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A survey on the security of cyber-physical systems

control Theory and Technology 2016年第1期14卷 2-10页

作者： Guangyu WU Jian SUN Jie CHEN School of Automation Beijing Institute of Technology Beijing 100081 China Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing 100081 China

Cyber-physical systems （CPSs） are integrations of computation, communication, control and physical processes. Typical examples where CPSs are deployed include smart grids, civil infrastructure, medical devices and manufacturing. Security is one of the most important issues that should be investigated in CPSs and hence has received much attention in recent years. This paper surveys recent results in this area and mainly focusses on three important categories： attack detection, attack design and secure estimation and control. We also discuss several future research directions including risk assessment, modeling of attacks and attacks design, counter-attack strategy and testbed and validation.

关键词： Security cyber-physical systems attack detection secure estimation and control

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A Model Reference Adaptive control with ADP-to-SMC Strategy for Unknown Nonlinear systems

A Model Reference Adaptive Control with ADP-to-SMC Strategy ...

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Asian control Conference

作者： Hao Fu Xin Chen Wei Wang School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China

ISBN: (纸本)9781509015740;9781509015733

In this paper, a novel online learning controller based on model reference adaptive control (MRAC) is presented to simplify the complexity of controlling a class of discrete nonlinear systems with a little prior knowledge, using approximate dynamic programming (ADP). Without the identifier and the assumption of a command generator model, the proposed approach employs a modified direct heuristic dynamic programming (HDP) to acquire two types of the bounded tracking errors, which are available to transform the system into a linear system with the uncertain bounded persistent disturbance. In addition, toggling between the learning and the sliding mode control (SMC) flexibly, an ADP-to-SMC strategy is developed to guarantee the better performance in MRAC. Finally, Simulation results demonstrate the effectiveness of the proposed control scheme.

关键词： Mathematical model Nonlinear systems Adaptation models Linear systems Computational modeling Linear programming Generators

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Nonlinear integral sliding mode variable structure control for two-tank system with input — Limitation

Nonlinear integral sliding mode variable structure control f...

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Annual Conference of Industrial Electronics Society

作者： Hai-Peng Ren Jiao Hu Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology Xi'an Shaanxi CN Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology Xi'an China

To deal with the unsatisfactory transient response of the conventional integral sliding mode control (ISMC), A nonlinear integral sliding mode controller (NISMC) is proposed in this paper, which uses a smooth nonlinear function with “small error amplification and large error saturation” property, meanwhile, takes the limited input into account. The proposed NISMC improves the transient performance, i.e., less controller chattering and less steady error. The two-tank system is usually treated as a paradigm to test the control algorithms. Five kinds of sliding-mode control methods (SMC) are used to control the two-tank liquid level to test the performance. The simulation and experimental results show that the proposed NISMC has the superior performance as compared to the comparison methods.

关键词： Liquids Two dimensional displays Level control Robustness Valves Sliding mode control Transient analysis

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Switching control System Based on Robust Model Reference Adaptive control

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Journal of systems Science & complexity 2016年第4期29卷 897-932页

作者： HU Qiong FEI Qing MA Hongbin WU Qinghe GENG Qingbo School of Automation Beijing Institute of Technology Shanghai Institute of Optics and Fine Mechanics Chinese Academy of Sciences State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institution of Technology

For conventional adaptive control, time-varying parametric uncertainty and unmodeled dynamics are ticklish problems, which will lead to undesirable performance or even instability and nonrobust behavior, respectively. In this study, a class of discrete-time switched systems with unmodeled dynamics is taken into consideration. Moreover, nonlinear systems are here supposed to be approximated with the class of switched systems considered in this paper, and thereby switching control design is investigated for both switched systems and nonlinear systems to assure stability and performance. For robustness against unmodeled dynamics and uncertainty, robust model reference adaptive control(RMRAC) law is developed as the basis of controller design for each individual subsystem in the switched systems or nonlinear systems. Meanwhile, two different switching laws are presented for switched systems and nonlinear systems, respectively. Thereby, the authors incorporate the corresponding switching law into the RMRAC law to construct two schemes of switching control respectively for the two kinds of controlled systems. Both closed-loop analyses and simulation examples are provided to illustrate the validity of the two proposed switching control schemes. Furthermore, as to the proposed scheme for nonlinear systems, its potential for practical application is demonstrated through simulations of longitudinal control for F-16 aircraft.

