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Model-Driven Deep Learning-Based Optimization of Downlink Precoding and Fronthaul Compression in Cell-Free MIMO systems

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IEEE Transactions on Network Science and Engineering 2025年第3期12卷 1804-1817页

作者： Chen, Yijie Xia, Wenchao Cai, Shu Zheng, Gan Zhu, Hongbo Nanjing University of Posts and Telecommunications Jiangsu Key Laboratory of Wireless Communications and Internet of Things Engineering Research Center of Health Service System Based on Ubiquitous Wireless Networks Ministry of Education Nanjing210003 China Nanjing University of Posts and Telecommunications Jiangsu Key Laboratory of Intelligent Information Processing and Communication Technology Nanjing210003 China

Cell-free multiple-input multiple-output (MIMO) system is a promising solution for wireless communications. However, the potential in improving system performance is restricted due to the capacity-limited fronthaul links. To tackle this problem, we utilize the compress-and forward approach, which leverages various compression and encoding techniques to reduce the fronthaul overhead. Thus, jointly optimizing precoding and fronthaul compression presents a significant challenge. However, current optimization algorithms frequently entail high computational complexity because of their iterative processes, rendering impractical for real-time use. To overcome this challenge, we present a model-driven deep learning-based framework to characterize the structure of precoding vectors and the compression matrix via low-dimensional parameters, leveraging the uplink-downlink duality as the expert knowledge. A deep neural network can learn these low-dimensional "key features" from channel state information. Simulation results indicate that our approach achieves performance comparable to the optimal algorithm and substantially reduces complexity. © 2013 IEEE.

关键词： Channel state information

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Semi-Autonomous Navigation Based on Local Semantic Map for Mobile Robot

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Journal of Shanghai Jiaotong university(Science) 2025年第1期30卷 27-33页

作者： ZHAO Yanfei XIAO Peng WANG Jingchuan GUO Rui Department of Automation Institute of Medical RoboticsShanghai Jiao Tong UniversityShanghai200240China State Key Laboratory of System Control and Information Processing Ministry of Education of ChinaShanghai200240China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240China State Grid Intelligence Technology Co. Ltd.Jinan250013China

Mobile robots represented by smart wheelchairs can assist elderly people with mobility *** paper proposes a multi-mode semi-autonomous navigation system based on a local semantic map for mobile robots,which can assist users to implement accurate navigation(e.g.,docking)in the environment without prior *** order to overcome the problem of repeated oscillations during the docking of traditional local path planning algorithms,this paper adopts a mode-switching method and uses feedback control to perform docking when approaching semantic *** last,comparative experiments were carried out in the real *** show that our method is superior in terms of safety,comfort and docking accuracy.

关键词： semi-autonomous navigation mobile robot semantic map voice interaction

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

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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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3D measurement of scattering media based on self-supervised fringe domain transformation

3D measurement of scattering media based on self-supervised ...

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2024 International Conference on Optical and Photonic Engineering, icOPEN 2024

作者： Tan, Ji Niu, Haipeng Luo, Suofan Liu, Jia He, Zhaoshui School of Automation Guangdong University of Technology Guangzhou510006 China Guangdong University of Technology Key Laboratory for IoT Intelligent Information Processing and System Integration Ministry of Education Guangzhou510006 China

ISBN: (数字)9781510688117

ISBN: (纸本)9781510688100

The scattering media measurement for structured light techniques remains challenging due to the subsurface scattering that destroys fringe patterns and introduces phase error. Recently, deep learning has been successfully applied to fringe analysis. Unfortunately, collecting a large scale of labeled data is difficult, especially in scattering media measurement scenarios. Inspired by image style transfer, we proposed a high-precision scattering medium measurement method based on self-supervised fringe domain transformation. Specifically, by treating degraded fringe and ideal fringe as two pattern styles, a cycle generation strategy is developed to achieve fringe enhancement by translating between two fringe domains. Two generators and two discriminators are used to form cycle-consistency constraints for self-supervised learning with unpaired dataset. Additionally, we combine numerical and physical constraints to jointly optimize network parameters, effectively suppressing phase-shift errors and improving phase quality. Since the proposed approach eliminates the need for label data, it exhibits great potential for applying deep learning to scattering medium measurement. Experiments verify that our method can obtain high-quality 3D morphology of translucent objects. © 2025 SPIE.

