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IEEE International Conference on Robotics and automation (ICRA)

作者： Wenhua Wu Guangming Wang Jiquan Zhong Hesheng Wang Zhe Liu MoE Key Lab of Artificial Intelligence AI Institute Shanghai Jiao Tong University Shanghai China Department of Automation Key Laboratory of System Control and Information Processing of Ministry of Education Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Engineering Research Center of Intelligent Control and Management Insititute of Medical Robotics Shanghai Jiao Tong University Shanghai China

Depth estimation is one of the most important tasks in scene understanding. In the existing joint self-supervised learning approaches of depth-pose estimation, depth estimation and pose estimation networks are independent of each other. They only use the adjacent image frames for pose estimation and lack the use of the estimated geometric information. To enhance the depth-pose association, we propose a monocular multi-frame unsupervised depth estimation framework, named PLPE-Depth. There are a depth estimation network and two pose estimation networks with image input and pseudo-LiDAR input. The main idea of our approach is to use the pseudo-LiDAR reconstructed from the depth map to estimate the pose of adjacent frames. We propose depth re-estimation with a better pose between the image pose and the pseudo-LiDAR pose to improve the accuracy of estimation. Besides, we improve the reconstruction loss and design a pseudo-LiDAR pose enhancement loss to facilitate the joint learning. Our approach enhances the use of the estimated depth information and strengthens the coupling between depth estimation and pose estimation. Experiments on the KITTI dataset show that our depth estimation achieves state-of-the-art performance at low resolution. Our source codes will be released on https://***/IRMVLabIPLPE-Depth.

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Practical Applicability of PLA for Industrial Wireless Networks: Gaps and Directions

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IEEE Network 2025年

作者： Liang, Wei Wei, Fuyou Wang, Qi Zhan, Ming Wang, Ke Chinese Academy of Sciences State Key Laboratory of Robotics Shenyang Institute of Automation Shenyang110016 China Chinese Academy of Sciences Key Laboratory of Networked Control System Shenyang Institute of Automation Shenyang110016 China Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Shenyang110169 China University of Chinese Academy of Sciences Beijing100049 China Shandong Normal University Jinan250014 China Taizhou University School of Electronics and Information Engineering Zhejiang Taizhou China

The rapid transformation of Industrial Cyber-Physical system (ICPS) has introduced significant cyber security challenges, particularly in the context of ICPS. Wireless networks are a critical component of these systems, but their open nature makes them vulnerable to security threats. Physical Layer Authentication (PLA) algorithms based on Channel State Information (CSI) are essential complements to existing security technologies in wireless networks. However, their practical application faces challenges such as restricted sampling rates and uneven sampling interval, which result in low-precision CSI, significant random phase offsets, and signal distortion. This study aims to explore the feasibility of deploying and applying existing representative algorithms on industrial wireless commercial devices. According to characteristics of authentication algorithms and the adopted authentication features, we selected five of the latest physical layer authentication algorithms including supervised, semi-supervised, and unsupervised algorithms and deployed them on commercial devices that comply with the WIA-FA standard. We conducted systematic experiments focusing on the motion parameters of devices, the CSI data sampling frequency, the interference caused by worker movement, the surface materials of the devices, and the types of attacks. This study explores the ability of these algorithms to resist attacks and environmental interference in commercial devices and industrial scenarios. Extensive experimental data were collected, and the results indicate that existing authentication algorithms still need improvement to meet the requirements of industrial applications. The experiment findings and the summarized application challenges of these algorithms provide significant guidance for future research and practical industrial implementations. © 1986-2012 IEEE.

关键词： Authentication

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An ${H_\infty }$ Load Frequency control Scheme for Multi-Area Power system Under Cyber-Attacks and Time-Varying Delays

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IEEE Transactions on Power systems 2022年第2期38卷 1336-1349页

作者： Guangdou Zhang Jian Li Olusola Bamisile Yankai Xing Dongsheng Cai Qi Huang Power System Wide-Area Measurement and Control Sichuan Province Key Laboratory School of Mechanical and Electrical Engineering University of Electronic Science and Technology of China Chengdu Sichuan China College of Nuclear Technology and Automation Engineering Chengdu University of Technology Sichuan China

