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The vulnerability of cyber-physical system under stealthy attacks

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arXiv 2020年

作者： Sui, Tianju Mo, Yilin Marelli, Damián Sun, Ximing Fu, Minyue School of Control Science and Engineering Dalian University of Technology Dalian China Department of Automation Tsinghua University Beijing China School of Automation Guangdong University of Technology Guangzhou China French Argentine International Center for Information and Systems Sciences National Scientific and Technical Research Council Argentina School of Electrical Engineering and Computer Science University of Newcastle CallaghanNSW2308 Australia School of Automation Guandong University of Technology China

In this paper, we study the impact of stealthy attacks on the Cyber-Physical System (CPS) modeled as a stochastic linear system. An attack is characterised by a malicious injection into the system through input, output or both, and it is called stealthy (resp. strictly stealthy) if it produces bounded changes (resp. no changes) in the detection residue. Correspondingly, a CPS is called vulnerable (resp. strictly vulnerable) if it can be destabilized by a stealthy attack (resp. strictly stealthy attack). We provide necessary and sufficient conditions for the vulnerability and strictly vulnerability. For the invulnerable case, we also provide a performance bound for the difference between healthy and attacked system. Numerical examples are provided to illustrate the theoretical results. Copyright © 2020, The Authors. All rights reserved.

关键词： Embedded systems

Robust Adaptive Back-stepping Attitude control for Hypersonic Reentry Vehicles

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Robust Adaptive Back-stepping Attitude Control for Hypersoni...

2019 IEEE International Conference on Unmanned systems, ICUS 2019

作者： Wu, Tiancai Wang, Honglun Li, Na Yu, Yue Wu, Jianfa Beihang University School of Automation Science and Electrical Engineering Shenyuan Honors College Beijing China Beihang University Sch. of Automat. Sci. and Elec. Engineering Science and Technology on Aircraft Control Laboratory Beijing China Beihang University Unmanned Systems Research Institute Beijing China Beijing Aerospace Automatic Control Institute Beijing China

ISBN: (纸本)9781728137926

In this paper, a robust adaptive back-stepping attitude controller is investigated for hypersonic reentry vehicle under unknown parameters and external disturbances. Firstly, the affine nonlinear system of HRV is established in the form of a cascade structure. Secondly, the robust attitude controller based on linear extended state observer, back-stepping method and adaptive control technique is proposed. An adaptive strategy is applied to identify the unknown parameters. Linear extended state observer is applied to observe and compensate the intricate external disturbances. control law and parameter adaptive law can be obtained, and the stability of closed-loop control system can be guaranteed by choosing the appropriate Lyapunov function. Finally, simulation results and discussions are presented to verify the effectiveness of the proposed control strategy. © 2019 IEEE.

关键词： Attitude control

Distributed Algorithm for Robust Resource Allocation with Polyhedral Uncertain Allocation Parameters

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Journal of systems Science & Complexity 2018年第1期31卷 103-119页

作者： ZENG Xianlin YI Peng HONG Yiguang School of Automation Beijing Institute of Technology Beijing 100081 China Department of Electrical and Systems Engineering Washington University in St. Louis St. Louis MO 63130 USA Key Laboratory of Systems and Control Institute of Systems Science Chinese Academy of Sciences Beijing 100190 China

This paper studies a distributed robust resource allocation problem with nonsmooth objective functions under polyhedral uncertain allocation parameters. In the considered distributed robust resource allocation problem, the（nonsmooth） objective function is a sum of local convex objective functions assigned to agents in a multi-agent network. Each agent has a private feasible set and decides a local variable, and all the local variables are coupled with a global affine inequality constraint,which is subject to polyhedral uncertain parameters. With the duality theory of convex optimization,the authors derive a robust counterpart of the robust resource allocation problem. Based on the robust counterpart, the authors propose a novel distributed continuous-time algorithm, in which each agent only knows its local objective function, local uncertainty parameter, local constraint set, and its neighbors＇ information. Using the stability theory of differential inclusions, the authors show that the algorithm is able to find the optimal solution under some mild conditions. Finally, the authors give an example to illustrate the efficacy of the proposed algorithm.

关键词： Distributed optimization resource allocation robust optimization polyhedral uncertain parameters nonsmooth optimization

Statistical approach to detection of attacks for stochastic cyber-physical systems

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arXiv 2020年

作者： Marelli, Damián Sui, Tianju Fu, Minyue Lu, Renquan School of Automation Guangdong University of Technology Guangzhou China French Argentine International Center for Information and Systems Sciences National Scientific and Technical Research Council Argentina School of Control Science and Engineering Dalian University of Technology Dalian China School of Electrical Engineering and Computer Science University of Newcastle CallaghanNSW2308 Australia School of Automation Guangdong Provincial Key Laboratory of Intelligent Decision and Cooperative Control Guandong University of Technology Guangzhou China

We study the problem of detecting an attack on a stochastic cyber-physical system. We aim to treat the problem in its most general form. We start by introducing the notion of asymptotically detectable attacks, as those attacks introducing changes to the system’s output statistics which persist asymptotically. We then provide a necessary and sufficient condition for asymptotic detectability. This condition preserves generality as it holds under no restrictive assumption on the system and attacking scheme. To show the importance of this condition, we apply it to detect certain attacking schemes which are undetectable using simple statistics. Our necessary and sufficient condition naturally leads to an algorithm which gives a confidence level for attack detection. We present simulation results to illustrate the performance of this algorithm. Copyright © 2020, The Authors. All rights reserved.