关键词： Velocity measurement

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OSSR: Online Scalable Scheduling and Routing for Industrial Time-Sensitive Networking

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IEEE Transactions on Network Science and Engineering 2025年第3期12卷 1761-1775页

作者： Xu, Lei Xu, Qimin Zhang, Yanzhou Wang, Shouliang Chen, Cailian Guan, Xinping Shanghai Jiao Tong University School of Electronic Information and Electrical Engineering Shanghai200240 China Shanghai Jiao Tong University Shanghai Key Laboratory of Integrated Administration Technologies for Information Security Shanghai200240 China Shanghai Jiao Tong University School of Electronics Information and Electrical Engineering Shanghai200240 China Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China Shanghai Jiao Tong University SJTU-Paris Elite Institute of Technology Shanghai200240 China

As the promising deterministic networking technology of Industrial Internet of Things (IIoT), Time-Sensitive Networking (TSN) has been widely investigated in recent years. Most existing research focuses on offline scheduling and routing for TSN, which is time-consuming and thus unsuitable for dynamic stream demands. To tackle this problem, an online scalable scheduling and routing (OSSR) scheme is proposed for TSN in this paper. A novel slot occupancy representation (SOR) model is established based on divisibility theory to transform the clique-based to a three-level tree-based mode in complex IIoT scenarios. This transformation reduces the computational complexity of maximum slot occupancy judgment from exponential to linear complexity. Based on the above SOR model, a load balance metric for stream scheduling is constructed to guide the optimal routing. Assessed by this metric, an online decoupled routing and scheduling algorithm is proposed to minimize the maximum slot occupancy of all links while guaranteeing high scalability. Evaluation results show that the proposed OSSR scheme outperforms the existing approaches with better adaption to dynamics and lower slot occupancy of links. © 2013 IEEE.

关键词： Scheduling algorithms

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Co-Design of Dynamic Quantizer and Small-Gain-Based Distributed Model Predictive control of Nonlinear Continuous system

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IEEE Transactions on control of Network systems 2025年

作者： Zheng, Yi Zhang, Yueyan Li, Shaoyuan Luo, Min Shanghai Jiao Tong University Department of Automation China Ministry of Education of China Key Laboratory of System Control and Information Processing Shanghai China

This paper presents a co-design control scheme that integrates Distributed Model Predictive control with dynamic quantizers for networked nonlinear continuous systems operating under limited communication bandwidth. Each subsystem-based Model Predictive control formulation considers the dynamic quantizer's influence within the optimization problem in the proposed method. Both the quantizer parameters and the control law are optimized simultaneously in real time, which offers potential improvements in the performance of the closed-loop system within a certain communication limitation. A stability constraint based on small-gain Lyapunov theory is designed for each subsystem's controller, allowing for a relaxation of the restrictions on the closed-loop subsystems compared to decentralized approaches. Additionally, a sufficient condition that ensures the stability of the overall system is provided. Simulation results demonstrate the effectiveness of the proposed co-design method. © 2014 IEEE.

关键词： Predictive control systems

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Convolution Type of Metaplectic Cohen's Distribution Time-Frequency Analysis Theory, Method and Technology

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IEEE Transactions on information Theory 2025年第3期71卷 2292-2314页

作者： Cui, Manjun Zhang, Zhichao Han, Jie Chen, Yunjie Cao, Chunzheng Nanjing University of Information Science and Technology School of Mathematics and Statistics Center for Applied Mathematics of Jiangsu Province Jiangsu International Joint Laboratory on System Modeling and Data Analysis Nanjing210044 China Nanjing University of Information Science and Technology School of Mathematics and Statistics Nanjing210044 China Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education Shanghai200240 China Hainan Normal University Key Laboratory of Computational Science and Application of Hainan Province Haikou571158 China Nanjing University of Information Science and Technology School of Remote Sensing and Geomatics Engineering Nanjing210044 China

The conventional Cohen's distribution can't meet the requirement of additive noises jamming signals high-performance denoising under the condition of low signal-to-noise ratio, it is necessary to integrate the metaplectic transform for non-stationary signal fractional domain time-frequency analysis. In this paper, we embark on blending time-frequency operators and coordinate operator fractionizations to formulate the definition of the joint fractionizations metaplectic Wigner distribution (JFMWD), based on which we integrate the generalized metaplectic convolution to address the unified representation issue of the convolution type of metaplectic Cohen's distribution (CMCD), whose special cases and essential properties are also derived. We blend Wiener filter principle and fractional domain filter mechanism of the metaplectic transform to design the least-squares adaptive filter method in the JFMWD domain, giving birth to the least-squares adaptive filter-based CMCD whose kernel function can be adjusted with the input signal automatically to achieve the minimum mean-square error (MSE) denoising in Wigner distribution domain. We discuss the optimal symplectic matrices selection strategy of the proposed adaptive CMCD through the minimum MSE minimization modeling and solving. Some examples are also carried out to demonstrate that the proposed filtering method outperforms some state-of-the-arts including the classical Gaussian filter, the Cohen's distribution filtering methods with fixed kernel functions, the classical Wiener filter, the adaptive generalized linear canonical convolution-based filtering method, the adaptive Cohen's distribution filtering method, the adaptive JFMWD-based Cohen's distribution filtering method, and the adaptive generalized metaplectic convolution-based Cohen's distribution filtering method in noise suppression. © 1963-2012 IEEE.