In the power system, the application of the signals transmitted from the sensors to the controller can significantly improve the dynamic performance. However, cyber-attacks and time delays exist widely in the communication network, which has a considerable effect on stability, operation, and control. In this paper, an ${{\boldsymbol{H}}_\infty }$ load frequency control (LFC) scheme for multi-area power systems under cyber-attacks and time-varying delays is investigated. First, false data injection attacks (FDIA), as well as denial of service (DoS) attacks, are viewed as two typical cyber-attacks and introduced into the multi-area power system. Then, the state-space equations of the LFC power system under these two attacks and time-varying delays are analyzed and modeled. Furthermore, by using Lyapunov stability theory and linear matrix inequality (LMI) method, an ${{\boldsymbol{H}}_\infty }$ LFC scheme for attacked and delayed power systems is developed. The purpose of the proposed controller is to guarantee the closed-loop system exponentially mean-square stable with prescribed ${{\boldsymbol{H}}_\infty }$ performance. Finally, a three-area LFC system is employed to demonstrate the effectiveness of the proposed mechanism. The simulation results verified that the control performance of an attacked and delayed system can be improved significantly via the designed controller.

关键词： Power system stability Delays Frequency control Delay effects Stability analysis Mathematical models Time-varying systems

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An Integration Evaluation Method for Substation Protection and Monitoring system Based on G1 Method and Expert Investigation 3

An Integration Evaluation Method for Substation Protection a...

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3rd International Conference on New Energy and Power engineering, ICNEPE 2023

作者： Deng, Xiongyao Yan, Yuxiang Lin, Chang Xia, Hao Xue, Ancheng Shu, Zhihuai Liu, Yu Chang, Naichao Fan, Chen Li, Zhongqing Meng, Jiangwen Dou, Xuewei Wang, Shenqiang Zhang, Long Wu, Fangying State Key Laboratory of Alternate Electric Power System with Renewable Energy Source North China Electric Power University Beijing China National Electric Power Dispatching and Control Center of State Grid Corporation of China Beijing China China Electric Power Research Institute Power Automation Department Nanjing China China Electric Power Research Institute Beijing China Beijing Sifang Engineering Co. Ltd Beijing China

ISBN: (纸本)9798350393224

Substation is the core hub of power system. With the expansion of the scale of the power system and the improvement of its intelligence, the problems of the redundancy of architecture and equipment in the protection and monitoring system of substation can no longer be ignored. This paper proposes an evaluation method for integration in the protection and monitoring system based on G1 method. Firstly, according to the requirements of integration in the protection and monitoring system, the corresponding indicators are proposed to form an index system for evaluating integration. And then, an evaluation method is proposed for integration of the protection and monitoring system, based on G1 method and expert investigation. Finally, the feasibility of the evaluation method is verified by comparing and analyzing the evaluation results of a typical substation and its structural optimization substation. © 2023 IEEE.

关键词： G1 method Integration evaluation Protection and monitoring system Substation

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Generalized Multi-kernel Maximum Correntropy Kalman Filter for Disturbance Estimation

arXiv

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arXiv 2023年

作者： Li, Shilei Shi, Dawei Lou, Yunjiang Zou, Wulin Shi, Ling The Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology Hong Kong The School of Automation Beijing Institute of Technology China The State Key Laboratory of Robotics and System School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen Shenzhen518055 China Xeno Dynamics Control Department Xeno Dynamics Co. Ltd Shenzhen518055 China

Disturbance observers have been attracting continuing research efforts and are widely used in many applications. Among them, the Kalman filter-based disturbance observer is an attractive one since it estimates both the state and the disturbance simultaneously, and is optimal for a linear system with Gaussian noises. Unfortunately, The noise in the disturbance channel typically exhibits a heavy-tailed distribution because the nominal disturbance dynamics usually do not align with the practical ones. To handle this issue, we propose a generalized multi-kernel maximum correntropy Kalman filter for disturbance estimation, which is less conservative by adopting different kernel bandwidths for different channels and exhibits excellent performance both with and without external disturbance. The convergence of the fixed point iteration and the complexity of the proposed algorithm are given. Simulations on a robotic manipulator reveal that the proposed algorithm is very efficient in disturbance estimation with moderate algorithm complexity. Copyright © 2023, The Authors. All rights reserved.

