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IEEE Conference on Decision and control

作者： Jia Qi Chongrong Fang Jianping He Dept. of Automation Key Laboratory of System Control and Information Processing Shanghai Jiao Tong University Ministry of Education of China and Shanghai Engineering Research Center of Intelligent Control and Management Shanghai China

Security issues are of significant importance for cyber-physical systems (CPS), where the attack design is a major concern. Most related studies on attack design implicitly consider that the control period and detection period are the same. However, the two periods could be different in practical systems with remote detection such as supervisory control and data acquisition (SCADA) systems, which could lead to new vulnerabilities for attackers. In this paper, we consider the design of innovation-based linear attack strategies for CPS when the control period and detection period are inconsistent. Specifically, we propose an attack framework that consists of attack strategies for detection and non-detection instants under the period discrepancy. On this basis, we design the optimal stealthy innovation-based linear attack strategies for state estimation and LQG control to maximize the estimation error or control cost, respectively. Simulations are given to demonstrate the effectiveness of the proposed attack strategies.

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Transient Stability Evaluation of Independent Microgrid based on Message Passing Graph Neural Network

Transient Stability Evaluation of Independent Microgrid base...

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International Conference on Electronics Technology (ICET)

作者： Jiubao Zhen Shufan Huang Xuwen Jia Haocheng Du College of Information and Electrical Engineering China Agricultural University Beijing China Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Shandong University Jinan China

Virtual synchronous generator is used to control independent microgrid to provide inertia and damping support, but it often brings transient stability problems. Due to the large number of nonlinear and non-smooth characteristics of highly electronic independent microgrid, it is difficult to analyze it by the traditional transient stability analysis method. In this paper, the independent microgrid controlled by virtual synchronization is taken as the object. Firstly, we compare the impact of detailed modeling of energy storage and simplified modeling on the transient stability, and then discuss the impact of current limiting link of virtual synchronous machine on the transient stability. Secondary, combined with the idea of graph neural network, we propose an independent microgrid transient stability evaluation model based on message passing graph neural network. The information corresponding to bus and transmission lines in microgrid is aggregated and updated by message passing mechanism, so as to depict the topological connection relationship of microgrid, and then consider the influence of topology structure on transient stability evaluation. Last, a WSCC-9 system with virtual synchronous machine is taken as an example. The results show that considering the energy storage detailed model and current limiting link can effectively improve the accuracy of stability analysis. The proposed method has stronger generalization ability and is more applicable to the microgrid system with variable topological structure.

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Preserving Topology of Network systems: Metric, Analysis, and Optimal Design

arXiv

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arXiv 2023年

作者： Li, Yushan Wang, Zitong He, Jianping Chen, Cailian Guan, Xinping Dept. 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 Shanghai China

Preserving the topology from being inferred by external adversaries has become a paramount security issue for network systems (NSs), and adding random noises to the nodal states provides a promising way. Nevertheless, recent works have revealed that the topology cannot be preserved under i.i.d. noises in the asymptotic sense. How to effectively characterize the non-asymptotic preservation performance still remains an open issue. Inspired by the deviation quantification of concentration inequalities, this paper proposes a novel metric named trace-based variance-expectation ratio. This metric effectively captures the decaying rate of the topology inference error, where a slower rate indicates better non-asymptotic preservation performance. We prove that the inference error will always decay to zero asymptotically, as long as the added noises are non-increasing and independent (milder than the i.i.d. condition). Then, the optimal noise design that produces the slowest decaying rate for the error is obtained. More importantly, we amend the noise design by introducing one-lag time dependence, achieving the zero state deviation and the non-zero topology inference error in the asymptotic sense simultaneously. Extensions to a general class of noises with multi-lag time dependence are provided. Comprehensive simulations verify the theoretical findings. Copyright © 2023, The Authors. All rights reserved.

关键词： Topology

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Optimal Parameters Setting of Wind Power for Frequency Regulation Based on Evaluation of Available Kinetic Energy

SSRN

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SSRN 2024年

作者： Zhang, Han Zhang, Feng Ding, Lei Salimu, Athuman Zhang, Gang State Key Laboratory Power System Intelligent Dispatch and Control of Ministry of Education School of Electrical Engineering Shandong University Jinan250061 China Yantai Research Institute of Harbin Engineering University Yantai264006 China

When a wind farm (WF) provides frequency support for the power grid, the frequency regulation parameters of wind turbine generators (WTGs) are normally set by the control of the rotor-side converter and generally decoupled from the time-varying available rotational kinetic energy (KE) in WTGs. Therefore, it may lead to a mismatch between the frequency regulation parameters and the frequency regulation ability of a WTG. In this paper, an optimal frequency regulation parameter setting method of wind power is proposed considering available KE evaluation of wind power, establishing the coupling relationship between frequency regulation parameters with available KE. Firstly, considering the spatiotemporal differences in wind speed within a WF, forecasting scenario-based evaluation method of the available KE for a WF is proposed. Secondly, a functional optimization model for equivalent wind power frequency regulation parameters is constructed and solved with numerical method to adapt to the time-varying available KE of wind power in the power grid. Then the frequency regulation parameters of the WF and WTG layers are set according to the energy-weight ratio. Finally, a case study is conducted to verify the proposed available KE evaluation method using forecasted wind speed scenarios and the effectiveness of the optimal frequency regulation parameter setting method using a two-area power system model. The results show that the energy evaluation method can effectively reduce evaluation error and the optimal frequency regulation parameter can improve the system frequency dynamic response, and prevent over-deceleration of WTG. © 2024, The Authors. All rights reserved.

