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arXiv 2022年

作者： Liu, Qi Yang, Bo Wang, Zhaojian Zhu, Dafeng Wang, Xinyi Ma, Kai Guan, Xinping The Department of Automation Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240 China School of Electrical Engineering Yanshan University Qinhuangdao066004 China

Due to the different losses caused by various photovoltaic (PV) array faults, accurate diagnosis of fault types is becoming increasingly important. Compared with a single one, multiple PV stations collect sufficient fault samples, but their data is not allowed to be shared directly due to potential conflicts of interest. Therefore, federated learning can be exploited to train a collaborative fault diagnosis model. However, the modeling efficiency is seriously affected by the model update mechanism since each PV station has a different computing capability and amount of data. Moreover, for the safe and stable operation of the PV system, the robustness of collaborative modeling must be guaranteed rather than simply being processed on a central server. To address these challenges, a novel asynchronous decentralized federated learning (ADFL) framework is proposed. Each PV station not only trains its local model but also participates in collaborative fault diagnosis by exchanging model parameters to improve the generalization without losing accuracy. The global model is aggregated distributedly to avoid central node failure. By designing the asynchronous update scheme, the communication overhead and training time are greatly reduced. Both the experiments and numerical simulations are carried out to verify the effectiveness of the proposed method. © 2022, CC BY.

关键词： Failure analysis

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High Sensitivity Submicron Scale Temperature Sensor Based on Perovskite Nanoplatelet Lasers

SSRN

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SSRN 2024年

作者： Zhao, Ruofan Tao, Jianxun Xi, Yuying Chen, Jiangzhao Ji, Ting Wang, Wenyan Wen, Rong Cui, Yanxia Chen, Junsheng Lia, Guohui College of Physics and Optoelectronics Key Laboratory of Interface Science and Engineering in Advanced Materials Key lab of Advanced Transducers and Intelligent Control System of Ministry of Education Taiyuan University of Technology Taiyuan030024 China School of Materials Science and Engineering Kunming University of Science and Technology Kunming650093 China Shanxi-Zheda institute of advanced materials and chemical engineering China Nano-Science Center Department of Chemistry University of Copenhagen Universitetsparken 5 CopenhagenDK-2100 Denmark

Submicron scale temperature sensors are crucial for a range of applications, particularly in micro and nanoscale environments. One promising solution involves the use of active whispering gallery mode (WGM) microresonators. These resonators can be remotely excited and read out using free-space structures, simplifying the process of sensing. In this study, we present a submicron-scale temperature sensor with a remarkable sensitivity up to 190 pm/℃ based on a triangular CH3NH3PbI3 nanoplatelet (NPL) laser. Notably, as temperature changes, the peak wavelength of the laser line shifts linearly. This unique characteristic allows for precise temperature sensing by tracking the peak wavelength of the NPL laser. The optical modes are confined within the perovskite NPL, which measures just 85 nanometers in height, due to total internal reflection. Our NPL laser boasts several key features, including a high Q-factor of ~ 2610 and a low laser threshold of about 19.8 µJ cm−2. The combination of exceptional sensitivity and ultra-small size makes our WGM device an ideal candidate for integration into systems that demand compact temperature sensors. This advancement paves the way for significant progress in the development of ultrasmall temperature sensors, opening new possibilities across various fields. © 2024, The Authors. All rights reserved.

关键词： Perovskite

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Event-triggered Consensus control of Heterogeneous Multi-agent systems: Model- and Data-based Analysis

arXiv

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arXiv 2022年

作者： Wang, Xin Sun, Jian Wang, Gang Chen, Jie The School of Automation The Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology Beijing10081 China The Beijing Institute of Technology Chongqing Innovation Center Chongqing401120 China The Department of Control Science and Engineering Tongji University Shanghai201804 China The State Key Lab of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing100081 China

This article deals with model- and data-based consensus control of heterogenous leader-following multi-agent systems (MASs) under an event-triggering transmission scheme. A dynamic periodic transmission protocol is developed to significantly alleviate the transmission frequency and computational burden, where the followers can interact locally with each other approaching the dynamics of the leader. Capitalizing on a discrete-time looped-functional, a model-based consensus condition for the closed-loop MASs is derived in form of linear matrix inequalities (LMIs), as well as a design method for obtaining the distributed controllers and event-triggering parameters. Upon collecting noise-corrupted state-input measurements during open-loop operation, a data-driven leader-following MAS representation is presented, and employed to solve the data-driven consensus control problem without requiring any knowledge of the agents' models. This result is then extended to the case of guaranteeing an H∞ performance. A simulation example is finally given to corroborate the efficacy of the proposed distributed event-triggering scheme in cutting off data transmissions and the data-driven design method. Copyright © 2022, The Authors. All rights reserved.

关键词： Linear matrix inequalities

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Point Cloud based Motion State Estimation Method for Autonomous Driving

Point Cloud based Motion State Estimation Method for Autonom...

