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Interference Suppression and Jitter Elimination Ability-Based Adaption Tracking Guidance for Robotic Fishes

IEEE/CAA Journal of Automatica Sinica 2025年第1期12卷 126-137页

作者： Dongfang Li Jie Huang Rob Law Xin Xu Limin Zhu Edmond Q.Wu IEEE the School of Electrical Engineering and Automation Fuzhou University the Key Laboratory of System Control and Information Processing Ministry of Education the School of Electrical Engineering and Automation Fuzhou University 5G+Industrial Internet Institute Fuzhou University the University of Macau the College of Mechatronics and Automation National University of Defense Technology the School of Mechanical Engineering Shanghai Jiao Tong University the Department of Computer Science and Engineering Shanghai Jiao Tong University

This work presents an adaptive tracking guidance method for robotic fishes. The scheme enables robots to suppress external interference and eliminate motion jitter. An adaptive integral surge line-of-sight guidance rule is designed to eliminate dynamics interference and sideslip issues. Limited-time yaw and surge speed observers are reported to fit disturbance variables in the model. The approximation values can compensate for the system's control input and improve the robots' tracking ***, this work develops a terminal sliding mode controller and third-order differential processor to determine the rotational torque and reduce the robots' run jitter. Then, Lyapunov's theory proves the uniform ultimate boundedness of the proposed method. Simulation and physical experiments confirm that the technology improves the tracking error convergence speed and stability of robotic fishes.

关键词： Adaptive integral surge line-of-sight approximation robotic fish speed observer

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Learning Knowledge Evolution with Time Duration from Finer-Time-Granularity Temporal Knowledge Graph

Learning Knowledge Evolution with Time Duration from Finer-T...

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2023 China Automation Congress, CAC 2023

作者： Du, Shaochong Chen, Kang Yang, Shijie Huo, Hong Fang, Tao Shanghai Jiao Tong University Department of Automation Shanghai China Ministry of Education Key Laboratory of System Control and Information Processing Shanghai China Shanghai Engineering Research Centre of Intelligent Control and Management Shanghai China

ISBN: (纸本)9798350303759

How to represent the temporal information corresponding to each fact in temporal knowledge graphs (TKGs) effectively is always challenging. Most existing representation learning methods usually map the timelines of knowledges into multiple points and ignore the underlying continuous time property and periodic characteristics behind those dense timestamps in finer-time granularity temporal knowledge graphs. A novel Knowledge Evolution with Time Duration (KETD) model is proposed for knowledge representation of temporal knowledge graphs with finer-time granularities. It represents the entity embedding as a time-varying nonlinear function to find the specific continuous time property from dense timestamps. To the best of our knowledge, it is the first attempt to learn embeddings of time durations and combines them into embeddings of entities and relations to predict potential periodic facts. It also uses the temporal point process to capture the impact of historical facts on the current fact. The experiments on self-built finer-time granularity TKG of Satellite-to-Earth Communication (STEC) and two public datasets have demonstrated the superiority of KETD compared to some baseline approaches. © 2023 IEEE.

关键词： Knowledge graph

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An Integrated Scheduling Algorithm of Satellite Observation and Data Download Based on Multi-Agent Deep Reinforcement Learning

An Integrated Scheduling Algorithm of Satellite Observation ...

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2023 China Automation Congress, CAC 2023

作者： Chen, Kang Du, Shaochong Huo, Hong Fang, Tao Shanghai Jiao Tong University Department of Automation Shanghai China Key Laboratory of System Control and Information Processing Ministry of Education Shanghai China Shanghai Engineering Research Centre of Intelligent Control and Management Shanghai China

ISBN: (纸本)9798350303759

The earth observation satellite scheduling has always been critical for the maximum use of limited satellite resources, which basically includes scheduling ground target observation and observation data downloading. Due to the complexity of the mathematical model and its NP-hardness, current research usually splits it into two problems to simplify the model. In this paper, we propose a model of the integrated scheduling problem of satellite observation and data downloading (ISP-SODD) based on the decentralized partially observable Markov decision process (Dec-POMDP), treating each satellite as an agent with autonomous decision-making capability. A multi-agent deep reinforcement learning-based (MADRL-based) algorithm is proposed to solve it. A series of simulation experiments of different scales validate the effectiveness of the method and its advantages compared with the traditional heuristic algorithms. To the best of our knowledge, this study is the first attempt to apply multi-agent reinforcement learning to a multi-satellite scheduling scenario with downloading considerations. © 2023 IEEE.