关键词： Kinetic energy

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Differential Private Discrete Noise-Adding Mechanism: Conditions, Properties, and Optimization

Differential Private Discrete Noise-Adding Mechanism: Condit...

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作者： Qin, Shuying He, Jianping Fang, Chongrong Lam, James Shanghai Jiao Tong University Department of Automation Shanghai200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Beijing100816 China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240 China Shenzhen Institute of Research and Innovation Shenzhen518055 China The University of Hong Kong Department of Mechanical Engineering Hong Kong999077 Hong Kong

Differential privacy is a widely used framework for evaluating privacy loss in data anonymization. While the continuous noise-adding mechanism has been extensively studied, there is a dearth of research on discrete random mechanisms for discretely distributed data. This study addresses this gap by examining the primary differential privacy conditions and properties for general discrete random mechanisms, and investigating the trade-off between data privacy and data utility. We establish sufficient and necessary conditions for discrete ϵ-differential privacy and sufficient conditions for discrete (ϵδ)-differential privacy, with closed-form expressions for differential privacy parameters. These conditions can be applied to evaluate the differential privacy properties of discrete noise-adding mechanisms with various types of noise. Moreover, we propose an optimal discrete ϵ-differential private noise-adding mechanism under the utility-maximization framework. Here, the utility is characterized by the similarity of the statistical properties between the mechanism's input and output. Our findings suggest that the optimal class of discrete noise probability distributions in the mechanism is staircase-shaped. © 1991-2012 IEEE.

关键词： Probability distributions

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A Review of Machine Tool Motorized Spindle Variable Pressure Preload Technology Research

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Recent Patents on Engineering 2025年第5期19卷

作者： Dai, Ye Deng, Hao Pan, Gaofeng Chen, Xinda Key Laboratory of Advanced Manufacturing and Intelligent Technology Ministry of Education School of Mechanical and Power Engineering Harbin University of Science and Technology Harbin150080 China School of College of Measurement and Control Technology and Communication Engineering Harbin University of Science and Technology Harbin150080 China

High-precision spindles are a vital study topic because of the growing demand for high-speed, high-precision, reliable, and long-lasting machine tools. Bearing preload is the primary means of improving the accuracy of the spindle rotor system. This patent study aims to summarize the research results, systematically analyze and evaluate the machine tool motorized spindle variable pressure preload technology, and provide a scientific basis for the practical application of the motor spindle variable pressure preload technology. This study is an in-depth analysis of the basic principles of the electric spindle preloading technology, the study of its influence mechanism on the thermal deformation, stiffness, slewing error, and life of the spindle system, and a discussion of the current shortcomings in the field of spindle preloading to provide a reference for the subsequent optimization. In the spindle system, the performance of rolling bearings and the design of bearing preload have an important impact on the spindle's accuracy and stability. The traditional preload method has yet to meet the requirements of modern high-speed machine tools. Real-time controllable preload has become the new direction of development, but the current preload technology still has certain limitations and needs to be further improved. In the future, the spindle bearing variable pressure preload technology will be more efficient and intelligent. © 2025 Bentham Science Publishers.

关键词： Machine tools

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Dynamic Event-Triggered Consensus on Matrix-weighted Networks:Leadless Case

Dynamic Event-Triggered Consensus on Matrix-weighted Network...

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第42届中国控制会议

作者： Lintao Dou Haoyu Wei Jian Huang Lulu Pan Haibin Shao Dewei Li the College of Intelligent Science National University of Defense Technology the Department of Automation Shanghai Jiao Tong Universityand Key Laboratory of System Control and Information ProcessingMinistry of Education of Chinaand Shanghai Engineering Research Center of Intelligent Control and Management

This paper examines the event-triggered consensus of the multi-agent system on matrix-weighted networks,where the interdependencies among higher-dimensional states of neighboring agents are characterized by matrix-weighted edges in the ***,a novel distributed dynamic event-triggered coordination strategy is proposed for this category of generalized networks,in which an auxiliary system is employed for each agent to dynamically adjust the triggering threshold,which plays an essential role in guaranteeing that the triggering time sequence does not exhibit Zeno *** event-triggered control protocols are proposed to guarantee leaderless consensus for multi-agent systems on matrix-weighted networks,***,the spectrum of matrix-valued weights is crucial in event-triggered mechanism design for matrix-weighted networks,generalizing those results only applicable for scalar-weighted *** proposed approach allows each agent to broadcast and receive information only at its triggering ***,simulation examples are provided to demonstrate the theoretical results.