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2023 International Conference on Advanced Mechatronic systems, ICAMechS 2023

作者： Jiang, Tao Zhu, Enzhi Wu, Sidong Zhang, Linshuai Gu, Shuoxin Xu, Lin Wang, Qian Tang, Xianggui Chengdu Univ. of Traditional Chinese Med. Unmanned Syst. Intelligent Percept. Contr. Technol. Eng. Laboratory of Sichuan Province Chengdu University of Information Technology School of Intelligent Medicine Chengdu China Chengdu University of Information Technology School of Automation Chengdu China Chengdu Univ. of Info. Technol. Unmanned Syst. Intelligent Perception Control Technology Engineering Laboratory of Sichuan Province Chengdu University of Information Technology School of Automation Chengdu China Chengdu University of Traditional Chinese Medicine School of Automation Chengdu Univ. of Info. Technol. Intl. Jt. Res. Ctr. of Robotics and Intell. Syst. of Sichuan Prov. School of Intelligent Medicine Chengdu China Chengdu University of Information Technology International Joint Research Center of Robotics and Intelligence System of Sichuan Province School of Automation Chengdu China

ISBN: (纸本)9798350307474

Generally, motion vector information primarily stems from moving objects, while static objects contribute minimally to the estimation task. Traditional approaches for motion vector estimation typically rely on scene flow methods that depend on deep models to extract features from individual points at a high cost. These methods then acquire flow information through complex matching mechanisms or feature decoding. Such approaches are computationally expensive and exhibit substantial latency. Moreover, they neglect the importance of motion objects in motion vector estimation and the interference from static objects. Therefore, this paper introduces a novel method that first performs point cloud motion segmentation and subsequently estimates motion vectors. This approach focuses on leveraging point cloud information annotated with motion objects to estimate three-dimensional scene flow more effectively. By employing motion segmentation, we can obtain annotations for moving objects, enabling greater emphasis on the estimation of motion vectors for more challenging cases. In our experiments conducted on the KITTI dataset, the proposed method demonstrates superior performance compared to existing scene flow estimation methods. Specifically, without considering motion segmentation errors, the error in the motion direction is only 0.0363 m/s, showcasing better performance. Additionally, our method achieves an error of 0.076 m for three-dimensional endpoint error (EPE3D), showcasing distinct advantages over current scene flow networks. © 2023 IEEE.

关键词： Errors

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intelligent intersection scheduling based on vehicle traffic priority

Intelligent intersection scheduling based on vehicle traffic...

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第40届中国控制会议

作者： Zhengxin Ruan Sicong Chen Yuanlong Li Liangren Shi Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Engineering Research Center of Intelligent Control and Management

This paper proposes an intelligent intersection management method based on the vehicle dynamic priority. By the information interaction between the autonomous vehicles（AVs） and the infrastructure equipment, the vehicle position and posture information is obtained in real time, and the priority of the vehicles passing through the conflict points in the scene is determined according to the order of the vehicles driving through the crossroads. Subsequently, to track the planned trajectory, we use the model predictive control（MPC） algorithm minimize the intersection delay with collision-free constraints. This guarantees the vehicles to drive through the intersection safely in the scene. Simulation experiments demonstrate the reliability and efficiency of the proposed algorithm.

关键词： Autonomous vehicle Intersection management system Vehicle-to-infrastructure communication Dynamic priority Model predictive control

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An Accelerated Gossip-Based Distributed Gradient Method

An Accelerated Gossip-Based Distributed Gradient Method

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第40届中国控制会议

作者： Xiaoxing Ren Dewei Li Yugeng Xi Haibin Shao Department of Automation Shanghai Jiao Tong UniversityKey Laboratory of System Control and Information ProcessingMinistry of Education of ChinaShanghai Engineering Research Center of Intelligent Control and Management

This paper studies distributed optimization over the multi-agent network. We develop and analyze a novel accelerated distributed gradient descent method, termed as G-DGDlm, for gossip communication protocol. G-DGDlm uses gradient tracking technique and local memory. Specifically, each agent stores two past variables, namely, an estimate of the average gradient and an estimate of the optimal solution. G-DGDlm achieves linear convergence for strongly convex and smoot√h functions when the related works, we remove the dependence of θ on global parameters and G-DGDlm is applicable to gossip communication protocol. Numerical experiments of distributed estimation in sensor networks show the faster convergence speed of G-DGDlm in comparison with the state-of-the-art methods.

关键词： Distributed convex optimization gossip communication first-order methods

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Event-Triggered Consensus on Matrix-weighted Networks

Event-Triggered Consensus on Matrix-weighted Networks

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Chinese Automation Congress (CAC)

作者： Lulu Pan Chongzhi Wang Haibin Shao Dewei Li Yugeng Xi Key Laboratory of System Control and Information Processing Ministry of Education of China and Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai China

ISBN: (纸本)9781665426480

In this work, we consider the consensus problem of the multi-agent system over matrix-weighted networks using an event-triggered mechanism. An event-triggered coordination strategy is proposed to steer this generalized category of multi-agent systems towards the bipartite consensus state. The triggering condition is periodically checked and distributed in the sense that the event detector only uses neighbors’ information and local computation at discrete sampling instants. Moreover, it is shown that the triggering condition is closely related to the spectrum of matrix-valued weights corresponding to the edges in the matrix-weighted network. In the meantime, the Zeno phenomenon can be avoided automatically under the proposed event trigger approach.

