avoiding algorithm runaway. © 2023 IEEE.

关键词： Reinforcement learning

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Robust control for Interval Type-2 T-S Fuzzy Discrete Systems with Input Delays and Cyber Attacks

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Journal of Systems Science & Complexity 2023年第4期36卷 1443-1462页

作者： LIU Chuang WU Jinxia YANG Weidong School of Automation University of Science and Technology BeijingBeijing 100083China College of Control Science and Engineering BoHai UniversityJinzhou 121001China College of Science Liaoning University of TechnologyJinzhou 121001China

This paper focuses on the robust control issue for interval type-2 Takagi-Sugeno(IT2 T-S)fuzzy discrete systems with input delays and cyber *** lower and upper membership functions are first utilized to IT2 fuzzy discrete systems to capture parameter *** considering the influences of input delays and stochastic cyber attacks,a newly fuzzy robust controller is ***,the asymptotic stability sufficient conditions in form of LMIs for the IT2 closed-loop systems are given via establishing a Lyapunov-Krasovskii ***,a solving algorithm for obtaining the controller gains is ***,the effectiveness of the developed IT2 fuzzy method is verified by a numerical example.

关键词： Asymptotic stability fuzzy robust control input delays IT2 T-S fuzzy discrete systems stochastic cyber attacks

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Privacy-Preserving Average Consensus Algorithm Under Round-Robin Scheduling Protocol

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IEEE/CAA Journal of Automatica Sinica 2024年第7期11卷 1705-1707页

作者： Yingjiang Guo Wenying Xu Haodong Wang Jianquan Lu Shengli Du the School of Mathematics Southeast UniversityNanjing 21189China the School of Electronic Information and Electrical Engineering Chengdu UniversityChengdu 610106Chengdu 610106China the School of Artificial Intelligence and Automation Beijing University of TechnologyBeijing 100124 the Engineering Research Center of Intelligent Perception and Autonomous Control Ministry of EducationBeijing 100124China

Dear Editor,Over the past decades,cooperative control and distributed optimization have gained significant research attention due to their broad applications such as signal processing,robotics,and social networks[1],[2].As a fundamental component of distributed control and optimization,the issue of average consensus has become a recurring topic of interest[3],[4].

关键词： optimization Round Robin

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Research on Wireless Power Transfer System for Aerospace Rotating Mechanism Applications 19th

Research on Wireless Power Transfer System for Aerospace Rot...

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19th Annual Conference of China Electrotechnical Society, ACCES 2024

作者： Tong, Lei Zhao, Wenbo Zhang, Qiang Lu, Ming Zhang, Jiantao Zhu, Chunbo School of Electrical Engineering and Automation Harbin Institute of Technology Harbin150001 China Beijing Institute of Control Engineering Beijing100000 China

ISBN: (纸本)9789819647996

With the popularization of wireless power transfer (WPT) in consumer electronics, this technology has attracted more and more researchers’ attention in the fields of automobile, aerospace, underwater ships and so on. WPT has become a subversive solution to the pain-point problem of many technical fields. At present, the rotating power supply in the aerospace is mainly realized by slip rings or cables. Slip rings are essentially current-carrying contact mechanical system, with the problems of short circuit and open circuit, which have become a technical bottleneck for long-life and high-reliability aerospace rotating mechanisms. WPT does not have mechanical wear problems and cable-drag problems. In this paper, a wireless rotating power supply system is proposed according to the requirements of space rotating mechanism, achieving an output power of 2.5 kW with an efficiency of 92% each channel. © Beijing Paike Culture Commu. Co., Ltd. 2025.

关键词： Inductive power transmission

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HarmonyNav: Robot Navigation in Human-Robot Coexistence Environment Considering Group and Pedestrian Intentions

HarmonyNav: Robot Navigation in Human-Robot Coexistence Envi...