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Iterative-Reweighting-Based Robust Iterative-Closest-Point Method

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Journal of Shanghai Jiaotong university(Science) 2021年第5期26卷 739-746页

作者： ZHANG Jianlin ZHOU Xuejun YANG Ming Department of Automation Shanghai Jiao Tong UniversityShanghai 200240China Key Laboratory of System Control and Information Processing of Ministry of Education Shanghai 200240China Noblelift Intelligent Equipment Co. Ltd.Huzhou 313100ZhejiangChina

In point cloud registration applications,noise and poor initial conditions lead to many false *** matches significantly degrade registration accuracy and speed.A penalty function is adopted in many robust point-to-point registration methods to suppress the influence of false ***,after applying a penalty function,problems cannot be solved in their analytical forms based on the introduction of ***,most existing methods adopt the descending *** this paper,a novel iterative-reweighting-based method is proposed to overcome the limitations of existing *** proposed method iteratively solves the eigenvectors of a four-dimensional matrix,whereas the calculation of the descending method relies on solving an eight-dimensional ***,the proposed method can achieve increased computational *** proposed method was validated on simulated noise corruption data,and the results reveal that it obtains higher efficiency and precision than existing methods,particularly under very noisy *** results for the KITTI dataset demonstrate that the proposed method can be used in real-time localization processes with high accuracy and good efficiency.

关键词： point cloud registration iterative reweighting iterative closest-point(ICP) robust localization

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Brillouin Frequency Shift Extraction by Bidirectional Integration of Brillouin Gain Spectrum

SSRN

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SSRN 2023年

作者： Liu, Shuangshuang Zhang, Jianzhong Ma, Zhe Liang, Zefeng Han, Jinfeng Xu, Jinglang Zhang, Mingjiang Key Laboratory of Advanced Transducers and Intelligent Control System Ministry of Education and Shanxi Province Taiyuan University of Technology Taiyuan030024 China College of Electronic Information and Optical Engineering Taiyuan University ofTechnology Taiyuan030024 China College of Physics Taiyuan University of Technology Taiyuan030024 China Shanxi-Zheda Institute of Advanced Materials and ChemicalEngineering Taiyuan030024 China

A novel Brillouin frequency shift (BFS) extraction approach based on bidirectional integration is proposed and investigated for mitigating the fluctuations in Brillouin optical time domain reflectometer (BOTDR) system. The proposed method involves calculating the BFS through the forward and backward integrations of the original Brillouin gain spectrum (BGS) data. The findings from both simulations and experiments demonstrate that bidirectional integration achieves superior BFS accuracy compared to Lorentzian curve fitting. To further evaluate its performance, the root mean square error of BFS is measured under the different signal-to-noise ratios (SNRs) and frequency steps and the results show that bidirectional integration has higher tolerance for low SNR. Specifically, bidirectional integration achieves a BFS accuracy of 0.853 MHz under SNR of 5.22 dB and significantly reduces the measurement time by 85.86%. Additionally, the introduced coefficient k characterizes the influence on the BGS compression, with bidirectional integration exhibiting a narrower full width at half maximum of BGS (52.74 MHz) compared to Lorentzian curve fitting (67.45 MHz). © 2023, The Authors. All rights reserved.

关键词： Extraction

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Unsupervised Learning of 3D Scene Flow from Monocular Camera

arXiv

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arXiv 2022年

作者： Wang, Guangming Tian, Xiaoyu Ding, Ruiqi Wang, Hesheng Department of Automation Institute of Medical Robotics 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 Shanghai Jiao Tong University Shanghai 200240 China

Scene flow represents the motion of points in the 3D space, which is the counterpart of the optical flow that represents the motion of pixels in the 2D image. However, it is difficult to obtain the ground truth of scene flow in the real scenes, and recent studies are based on synthetic data for training. Therefore, how to train a scene flow network with unsupervised methods based on real-world data shows crucial significance. A novel unsupervised learning method for scene flow is proposed in this paper, which utilizes the images of two consecutive frames taken by monocular camera without the ground truth of scene flow for training. Our method realizes the goal that training scene flow network with real-world data, which bridges the gap between training data and test data and broadens the scope of available data for training. Unsupervised learning of scene flow in this paper mainly consists of two parts: (i) depth estimation and camera pose estimation, and (ii) scene flow estimation based on four different loss functions. Depth estimation and camera pose estimation obtain the depth maps and camera pose between two consecutive frames, which provide further information for the next scene flow estimation. After that, we used depth consistency loss, dynamic-static consistency loss, Chamfer loss, and Laplacian regularization loss to carry out unsupervised training of the scene flow network. To our knowledge, this is the first paper that realizes the unsupervised learning of 3D scene flow from monocular camera. The experiment results on KITTI show that our method for unsupervised learning of scene flow meets great performance compared to traditional methods Iterative Closest Point (ICP) and Fast Global Registration (FGR). The source code is available at: https://***/IRMVLab/3DUnMonoFlow. Copyright © 2022, The Authors. All rights reserved.

关键词： Unsupervised learning

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