关键词： Stochastic systems

FSD-10: A dataset for competitive sports content analysis

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arXiv 2020年

作者： Liu, Shenglan Liu, Xiang Huang, Gao Feng, Lin Hu, Lianyu Jiang, Dong Zhang, Aibin Liu, Yang Qiao, Hong Faculty of Electronic Information and Electrical Engineering Dalian University of Technology Dalian Liaoning116024 China Faculty of Tsinghua University of Technology Beijing China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China

Action recognition is an important and challenging problem in video analysis. Although the past decade has witnessed progress in action recognition with the development of deep learning, such process has been slow in competitive sports content analysis. To promote the research on action recognition from competitive sports video clips, we introduce a Figure Skating Dataset (FSD-10) for finegrained sports content analysis. To this end, we collect 1484 clips from the worldwide figure skating championships in 2017-2018, which consist of 10 different actions in men/ladies programs. Each clip is at a rate of 30 frames per second with resolution 1080 × 720. These clips are then annotated by experts in type, grade of execution, skater info,.etc. To build a baseline for action recognition in figure skating, we evaluate state-of-the-art action recognition methods on FSD-10. Motivated by the idea that domain knowledge is of great concern in sports field, we propose a keyframe based temporal segment network (KTSN) for classification and achieve remarkable performance. Experimental results demonstrate that FSD-10 is an ideal dataset for benchmarking action recognition algorithms, as it requires to accurately extract action motions rather than action poses. We hope FSD-10, which is designed to have a large collection of finegrained actions, can serve as a new challenge to develop more robust and advanced action recognition models. Copyright © 2020, The Authors. All rights reserved.

关键词： Sports

Feedforward and Feedback Model Free Adaptive Iterative Learning control with Application to a Linear Motor System

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Feedforward and Feedback Model Free Adaptive Iterative Learn...

第三十八届中国控制会议

作者： Li Duan Xian Yu ShangTai Jin ZhongSheng Hou XuHui Bu the Advanced Control Systems Lab the School of Electronic and Information Engineering Beijing Jiaotong University the School of Automation Qingdao University the School of Electrical Engineering and Automation Henan Polytechnic University

In this paper, a discrete-time feedforward and feedback model-free adaptive iterative learning control(FFMFAILC)approach is applied to the position tracking of the linear motor gantry system LMG2A-CB6-CC8. Firstly, the feedforward controller is designed by utilizing the model-free adaptive iterative(MFAILC) approach. Then the FFMFAILC method is proposed by adding the feedback control law based on the original MFAILC to reject non-repetitive exogenous ***, the effectiveness and robustness of the FFMFAILC approach are verified through simulation and experiment on the linear motor gantry system compared with the MFAILC approach.

关键词： feedforward and feedback control model free adaptive iterative(MFAILC) linear motor position tracking

Reduced order modeling of diffusively coupled network systems: An optimal edge weighting approach

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arXiv 2020年

作者： Cheng, Xiaodong Yu, Lanlin Ren, Dingchao Scherpen, Jacquelien M.A. Control Systems Group Department of Electrical Engineering Eindhoven University of Technology Eindhoven5600 MB Netherlands Institute of Advanced Technology Westlake Institute for Advanced Study Westlake University Hangzhou310024 China Department of Automation University of Science and Technology of China Hefei230026 China Jan C. Willems Center for Systems and Control Engineering and Technology Institute Groningen Faculty of Science and Engineering University of Groningen Nijenborgh 4 Groningen9747 AG Netherlands

This paper studies reduced-order modeling of dynamic networks with strongly connected topology. Given a graph clustering of an original complex network, we construct a quotient graph with less number of vertices, where the edge weights are parameters to be determined. The model of the reduced network is thereby obtained with parameterized system matrices, and then an edge weighting procedure is devised, aiming to select an optimal set of edge weights that minimizes the approximation error between the original and the reduced-order network models in terms of H2-norm. The effectiveness of the proposed method is illustrated by a numerical example. Copyright © 2020, The Authors. All rights reserved.

关键词： Complex networks

Convex Relaxation with Log-Determinant Divergence-L1 Regularization for 3D Shape Reconstruction

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Convex Relaxation with Log-Determinant Divergence-L1 Regular...

第三十八届中国控制会议

作者： Wei Cao Luefeng Chen Min Wu Witold Pedrycz School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Department of Electrical and Computer Engineering University of Alberta

Investigated is the problem of estimating the 3 D shape of an object defined by a set of 3 D landmarks with their 2 D correspondences in a single image. To solve this problem, we use a dictionary of the basic shape with LDD-L1 regularization,which is the construction of the shape space model. Based on the proposed convex optimization method, 3 D human pose reconstruction by shape space model and 3 D variable shape model was carried out on the mocap database. To improve accuracy and reduce the number of iterations, we use PSO algorithm to optimize initial value of the key parameter. The experimental results show that the improved algorithm exhibits less iterations but higher accuracy, which can be much helpful in practical applications.

关键词： LDD-L1 regularization 3D reconstruction PSO

Finite-time Passive control of Networked Semi-Markov Jump systems with Time-varying Delays

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Finite-time Passive Control of Networked Semi-Markov Jump Sy...

第三十八届中国控制会议

作者： Yidao Ji Wei Wu School of Automation and Electrical Engineering University of Science and Technology Beijing State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences

This paper studies the finite-time control issue of semi-Markov jump systems with time-varying delays based under passivity framework. Firstly, sufficient criterion is derived to ensure that finite-time boundedness condition can be satisfied and the desired passivity performance can be achieved simultaneously. Then, state-feedback controller procedure is presented with help of linear matrix inequalities(LMIs). Finally, a simulation example is provided for showing the applicability of the developed method.

关键词： finite-time boundedness semi-Markov jump systems time-varying delays passivity