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2024 Jiangsu Annual Conference on automation, JACA 2024

作者： Wang, Yutao Fang, Fang Liu, Chenyang Fan, Tao Li, Yi The Key Laboratory of Measurement and Control of Complex Systems of Engineering School of Automation Southeast University Ministry of Education Nanjing210096 China

ISBN: (纸本)9781837242689

Service robots must navigate efficiently and harmoniously in human-robot coexistence environments. Previous studies often treated pedestrians as independent entities, ignoring human intentions and leading to group intersections and performance issues. We introduce HarmonyNav, a crowd navigation algorithm that enhances human-robot harmony. Our method uses Human-Robot Interaction sub-networks to account for indirect group impacts on pedestrians and predicts pedestrian trajectories to infer intentions. Employing proximal policy optimization (PPO) in reinforcement learning, we develop a harmonious navigation policy. In simulation experiments, our results show improved navigation performance, reducing group intersections and individual intrusions. © The Institution of engineering & Technology 2024.

关键词： Reinforcement learning

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Improved target detection algorithm based on YOLOv5s 24

Improved target detection algorithm based on YOLOv5s

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6th International Conference on control and Computer Vision, ICCCV 2024

作者： Chen, Boyang Han, Chunxiao Wu, Han Tianjin Key Laboratory of Information Sensing & Intelligent Control School of Automation and Electrical Engineering Tianjin University of Technology and Education China

ISBN: (纸本)9798400718045

Target detection is a research hotspot in the field of computer vision and machine learning, and the deep learning model greatly improves the efficiency of target detection and classification by obtaining feature information and classification through multi-layer neural networks, which is the mainstream algorithm for target detection at present. In this paper, YOLOv5s target detection algorithm is improved, and the SIoU loss function is chosen to replace the CIoU loss function used in the original model, while the SimAM attention mechanism is added to the Neck module of the YOLOv5s model, and it is proved through experiments that the improved model improves the average precision (mAP@0.5) by 0.2% over the original model, and the recall rate (Recall) is improved by 0.8%. The faster convergence and improved precision of the model further improves the performance of the model. © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Adversarial machine learning

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Dynamic Quantized control of Fuzzy Semi-Markov Jump Systems With Fading Channels: An Improved Event-Triggered Mechanism

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IEEE Transactions on Systems, Man, and Cybernetics: Systems 2025年第5期55卷 3519-3531页

作者： Hu, Meng-Jie Park, Ju H. Cheng, Jun Wang, Yan-Wu China University of Mining and Technology School of Information and Control Engineering Xuzhou221116 China Yeungnam University Department of Electrical Engineering Gyeongsan38541 Korea Republic of Guangxi Normal University School of Mathematics and Statistics Guilin541006 China Huazhong University of Science and Technology School of Artificial Intelligence and Automation Wuhan430074 China

This article focuses on the dynamic quantized control for Takagi-Sugeno fuzzy semi-Markov jump systems (T-S FSMJSs) under fading channels and deception attacks, employing an improved event-triggered mechanism (ETM) strategy. Specifically, a more generalized semi-Markov process (SMP) that is governed by a higher-level deterministic switching signal (HLDSS) is addressed. A novel dynamic ETM is skillfully developed based on the information of quantization and two internal dynamic adjusting variables to further enhance the network bandwidth utilization. The dual asynchronous phenomenon between the plant and controller (asynchronous modes and mismatched premise variables) is addressed. This implies that the designed controller is not required to share the same membership functions and modes as the plant, establishing a more rational structure. The hidden semi-Markov model (HSMM) is attained to characterize the stochastic varying channel fading amplitudes. The Lyapunov function incorporating mode and fuzzy information is constructed to establish sufficient criteria ensuring the strictly dissipative performance and mean-square exponential stability (MSES) of the resulting closed-loop systems, and a new security fuzzy dual asynchronous controller is then developed. Finally, the efficacy and applicability of the results are demonstrated through numerical and practical examples. © 2025 IEEE.

关键词： Membership functions

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Research on Automotive Parts Recognition Based on Improved YOLOv5 Algorithm

Research on Automotive Parts Recognition Based on Improved Y...

