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IEEE International Conference on Robotics and Automation (ICRA)

作者： Xinyi Wang Jiwen Xu Chuanxiang Gao Yizhou Chen Jihan Zhang Chenggang Wang Yulong Ding Ben M. Chen Department of Mechanical and Automation Engineering The Chinese University of Hong Kong Shatin N.T. Hong Kong China Department of Automation Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Jiao Tong University Shanghai P. R. China Department of Control Science and Engineering Tongji University Shanghai China Frontiers Science Center for Intelligent Autonomous Systems Ministry of Education China

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Multi-robot systems have increasingly become instrumental in tackling coverage problems. However, the challenge of optimizing task efficiency without compromising task success still persists, particularly in expansive, unstructured scenarios with dense obstacles. This paper presents an innovative, decentralized Voronoi-based coverage control approach to reactively navigate these complexities while guaranteeing safety. This approach leverages the active sensing capabilities of multi-robot systems to supplement GIS (Geographic information system), offering a more comprehensive and real-time understanding of environments like post-disaster. Based on point cloud data, which is inherently non-convex and unstructured, this method efficiently generates collision-free Voronoi regions using only local sensing information through spatial decomposition and spherical mirroring techniques. Then, deadlock-aware guided map integrated with a gradient-optimized, centroid Voronoi-based coverage control policy, is constructed to improve efficiency by avoiding exhaustive searches and local sensing pitfalls. The effectiveness of our algorithm has been validated through extensive numerical simulations in high-fidelity environments, demonstrating significant improvements in task success rate, coverage ratio, and task execution time compared with others.

关键词： Point cloud compression system recovery Robot sensing systems Sensors Safety Multi-robot systems Task analysis

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Differentially Private Distributed Mismatch Tracking Algorithm for Constraint-Coupled Resource Allocation Problems

Differentially Private Distributed Mismatch Tracking Algorit...

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IEEE Conference on Decision and control

作者： Wenwen Wu Shanying Zhu Shuai Liu Xinping Guan Department of Automation Shanghai Jiao Tong University Shanghai China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai China School of Control Science and Engineering Shandong University Jinan China

ISBN: (数字)9781665467612

ISBN: (纸本)9781665467629

This paper considers privacy-concerned distributed constraint-coupled resource allocation problems over an undirected network, where each agent holds a private cost function and obtains the solution via only local communication. With privacy concerns, we mask the exchanged information with independent Laplace noise against attackers with potential access to all network communications. We propose a differentially private distributed mismatch tracking algorithm (diff-DMAC) to achieve cost-optimal distribution of resources while preserving privacy. Adopting constant stepsizes, the linear convergence property of diff-DMAC in mean square is established under the standard assumptions of Lipschitz smoothness and strong convexity. Moreover, it is theoretically proven that the proposed algorithm is ϵ-differentially private. And we also show the trade-off between convergence accuracy and privacy level. Finally, a numerical example is provided for verification.

关键词： Privacy Differential privacy Cost function Resource management Standards Convergence

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Research on the High-Precision Unmanned Operation control Algorithm of theVibroseis Vehicle

Research on the High-Precision Unmanned Operation Control Al...

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第40届中国控制会议

作者： LI Bin WANG Shoukun WANG Shuai WANG Junzheng LIU Shangfei State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Key Laboratory of Servo Motion System Drive and Control Ministry of Industry and Information Technology Beijing Institute of Technology

In order to meet the demand for high-precision operation of the vibroseis vehicle in the case of unmanned driving, an unmanned operation system that meets the working characteristics of the vibroseis vehicle is designed, and the key technical problems are studied, so that the vibroseis vehicle can operate in the complex environment of the field and improve the efficiency of geological exploration greatly. Firstly, the coordinate system and the kinematic model without sideslip of the articulated vehicle are established successively. Secondly, in order to improve the path tracking accuracy of the vibroseis vehicle, a model predictive control algorithm based on the kinematic model is designed for vehicle path tracking. In order to improve the positioning accuracy of the working point, a compensation algorithm for positioning error is proposed to reduce the positioning error caused by terrain factors. Finally, the unmanned operation platform is built and the path tracking algorithm and the compensation algorithm for positioning error are verified on the platform. The real vehicle test data shows that the path tracking algorithm proposed in this paper can control the average lateral error of the path tracking of the vibroseis vehicle within 22 *** with the PID control method, its path tracking accuracy can be improved by 59%. The average positioning error of working point is controlled within about 15 cm by adopting the compensation algorithm for positioning error.

关键词： Vibroseis vehicle Unmanned operation Path tracking Positioning compensation

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Point Cloud Preprocessing on 3D LiDAR data for Unmanned Surface Vehicle in Marine Environment

Point Cloud Preprocessing on 3D LiDAR data for Unmanned Surf...