关键词： Longitudinal control of F-16 aircraft switching control switching law. nonlinear systems RMRAC switched systems

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Maximum power point tracking control of direct-drive permanent magnet wind turbine based on adaptive neuro-fuzzy inference system 5

Maximum power point tracking control of direct-drive permane...

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5th International Workshop on Advanced Computational Intelligence and intelligent Informatics, IWACIII 2017

作者： Ding, Min Ou, Yingxiong Hu, Bo She, Jinhua Wu, Min School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China State Grid Energy Research Institute Beijing102200 China School of Engineering Tokyo University of Technology Tokyo192-0982 Japan

The power from wind varies depending on the environmental factors. Because of the randomness and intermittent of wind, it is difficult for the wind energy conversion system to locate and track the maximum power point (MPP) with fast speed and high accuracy under the condition of variable wind speed. In this paper, a variable-speed wind-generator maximum power point tracking (MPPT) control method based on adaptative neuro-fuzzy inference system (ANFIS) is presented. It is designed as a combination of the Sugeno fuzzy model and neural network. The ANFIS based controller predicts the optimum speed with the inputs as the speed change and power change, and controls the speed with PI controllers. The performance of the proposed controller is tested for direct-drive permanent magnet wind turbine based wind energy conversion system under fast wind speed variation in MATLAB/Simulink. The simulation results show that the designed control method has good dynamic characteristics and steady-state accuracy in wind power MPPT and improves the working efficiency.

关键词： Wind turbines

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Stability analysis of human–adaptive controller interactions

Stability analysis of human–adaptive controller interaction...

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AIAA Guidance, Navigation, and control Conference, 2017

作者： Yucelen, Tansel Yildiz, Yildiray Sipahi, Rifat Youse, Ehsan Nguyen, Nhan Department of Mechanical Engineering University of South Florida TampaFL United States Mechanical Engineering Department Systems Laboratory at Bilkent University Ankara Turkey Mechanical and Industrial Engineering Department Complex Dynamic Systems and Control Laboratory Northeastern University BostonMA United States Advanced Control and Evolvable Systems Group Intelligent Systems Division Ames Research Center of the National Aeronautics and Space Administration Moffett FieldCA United States

ISBN: (数字)9781624104503

ISBN: (纸本)9781624104503

In this paper, stability of human in the loop model reference adaptive control architectures is analyzed. For a general class of linear human models with time-delay, a fundamental stability limit of these architectures is established, which depends on the parameters of this human model as well as the reference model parameters of the adaptive controller. It is shown that when the given set of human model and reference model parameters satisfy this stability limit, the closed-loop system trajectories are guaranteed to be stable. © 2017, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Closed loop systems

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Duplicate checking Strategies for Selecting Topics for Graduation Thesis Based on Maximum Public Sequence

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IOP Conference Series: Earth and Environmental Science 2019年第3期267卷

作者： Guorui Yu Li Huang Jiewen Sun Shangchun Liao School of Computer Science and Technology Wuhan University of Science and Technology phone:*** Intelligent Information Processing and Hubei Real-time Industrial Systems Laboratory. Key Laboratory of Metallurgical Equipment and Control Technology Wuhan University of Science and Technology Ministry of Education.

The system is based on the undergraduate thesis management system as the practice platform, focusing on the realization of the thesis topic check function. The current check-up detection system is based on the entire contents of the query, and does not meet the requirements for an undergraduate thesis query. According to the characteristics of the thesis, the system first divides the keywords into the topic, selects the irrelevant parts, then removes the irrelevant words, and finally checks the keywords in the topic, and realizes the efficient and accurate check for inspection.