关键词： Reinforcement learning

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Global Update Guided Federated Learning 41

Global Update Guided Federated Learning

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第41届中国控制会议

作者： Qilong Wu Lin Liu Shibei Xue Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China School of Electronic Information Engineering Shanghai Dianji University

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

Federated learning protects data privacy and security by exchanging models instead of ***,unbalanced data distributions among participating clients compromise the accuracy and convergence speed of federated learning *** alleviate this problem,unlike previous studies that limit the distance of updates for local models,we propose global-updateguided federated learning(FedGG),which introduces a model-cosine loss into local objective functions,so that local models can fit local data distributions under the guidance of update directions of global ***,considering that the update direction of a global model is informative in the early stage of training,we propose adaptive loss weights based on the update distances of local *** simulations show that,compared with other advanced algorithms,FedGG has a significant improvement on model convergence accuracies and ***,compared with traditional fixed loss weights,adaptive loss weights enable our algorithm to be more stable and easier to implement in practice.

关键词： Federated Learning Cosine Similarity Adaptive Loss Weights

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Top gate engineering of field-effect transistors based on wafer-scale two-dimensional semiconductors

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Journal of Materials Science & Technology 2022年第11期106卷 243-248页

作者： Jingyi Ma Xinyu Chen Yaochen Sheng Ling Tong Xiaojiao Guo Minxing Zhang Chen Luo Lingyi Zong Yin Xia Chuming Sheng Yin Wang Saifei Gou Xinyu Wang Xing Wu Peng Zhou David Wei Zhang Chenjian Wu Wenzhong Bao State Key Laboratory of ASIC and System School of MicroelectronicsFudan UniversityShanghai200433China In Situ Devices Center Shanghai Key Laboratory of Multidimensional Information ProcessingEast China Normal UniversityShanghai 200241China School of Electronic Information Soochow UniversitySuzhou215006China

The investigation of two-dimensional(2D)materials has advanced into practical device applications,such as cascaded logic ***,incompatible electrical properties and inappropriate logic levels remain enormous *** this work,a doping-free strategy is investigated by top gated(TG)MoS_(2) field-effect transistors(FETs)using various metal gates(Au,Cu,Ag,and Al).These metals with different work functions provide a convenient tuning knob for controlling threshold voltage(V_(th))for MoS_(2) *** instance,the Al electrode can create an extra electron doping(n-doping)behavior in the MoS_(2) TG-FETs due to a dipole effect at the gate-dielectric *** this work,by achieving matched electrical properties for the load transistor and the driver transistor in an inverter circuit,we successfully demonstrate wafer-scale MoS_(2) inverter arrays with an optimized inverter switching threshold voltage(V_(M))of 1.5 V and a DC voltage gain of 27 at a supply voltage(V_(DD))of 3 *** work offers a novel scheme for the fabrication of fully integrated multistage logic circuits based on wafer-scale MoS_(2) film.

关键词： Two-dimensional semiconductor MoS_(2) Top gate Field effect transistor Logic inverter

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Distributed Optimization of Heterogeneous Linear Multi-Agent systems with Unknown Disturbances 63

Distributed Optimization of Heterogeneous Linear Multi-Agent...

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63rd IEEE Conference on Decision and control, CDC 2024

作者： Duan, Mengmeng Zhu, Shanying Yang, Ziwen Chen, Cailian Guan, Xinping The authors are with the Department of Automation Shanghai Jiao Tong University Shanghai 200240 ChinaKey Laboratory of System Control and Information Processing Ministry of Education of China Shanghai 200240 China and also Shanghai Engineering Research Center of Intelligent Control and Management Shanghai 200240 China

ISBN: (纸本)9798350316339

In this paper, we investigate the distributed optimization problem for heterogeneous linear multi-agent systems with unknown disturbances. By applying the primal-dual method and the time-scale separation technique, a distributed dynamic controller without using any disturbance information is proposed. Based on the optimal condition, the relationship between the optimal solution and the equilibrium point of the system is established, and it is shown that the distributed optimization problem is solved provided that the closed-loop system is stable. Then, inspired by the nonsingular perturbation analysis, it is proved that the closed-loop system is exponentially input-to-state stable with respect to the derivative of the disturbance. Numerical examples are provided to illustrate the theoretical results. © 2024 IEEE.

关键词： Closed loop systems

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Distributed Secondary control of DC Microgrids with Operation Loss Reduction

Distributed Secondary Control of DC Microgrids with Operatio...

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第43届中国控制会议

作者： Maoxiang Qiu Zhicheng Zhang Zhiqiang Zuo Yijing Wang Tianjin Key Laboratory of Intelligent Unmanned Swarm Technology and System School of Electrical and Information Engineering Tianjin University Key Laboratory of System Control and Information Processing Ministry of Education

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

In DC microgrids, current sharing and voltage regulation are two main objectives for real-time control, while the operation loss reduction is typically achieved by steady-state optimization. However, the ratio of current sharing is generally determined by the result of the centralized optimization in the classical hierarchical control framework of DC microgrids. Such an issue brings insufficient capability in respond to the changes of photovoltaic power and stored energy in the solar-powered energy systems. To handle this, this work proposes a distributed control scheme for single-bus DC microgrids. Under the proposed controller, the objectives of current sharing, bus voltage regulation and the total operation loss(converter loss and line loss) reduction can be guaranteed simultaneously. Moreover, the constraints on line currents and bus voltage are tackled as ***, simulations verify the performance of the proposed control scheme.