关键词： Kalman filters

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Pathological axonal enlargement in connection with amyloidosis,lysosome destabilization,and bleeding is a major defect in Alzheimer’s disease

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Neural Regeneration Research 2026年第2期21卷 790-799页

作者： Hualin Fu Jilong Li Chunlei Zhang Guo Gao Qiqi Ge Xinping Guan Daxiang Cui Institute of Nano Biomedicine and Engineering School of Sensing Science and EngineeringSchool of Electronic Information and Electrical EngineeringShanghai Jiao Tong UniversityShanghaiChina Institute of Marine Equipment Shanghai Jiao Tong UniversityShanghaiChina National Center for Translational Medicine Shanghai Jiao Tong UniversityShanghaiChina Department of Automation Shanghai Jiao Tong UniversityShanghaiChina The Key Laboratory of System Control and Information Processing Ministry of EducationShanghaiChina

Alzheimer’s disease is a multi-amyloidosis disease characterized by amyloid-βdeposits in brain blood vessels,microaneurysms,and senile *** amyloid-βdeposition affects axon pathology has not been examined *** used immunohistochemistry and immunofluorescence staining to analyze the forebrain tissue slices of Alzheimer’s disease *** axonal amyloidosis with distinctive axonal enlargement was observed in patients with Alzheimer’s *** average,amyloid-β-positive axon diameters in Alzheimer’s disease brains were 1.72 times those of control brain ***,axonal amyloidosis was associated with microtubule-associated protein 2 reduction,tau phosphorylation,lysosome destabilization,and several blood-related markers,such as apolipoprotein E,alpha-hemoglobin,glycosylated hemoglobin type A1C,and *** destabilization in Alzheimer’s disease was also clearly identified in the neuronal soma,where it was associated with the co-expression of amyloid-β,Cathepsin D,alpha-hemoglobin,actin alpha 2,and collagen type *** suggests that exogenous hemorrhagic protein intake influences neural lysosome ***,the data showed that amyloid-β-containing lysosomes were 2.23 times larger than control ***,under rare conditions,axonal breakages were observed,which likely resulted in Wallerian *** summary,axonal enlargement associated with amyloidosis,micro-bleeding,and lysosome destabilization is a major defect in patients with Alzheimer’s *** finding suggests that,in addition to the well-documented neural soma and synaptic damage,axonal damage is a key component of neuronal defects in Alzheimer’s disease.

关键词： Alzheimer’s disease amyloid-β amyloidosis axonal enlargement hemoglobin hemorrhage lysosome destabilization neuropil thread tau Wallerian degeneration

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Resource Allocation for Coupled Slices in Edge-Assisted Industrial IoT systems

Resource Allocation for Coupled Slices in Edge-Assisted Indu...

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IEEE International Conference on Communications in China (ICCC)

作者： Xiaojing Wen Cailian Chen Cheng Ren Ling Lyu Xinping Guan Department of Automation Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Ministry of Education of China and Shanghai Engineering Research Center of Intelligent Control and Management Shanghai P. R. China School of Information Science and Technology Dalian Maritime University Dalian China

Multiple types of sensors are utilized for remote monitoring of single industrial process to compensate for the limited accuracy of a single type of sensor. Network slicing technology is considered promising for collecting data from heterogeneous sensors and meeting diverse Quality of Service (QoS) requirements. However, existing research on network slicing optimization mainly focuses on inter-slice resource constraints based on slice heterogeneity, neglecting slice coupling feature. In this regard, this paper proposes a novel network slicing framework for edge-assisted industrial IoT systems. The framework includes a slice coupling model and network resource allocation (transmission and computing) to address the problem of improving estimation performance while ensuring system convergence. The slice coupling model is primarily composed of the estimation error covariance of two slices, calculated using the Age of Task (AoT) as a bridge, which reflects the accuracy and freshness of the estimation. To reduce the complexity of the direct solution, the optimization problem is scaled down and decoupled. The iterative Particle Swarm Optimization (PSO) algorithm is proposed to determine the allocation rates of inter-slice transmission and computing resources. Simulation results demonstrate that the proposed algorithm achieves a flexible balance under heterogeneous estimation weights and exhibits near-optimal performance.