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2020 IEEE International Conference on information Technology, Big Data and Artificial Intelligence, ICIBA 2020

作者： Qi, Xianzhi Fu, Wenxing An, Pei Wu, Bingli Ma, Jie National Key Laboratory of Science and Technology on Multispectral Information Processing School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100071 China

ISBN: (纸本)9781728152240

Point cloud preprocessing is still a challenging task in the marine environment, for it is difficult to filter out non-obstacle points while avoiding damage to the obstacle completeness. In this paper, we propose a novel data preprocessing method on 3D LiDAR data for the unmanned surface vehicle in the marine environment. It consists of two tasks: outlier removal and wake filtering. As the spatial resolution of LiDAR changes with distance, we exploit distance normalization on statistical outlier filter for robust outlier removal. Considering the gradient difference between wave wake and obstacle surface near the water, we define and calculate the vertical state of point cloud on the range image to obtain the pre-filtering point set, and then use the RANSAC method to filter out the wake points. Experiments on real data has demonstrated the effectiveness of the proposed algorithm both in terms of feasibility and accuracy. © 2020 IEEE.

关键词： Wakes

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Tracking Performance of Networked systems with Limited Bandwidth and Colored Noise

Tracking Performance of Networked Systems with Limited Bandw...

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Chinese Automation Congress (CAC)

作者： Bin Zhang Xiaowei Jiang Li Sun Xianhe Zhang School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China Key Laboratory of System Control and Information Processing Ministry of Education Shanghai China School of Statistics and Mathematics Zhongnan University of Economics and Law Wuhan China School of Electrical Engineering and Automation Hubei Normal University Huangshi China

This study investigated the optimal tracking performance (OTP) of multi-input multi-output (MIMO), discrete- time networked control systems (NCSs). The limits of tracking performance (TP) under the influences of bandwidth, encoding- decoding, and additive coloured Gaussian noise (ACGN) are derived using the techniques of coprime decomposition and all-pass decomposition. The results reveal the negative impact of non-minimum phase (NMP) zeros and unstable poles of the plant as well as network communication constraints on the TP of NCSs. Finally, a numerical simulation is discussed and verifies our conclusions.

关键词： Networked control systems Gaussian noise Bandwidth Numerical simulation Downlink Decoding Colored noise

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An IMU Error Correction Method Based on Multithreshold ZV Detection and SRCKF

An IMU Error Correction Method Based on Multithreshold ZV De...

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Cyber-Physical Social Intelligence (ICCSI), International Conference on

作者： Jialiang Luo Shichao Chen Yisheng Lv Wenqiao Sun Fan Yang Ruijie Xu The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences School of Information Engineering China University of Geosciences Beijing China The State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences The Center of National Railway Intelligent Transportation System Engineering and Technology China Academy of Railway Sciences Corporation Limited Beijing China The State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences Beijing China Transportation and Economics Research Institute and the Center of National Railway Intelligent Transportation System Engineering and Technology China Academy of Railway Sciences Corporation Limited China The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences College of Rail Transit Shan Dong JiaoTong University Jinan China Department of Aeronautical and Aviation Engineering The Hong Kong Polytechnic University Hong Kong China

With the rapid development and widespread application of Inertial Measurement Units (IMUs), IMU-based human localization has become critically important in environments lacking Global Navigation Satellite systems (GNSS) signals. Methods such as UWB/WIFI and other anchor-based localization have been employed to enhance the positioning accuracy. However, these methods are susceptible to the environmental interference and increased costs. In contrast, SINS-based localization methods eliminate reliance on the external data. However, this method can suffer from drift errors due to cumulative integration errors. Inertial navigation error correction techniques like Zero Detection Update Technology (ZUPT) provide potential solutions to address drift errors. This paper proposes an error correction method based on the multithreshold zero-velocity detection and Square Root Cubature Kalman Filter (SRCKF) updates. Compared to the single fixed threshold detection, the multi-threshold zero-velocity detection reduces the likelihood of missed zero velocity detection and false alarms, providing accurate time intervals for error correction. Experimental results demonstrate that the SRCKF-based algorithm reduces position deviation to approximately 0.3146 meters, corresponding to an error ratio of1.14%. The proposed method enables cost-effective and accurate pedestrian localization, driving advancements in the field.