关键词： DC Microgrids Current Sharing Voltage Regulation Operation Loss Reduction Distributed Secondary control

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Health monitoring by optical fiber sensing technology for rechargeable batteries

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eScience 2024年第1期4卷 79-95页

作者： Yi Zhang Yanpeng Li Zezhou Guo Jianbo Li Xiaoyu Ge Qizhen Sun Zhijun Yan Zhen Li Yunhui Huang State Key Laboratory of Material Processing and Die&Mould Technology School of Materials Science and EngineeringHuazhong University of Science and TechnologyWuhanHubei430074China School of Optical and Electronic Information National Engineering Laboratory for Next Generation Internet Access SystemWuhan National Laboratory for OptoelectronicsHuazhong University of Science and TechnologyWuhanHubei430074China Henan Key Laboratory of Laser and Opto-electric Information Technology School of Electrical and Information EngineeringZhengzhou UniversityZhengzhouHenan45001China

With the proposal of a“smart battery,”real-time sensing by rechargeable batteries has become progressively more important in both fundamental research and practical ***,many traditional sensing technologies suffer from low sensitivity,large size,and electromagnetic interference problems,rendering them unusable in the harsh and complicated electrochemical environments of *** optical sensor is an alternative approach to realize multiple-parameter,multiple-point measurements ***,it has garnered significant *** analyzing these measured parameters,the state of interest can be decoded to monitor a battery's *** review summarizes current progress in optical sensing techniques for batteries with respect to various sensing parameters,discussing the current limitations of optical fiber sensors as well as directions for their future development.

关键词： Optical fiber sensing Rechargeable battery Real-time sensing Health monitoring

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Cross-Modality Guided Multi-Scale Feature Representation Based Image Compression for Industrial Scene Understanding 22

Cross-Modality Guided Multi-Scale Feature Representation Bas...

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22nd IEEE International Conference on Industrial Informatics, INDIN 2024

作者： Tu, Jingzheng Yan, Yan Lu, Ying Chen, Cailian Zhou, Shiru China Academy of Aerospace Science and Innovation Beijing100088 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China Department of Automation Shanghai Jiao Tong University Shanghai200240 China

ISBN: (纸本)9798331527471

Industrial surveillance videos capture subsequent video frames and deliver them to processing servers for video analytics. In such a case, image compression is a promising technology in industrial scene understanding due to its reduced transmission burden. Existing works focus on establishing macroscopic visual feature maps that contain compact image information. In this article, a cross-modality guided multi-scale feature representation based image compression method is proposed for understanding industrial scenes. Firstly, an image compressing framework with multi-grained representation (MGRIC) is proposed for industrial scene understanding, which builds image patch, structure, semantic, and signal levels feature maps. Secondly, an encoder-decoder architecture is designed for image compression with diverse granularities. Thirdly, an interaction policy between different levels is developed to ensure the subsequent level’s decoding. Experiments on the CUB-200-2011 dataset demonstrate that the proposed MGRIC method achieves competitive performance, which verifies its effectiveness. © 2024 IEEE.

关键词： Decoding

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Optimal control Synthesis of Markov Decision Processes for Efficiency with Surveillance Tasks 63

Optimal Control Synthesis of Markov Decision Processes for E...

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63rd IEEE Conference on Decision and control, CDC 2024

作者： Chen, Yu Yin, Xuanyuan Ye, Hao Li, Shaoyuan Yin, Xiang Shanghai Jiao Tong University Department of Automation and Key Laboratory of System Control and Information Processing Shanghai200240 China Nanyang Technological University School of Chemistry Chemical Engineering and Biotechnology Singapore Tsinghua University Department of Automation China

ISBN: (纸本)9798350316339

We investigate the problem of optimal control synthesis for Markov Decision Processes (MDPs), addressing both qualitative and quantitative objectives. Specifically, we require the system to fulfill a qualitative surveillance task in the sense that a specific region of interest can be visited infinitely often with probability one. Furthermore, to quantify the performance of the system, we consider the concept of efficiency, which is defined as the ratio between rewards and costs. This measure is more general than the standard long-run average reward metric as it aims to maximize the reward obtained per unit cost. Our objective is to synthesize a control policy that ensures the surveillance task while maximizes the efficiency. We provide an effective approach to synthesize a stationary control policy achieving -optimality by integrating state classifications of MDPs and perturbation analysis in a novel manner. Our results generalize existing works on efficiency-optimal control synthesis for MDP by incorporating qualitative surveillance tasks. © 2024 IEEE.

关键词： Markov processes

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