关键词： Automation Image edge detection Detectors Eigenvalues and eigenfunctions Multi-agent systems

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Topology Inference for Networked Dynamical systems: A Causality and Correlation Perspective

Topology Inference for Networked Dynamical Systems: A Causal...

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IEEE Conference on Decision and control

作者： Yushan Li Jianping He Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University the Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China

ISBN: (纸本)9781665436601

Networked dynamical systems (NDSs) have gained considerable attention in recent years, where the networked agents cooperate to accomplish the common task through the interaction topology. In this paper, we focus on the topology inference problem of NDSs. Different from traditional methods, we aim to infer the internal interaction topology from the perspective of node causality and correlation, covering both directed/undirected topology structures and the asymptotic/marginal stabilities of NDSs. Specifically, we propose a causality-based method that takes the noise characteristic into account and asymptotically approaches the real interaction topology structure, with only single round observations over the dynamical process. When the observation number is small, we further design a correlation-based modification to effectively alleviate the influence of noises. We demonstrate the close relation between the proposed method and the traditional Granger estimator and ordinary least square (OLS) estimator in terms of observation rounds and horizon. We further prove the equivalence conditions of the proposed method with the two estimators from the system stability and noise characteristic. The proposed causality-correlation combined method enjoys analogous asymptotic inference performance with Granger estimator of multiple observation rounds, and outperforms OLS estimator in single observation round, verified by extensive simulations.

关键词： Degradation Asymptotic stability Correlation Network topology Conferences Stability analysis Topology

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Analysis of Fault Characteristics and Distance Protection Adaptability for VSC-HVDC-Connected Offshore Wind Farms

Analysis of Fault Characteristics and Distance Protection Ad...

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IEEE Asia Power and Energy engineering Conference (APEEC)

作者： Fang Peng Houlei Gao Weiying Miao Xinchi Feng Bin Xu Yitong Wu Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Shandong University Jinan China Substation Maintenance Center State Grid Hangzhou Power Supply Company Hangzhou China State Grid Nanjing Power Supply Company Nanjing China School of Electrical Engineering Shandong University Jinan China

With the characteristics of low loss, low harmonic content and large transmission capacity, voltage source converter based high voltage direct current transmission (VSC-HVDC) has become the focus of the development for large-capacity and long-distance power transmission system connected with offshore wind farms. However, since the power supplies on both sides are controlled, the fault characteristics are changed, and the performance of the traditional distance protection is influenced. Based on the control strategy, the amplitude and phase angle of the equivalent positive and negative sequence impedances at the two sides of the transmission line are analyzed, and the current phasor expressions of the wind farm side and the VSC-HVDC side of the faulted line are derived. Then the adaptability of distance protection using power frequency component (DPPFC) of transmission line for VSC-HVDC-connected offshore wind farm is analyzed under different fault conditions. The results show that the amplitude and phase angle of the equivalent positive and negative sequence impedances of the wind farm and the VSC-HVDC system are affected by the control strategy of the converter and the fault conditions. The DPPFC is not suitable for VSC-HVDC-connected offshore wind farm system. The ability to avoid the effect of fault resistance of the DPPFC at the wind farm side gets worse. The simulation conducted by EMTP-RV verifies the effectiveness of the analysis.

关键词： Resistance Analytical models Power transmission lines Power transmission Wind farms Propagation losses Power conversion

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Bearing-only Formation control of Nonholonomic Agents with Unknown Dynamic Leaders

Bearing-only Formation Control of Nonholonomic Agents with U...

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Chinese Automation Congress (CAC)

作者： Haifan Su Ziwen Yang Shanying Zhu Cailian Chen Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai China

ISBN: (纸本)9781665426480

In this paper, the problem of bearing-only formation tracking control of multiple nonholonomic agents is studied. A leader-follower structure is adopted, where the leaders are moving at an unknown constant linear velocity and time-varying orientation. To solve the problem using bearing-only measurements, a finite-time estimator is firstly proposed to estimate the leaders’ orientation information. Then, an adaptation law for estimating the leaders’ linear velocity is proposed, based on which control inputs for tracking the leaders in a predefined bearing-based formation are designed, so that formation tracking can be achieved asymptotically. Rigorous theoretical analysis of the closed-loop system is given. It is proved that both the estimation errors and formation errors converge to zero under the connectivity of the communication graph and conditions for bearing rigidity. Numerical simulations are presented to testify the effectiveness of the proposed method.

关键词： Estimation error Automation Simulation Numerical simulation Rigidity Velocity measurement Closed loop systems

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