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Model-Free Nonlinear Feedback Optimization

arXiv

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arXiv 2022年

作者： He, Zhiyu Bolognani, Saverio He, Jianping Dörfler, Florian Guan, Xinping Automatic Control Laboratory ETH Zürich Zürich8092 Switzerland 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

Feedback optimization is a control paradigm that enables physical systems to autonomously reach efficient operating points. Its central idea is to interconnect optimization iterations in closed-loop with the physical plant. Since iterative gradient-based methods are extensively used to achieve optimality, feedback optimization controllers typically require the knowledge of the steady-state sensitivity of the plant, which may not be easily accessible in some applications. In contrast, in this paper, we develop a model-free feedback controller for efficient steady-state operation of general dynamical systems. The proposed design consists of updating control inputs via gradient estimates constructed from evaluations of the nonconvex objective at the current input and at the measured output. We study the dynamic interconnection of the proposed iterative controller with a stable nonlinear discrete-time plant. For this setup, we characterize the optimality and stability of the closed-loop behavior as functions of the problem dimension, the number of iterations, and the rate of convergence of the physical plant. To handle general constraints that affect multiple inputs, we enhance the controller with Frank-Wolfe-type updates. © 2022, CC BY-SA.

关键词： Feedback control

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I Can Read Your Mind: control Mechanism Secrecy of Networked Dynamical systems under Inference Attacks

arXiv

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arXiv 2022年

作者： He, Jianping Li, Yushan Cai, Lin Guan, Xinping The 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 The Dept. of Electrical and Computer Engineering University of Victoria BC Canada

Recent years have witnessed the fast advance of security research for networked dynamical system (NDS). Considering the latest inference attacks that enable stealthy and precise attacks into NDSs with observation-based learning, this article focuses on a new security aspect, i.e., how to protect control mechanism secrets from inference attacks, including state information, interaction structure and control laws. We call this security property as control mechanism secrecy, which provides protection of the vulnerabilities in the control process and fills the defense gap that traditional cyber security cannot handle. Since the knowledge of control mechanism defines the capabilities to implement attacks, ensuring control mechanism secrecy needs to go beyond the conventional data privacy to cover both transmissible data and intrinsic models in NDSs. The prime goal of this article is to summarize recent results of both inference attacks on control mechanism secrets and countermeasures. We first introduce the basic inference attack methods on the state and structure of NDSs, respectively, along with their inference performance bounds. Then, the corresponding countermeasures and performance metrics are given to illustrate how to preserve the control mechanism secrecy. Necessary conditions are derived to guide the secrecy design. Finally, thorough discussions on the control laws and open issues are presented, beckoning future investigation on reliable countermeasure design and tradeoffs between the secrecy and control performance. Copyright © 2022, The Authors. All rights reserved.

关键词： Cybersecurity

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A new method of single-phase ground fault line selection based on principal component analysis and support vector machine

A new method of single-phase ground fault line selection bas...

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Chinese Automation Congress (CAC)

作者： Sicheng Wen Shangbin Jiao Qing Zhang Qing Wang Key Laboratory of complex system and intelligent information processing in Shaanxi Province Xi'an University of Technology Xi’an China

ISBN: (数字)9781728176871

ISBN: (纸本)9781728176888

For the existing single-fault line selection methods that cannot accurately identify all single-phase grounding faults in a small current grounding system, this paper proposes a new method of small current single-phase grounding fault line selection based on the combination of principal component analysis and support vector machine. This method first uses wavelet transform to denoise and divide the transient zero-sequence current of the bus and each feeder; then uses the zero-sequence energy method to first detect the bus fault. If the detected fault is a bus fault, end of line selection; if the detected fault is not a bus fault, use principal component analysis to reduce the dimension of the fault zero sequence current signal. Select the three most influential factors, and enter the support vector machine classifier to finally get the fault line. Use Matlab/Simulink to build a simulation model and simulate fault experiments. The final experimental results show that this method has high stability in line selection and is not affected by noise, ground resistance, fault angle, fault distance, and the number of feeders. Identity bus faults and feeder faults, and select lines accurately.

关键词： OWL Germanium

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Global Finite Time Stabilization of SISO Hurwitz Linear systems Subject to Actuator Saturation: The Case of Real Eigenvalues

Global Finite Time Stabilization of SISO Hurwitz Linear Syst...

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American control Conference (ACC)

作者： Tan Hou Yuanlong Li Zongli Lin Department of Automation Shanghai Jiao Tong University Shanghai P. R. China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai P. R. China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai P. R. China Charles L. Brown Department of Electrical and Computer Engineering University of Virginia Charlottesville VA U.S.A.

ISBN: (数字)9798350382655

ISBN: (纸本)9798350382662

This paper considers the global finite time stabilization of linear systems subject to actuator saturation. We show that a controllable SISO system whose eigenvalues are real and negative can be globally stabilized in finite time by a homogeneous feedback law. To obviate numerical issues, this homogeneous feedback law is implemented by discretizing a compact set. Numerical simulation validates the effectiveness of the proposed approach.

关键词： Linear systems Actuators Numerical simulation control systems Eigenvalues and eigenfunctions

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