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Spike-burst chimera states in an adaptive exponential integrate-and-fire neuronal network

arXiv

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arXiv 2019年

作者： Santos, Moises S. Protachevicz, Paulo R. Iarosz, Kelly C. Caldas, Iberê L. Viana, Ricardo L. Borges, Fernando S. Ren, Hai-Peng Szezech, José D. Batista, Antonio M. Grebogi, Celso Department of Physics Federal University of Paraná CuritibaPR80060-000 Brazil Graduate in Science Program - Physics State University of Ponta Grossa Ponta Grossa PR84030-900 Brazil Institute of Physics University of São Paulo São PauloSP05508-900 Brazil Center for Mathematics Computation and Cognition Federal University of ABC São Bernardo do CampoSP09606-045 Brazil Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xian University of Technology Xi'an710048 China Xian Technological University Xi'an710021 China Graduate in Science Program - Physics State University of Ponta Grossa Ponta Grossa PR84030-900 Brazil Institute for Complex Systems and Mathematical Biology King's College University of Aberdeen AberdeenAB24 3UE United Kingdom

Chimera states are spatiotemporal patterns in which coherence and incoherence coexist. We observe the coexistence of synchronous (coherent) and desynchronous (incoherent) domains in a neuronal network. The network is composed of coupled adaptive exponential integrate-and-fire neurons that are connected by means of chemical synapses. In our neuronal network, the chimera states exhibit spatial structures both with spikes and bursts activities. Furthermore, those desynchronised domains not only have either spike or burst activity, but we show that the structures switch between spikes and bursts as the time evolves. Moreover, we verify the existence of multicluster chimera states. Copyright © 2019, The Authors. All rights reserved.

关键词： Neural networks

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A LiDAR Odometry for Outdoor Mobile Robots Using NDT Based Scan Matching in GPS-denied environments

A LiDAR Odometry for Outdoor Mobile Robots Using NDT Based S...

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IEEE International Conference on Cyber Technology in Automation, control, and intelligent systems

作者： Bo Zhou Zhongqiang Tang Kun Qian Fang Fang Xudong Ma Key Laboratory of Measurement and Control of Complex Systems of Engineering School of Automation Southeast University

ISBN: (纸本)9781538604915

The three-dimensional localization problem of outdoor mobile robots is a primary issue for autonomous navigation applications, since the accuracy of positioning will affect the incoming mapping and path planning tasks heavily. In this paper, using INS, encoder and laser LiDAR as the main means for pose perception, a laser LiDAR aided odometry approach based on the normal distributions transform(NDT) scan matching approach is proposed to improve the precision of pose estimates for a mobile robot in GPS denied outdoor environments. The 3D kinematic model of the mobile robot is developed so that the IMU and the encoder data can be fused firstly to obtain the initial localization result with dead reckoning technologies. On that basis, the three-dimensional NDT scan matching method is introduced to compute the pose transformation matrix in real-time using the adjacent two depth frames from LiDAR data, which can get fine pose estimates by calibrate the accumulation errors periodically. Experiments results show the correctness and validity of the presented method.

关键词： Out mobile robots LiDAR odometry NDT matching Auxiliary positioning Outdoor mobile robot Nondestructive Testing Mobile robots Lidar positioning accuracy odometry scanning transformation matrix

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Incorporating message embedding into co-factor matrix factorization for retweeting prediction

Incorporating message embedding into co-factor matrix factor...

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2017 International Joint Conference on Neural Networks, IJCNN 2017

作者： Wang, Can Li, Qiudan Wang, Lei Dajun Zeng, Daniel State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China University of Chinese Academy of Sciences Beijing China Department of Management Information Systems University of Arizona TucsonAZ United States

ISBN: (纸本)9781509061815

With the rapid growth of Web 2.0, social media has become a prevalent information sharing and spreading platform, where users can retweet interesting messages. To better understand the propagation mechanism for information diffusion, it is necessary to model the user retweeting behavior and predict future retweets. Some existing work in retweeting prediction based on matrix factorization focuses on using user-message interaction information, user information and social influence information, etc. The challenge of improving prediction performance is how to jointly perform deep representation of these information to solve the sparsity problem and then learn a more comprehensive retweeting behavior model. Inspired by word2vec and co-factor matrix factorization model, this paper proposes a hybrid model, called HCFMF, for learning users' retweeting behavior, it first computes the message content similarity by considering the message co-occurrence, the author information and word2vec based low-dimensional representation of content, then, jointly decomposes the user-message matrix and message-message similarity matrix based on a co-factorization model. We empirically evaluate the performance of the proposed model on real world weibo datasets. Experimental results show that taking the dense representation of author and content information into consideration could allow us make more accurate analysis of users' retweeting patterns. The mined patterns could serve as a feedback channel for both consumers and management departments. © 2017 IEEE.

关键词： Forecasting

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