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2024 International Conference on Remote Sensing, Mapping, and Image Processing, RSMIP 2024

作者： Xu, Yu Hu, Shan Ming, Rui Zhang, Tianzhi School of Automation and Electrical Engineering Tianjin University of Technology and Education Key Laboratory of Information Sensing & Intelligent Control Tianjin China

ISBN: (纸本)9781510680012

With the continuous development of the automotive industry, the target detection and recognition of automotive parts have become crucial factors for automakers to enhance automation levels. In this paper, to ensure improved detection accuracy while meeting real-time detection requirements, we propose an enhanced YOLOv5 model for automotive parts recognition. This method optimizes candidate box parameters using the K-Means algorithm, addresses feature mismatch issues through variational convolution, and optimizes the loss function using GIOU instead of IOU. Experimental results show that the improved YOLOv5 algorithm achieves an average precision of 99.1%, representing a relative improvement of 1.72% over Fast R-CNN and 3.91% over the standard YOLOv5 algorithm. Furthermore, it demonstrates excellent real-time detection performance, meeting the demands of practical application scenarios. © 2024 SPIE.

关键词： Object recognition

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Offline Parameter Identification for Medium-Voltage Permanent Magnet Synchronous Machine 8

Offline Parameter Identification for Medium-Voltage Permanen...

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8th International Conference on Power Energy Systems and Applications, ICoPESA 2024

作者： Zhang, Lei Shi, Shengdong Feng, Ming Chen, Yufeng School of Automation and Electrical Engineering Chengdu Technological University Chengdu China Sichuan Institute for Food and Drug Control Chengdu China

ISBN: (纸本)9798350351668

This paper describes a novel offline parameter identification technique, specifically for medium voltage interior permanent magnet synchronous machine driven by Cascaded H-Bridge inverter. Accurate identification of parameters is indispensable to correct decoupling of current loop in vector control. Unlike low voltage permanent magnet synchronous machines commonly driven by the conventional six-switch inverter, the proposed method specifically focuses on medium voltage applications and takes advantage of the topology of cascaded H bridge to tune machine parameters of resistance, d-axis inductance, q-axis inductance and magnetic flux linkage. By properly modifying the topology structure, the accuracy of identification can be improved with issues like voltage drop across semiconductor devices and low duty ratio considered. In the end, the paper presents simulation results using proposed technique, followed by theoretical analysis as proof of the feasibility of the proposed method. © 2024 IEEE.

关键词： Permanent magnets

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AIoT for Aircraft Final Assembly:An Intelligent and Collaborative Framework

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Journal of Communications and Information Networks 2024年第3期9卷 262-276页

作者： Cheng Ren Xiaojing Wen Xinping Guan Cailian Chen Yehan Ma Department of Automation Shanghai Jiao Tong UniversityShanghai 200240China Key Laboratory of System Control and Information Processing Ministry of Education of ChinaShanghai 200240China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai 200240China School of Electronic Information and Electrical Engineering Shanghai Jiao Tong UniversityShanghai 200240China

Aircraft final assembly line(AFAL)involves thousands of processes that must be completed before ***,the heavy reliance on manual labor in most assembly processes affects the quality and prolongs the delivery *** the advent of artificial intelligence of things(AIoT)technologies has introduced advancements in certain AFAL scenarios,systematically enhancing the intelligence level of the AFAL and promoting the widespread deployment of artificial intelligence(AI)technologies remain significant *** address these challenges,we propose the intelligent and collaborative aircraft assembly(ICAA)framework,which integrates AI technologies within a cloud-edge-terminal *** ICAA framework is designed to support AI-enabled applications in the AFAL,with the goal of improving assembly efficiency at both individual and multiple process *** analyze specific demands across various assembly scenarios and introduce corresponding AI technologies to meet these *** three-tier ICAA framework consists of the assembly field,edge data platform,and assembly cloud platform,facilitating the collection of heterogeneous terminal data and the deployment of AI *** framework enhances assembly efficiency by reducing reliance on manual labor for individual processes and fostering collaboration across multiple *** provide detailed descriptions of how AI functions at each level of the ***,we apply the ICAA framework to a real AFAL,focusing explicitly on the flight control system testing *** practical implementation demonstrates the effectiveness of the framework in improving assembly efficiency and promoting the adoption of AIoT technologies.

关键词： intelligent aircraft final assembly line AIoT cloud-edge-terminal framework design

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