关键词： Adaptive filtering

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Online Voltage Regulation of Distribution Networks in Energy Sharing Markets: a Feedback-Based Method With Parameter Estimation

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IEEE Transactions on Smart Grid 2025年

作者： Wang, Wenyue Liu, Yiming Wang, Zhaojian Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Department of Automation Shanghai200240 China

With the number of prosumers rising quickly, energy sharing markets in distribution networks are emerging. The trading of active power influences the power flow in the distribution network, which will cause voltage fluctuation when the line resistance is not trivial. In this paper, we investigate the voltage regulation problem of distribution networks with the consideration of electricity markets. We first formulate the problem in the form of a non-cooperative game. The uniqueness of generalized Nash Equilibrium (GNE) is proved. Then, a feedback-based GNE seeking algorithm is proposed with online parameter estimation without knowing accurate values of resistance and reactance. The estimation error is proved to be accurate in expectation. The convergence of the algorithm is also guaranteed theoretically. Finally, numerical results in the IEEE 33-bus system validate the effectiveness of the algorithm. © 2010-2012 IEEE.

关键词： Power distribution networks

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Extended State Observer-based Hybrid Dynamic Event-Triggered Consensus control with External Disturbances 24

Extended State Observer-based Hybrid Dynamic Event-Triggered...

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2nd International Conference on Frontiers of Intelligent Manufacturing and Automation, CFIMA 2024

作者： Pei, Wenliang Hua, Changchun Cui, Hailong Zhao, Guanglei Ma, Zhuang The Institute of Electrical Engineering The Key Lab of Intelligent Rehabilitation and Neuroregulation in Hebei Province Key Laboratory of Intelligent Control and Neural Information Processing Ministry of Education Yanshan University Hebei China Tangshan University Hebei China

ISBN: (纸本)9798400710681

This paper solves the event-triggered robust consensus problem of disturbed multi-agent systems (MASs) in fully distributed fashion. First, a distributed extended state observer (DESO) is developed for appropriately estimating system states and external disturbances. Then, by utilising these estimates, a fully distributed event-triggering control protocol, that composes of an adaptive distributed controller to avoid using global information while maintaining desired consensus property, and a novel hybrid dynamic event-triggering mechanism (ETM) to save communication resources, is put forward for the MASs. It is notable that an auxiliary differential equation is incorporated in the triggering condition, with which, positive minimum interevent times (MIETs) are available to ease the hardware implementation, while being with adaptive coefficients, the proposed hybrid dynamic ETM can be independent of any global information. Finally, the obtained main results are testified via a numerical example. © 2024 Copyright held by the owner/author(s).

关键词： State estimation

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Distributed Identification With Input Design for Network systems

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IEEE Transactions on control of Network systems 2025年

作者： Mao, Xiangyu He, Jianping Fang, Chongrong Shanghai Jiao Tong University The Dept. of Automation China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China

The distributed identification of network systems under local observation has recently become one of the research hot spots. Due to the unobservable influence of other subsystems and the noise, it is difficult for local subsystems to achieve convergent identification under local observations. This paper proposes a distributed identification algorithm for local subsystems to identify their parameter matrices under local observation with a guarantee of convergence. We obtain the necessary and sufficient conditions for the convergence of local identification. We prove that by injecting an independent random signal to the local subsystem, which is easy to implement, using a simple least-squares method to identify local systems can achieve convergent identification for a certain probability. Meanwhile, we give the minimal level of variance of the injected signal that can still guarantee the convergence of the identification. Next, we add the designed input as a vector of Gaussian noises with decreasing variance to a known controller, proving that it can converge to the original controller. Simulations demonstrate the effectiveness of the proposed algorithms. © 2025 IEEE.

关键词： Least squares approximations

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