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Autoregressive GNN-ODE GRU Model for Network Dynamics

arXiv

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arXiv 2022年

作者： Liang, Bo Wang, Lin Wang, Xiaofan Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China Shanghai Key Laboratory of Power Station Automation Technology School of Mechatronic Engineering and Automation Shanghai University Shanghai China

Revealing the continuous dynamics on the networks is essential for understanding, predicting, and even controlling complex systems, but it is hard to learn and model the continuous network dynamics because of complex and unknown governing equations, high dimensions of complex systems, and unsatisfactory observations. Moreover, in real cases, observed time-series data are usually non-uniform and sparse, which also causes serious challenges. In this paper, we propose an Autoregressive GNN-ODE GRU Model (AGOG) to learn and capture the continuous network dynamics and realize predictions of node states at an arbitrary time in a data-driven manner. The GNN module is used to model complicated and nonlinear network dynamics. The hidden state of node states is specified by the ODE system, and the augmented ODE system is utilized to map the GNN into the continuous time domain. The hidden state is updated through GRUCell by observations. As prior knowledge, the true observations at the same timestamp are combined with the hidden states for the next prediction. We use the autoregressive model to make a one-step ahead prediction based on observation history. The prediction is achieved by solving an initial-value problem for ODE. To verify the performance of our model, we visualize the learned dynamics and test them in three tasks: interpolation reconstruction, extrapolation prediction, and regular sequences prediction. The results demonstrate that our model can capture the continuous dynamic process of complex systems accurately and make precise predictions of node states with minimal error. Our model can consistently outperform other baselines or achieve comparable performance. Copyright © 2022, The Authors. All rights reserved.

关键词： Forecasting

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Pinr: A Physics-Integrated Neural Representation for Dynamic Fluid Scenes

SSRN

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SSRN 2024年

作者： Zhao, Ziyu Zhou, Sifan Lu, Xiaobo Zeng, Weili Qian, Jian School of Automation Southeast University Nanjing China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing China College of Civil Aviation Nanjing University of Aeronautics and Astronautics Nanjing China Key Laboratory of ASIC and System Fudan University Shanghai China

Recent research based on neural representation has achieved impressive results in dynamic reconstruction. However, reconstructing high-fidelity dynamic fluid scenes from multi-view videos remains challenging due to the complex fluid phenomena such as translucency, scattering, occlusion, and visual ambiguity. In this paper, we present a novel neural representation that simultaneously exploits physics knowledge and differentiable volume rendering techniques to construct a physically plausible neural field. We first propose a simple yet effective state field to separate fluid and non-fluid contents apart, which essentially reduces the amount of computation and appearance ambiguity. To achieve robust optimization and fast convergence, we introduce intermediate velocity in neural representation based on Helmholtz Decomposition to decouple physical quantities (velocity, pressure and density) that are tightly coupled in physical equations. In contrast to previous physics-informed reconstruction methods, we explore a novel solution by introducing a fast and stable fluid solver to update the intermediate velocity to a physically conserved incompressible velocity. This solver is based on a parallelizable multi-scale architecture, which can effectively avoid degenerate solutions. By adopting the proposed physics-aware loss, we achieved better convergence and superior performance in dynamic fluid scenes. Extensive experiments show that the proposed method can achieve state-of-the-art results for reconstructing dynamic fluid scenes, and the performance and efficiency have been significantly improved in different scenarios. © 2024, The Authors. All rights reserved.

关键词： Computer vision

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Blockchain-based peer to peer energy trading using distributed model predictive control

Blockchain-based peer to peer energy trading using distribut...

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European control Conference (ECC)

作者： Manuel Sivianes Ascensió n Zafra-Cabeza Carlos Bordons Systems Engineering and Automatic Control Department School of Engineering Universidad de Sevilla Seville Spain System Engineering and Automation Department School of Engineering Universidad de Sevilla Seville Spain Systems Engineering and Automatic Control Department ENGREEN Laboratory of Engineering for Energy and Environmental Sustainability Universidad de Sevilla Seville Spain

ISBN: (数字)9783907144077

ISBN: (纸本)9781665497336

The energy network is experiencing a decentralizing process due to the recent inclusion of distributed energy resources (DERs), such as photovoltaics (PV), electric vehicles (EV), or batteries. This paradigmatic shift involves new challenges that require enhancing the electricity system's flexibility while preserving its integrity and stability. One way of dealing with them is by unbundling the electrical network into smaller, more manageable units, known as microgrids (MG). Nonetheless, the usage of distributed architectures leads to more exchanged data and control information between end agents, involving security or privacy issues. In this context, blockchain technology emerges as a feasible solution that promises transparent, tamper-proof, and safe systems in a decentralized ecosystem. This paper proposes a distributed energy management platform that takes full advantage of the blockchain technology to enable safe peer to peer (P2P) transactions. A Distributed model predictive control (DMPC) scheme is adopted, and its performance is compared with the centralized approach.

关键词： Photovoltaic systems Smart contracts Microgrids Prediction algorithms Stability analysis Blockchains Peer-to-peer computing

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