检索结果-内蒙古大学图书馆

False Noise Attack Detection for differentially-private distributed control of microgrids

学校读者我要写书评

暂无评论

Automatica 2025年 179卷

作者： Feng Ye Xianghui Cao Lin Cai Mo-Yuen Chow School of Automation Southeast University Nanjing 210096 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing 210096 China Department of Electrical and Computer Engineering University of Victoria Victoria BC V8W 3P6 Canada UM-SJTU Joint Institute Shanghai Jiao Tong University Shanghai 200240 China

Privacy preserving in distributed control is getting more attention, and differential privacy (DP) is the common tool to protect data privacy, in which additive noise is applied in the algorithm function. However, DP can be leveraged by false noise (FN) attacks because attack vectors can be disguised as artificial noise in DP. FN attacks are a concern as the stealth attacks are hard to detect. Moreover, DP in distributed control makes FN attack detection more difficult. Hence, detecting FN attacks in privacy-preserving distributed control is critical and challenging. In this paper, taking distributed energy management systems as the control object, we propose a novel peer-to-peer attack detection approach, named False Noise Attack Detection (FNAD). In FNAD, each device observes the power decisions of its neighbors based on the data from its two-hop neighbors, estimates the power decisions of its neighbors by a Kalman filter, and updates the detection index of each neighbor according to the residues of the Kalman filter at each iteration. The detection index is developed based on information entropy, without any prior knowledge of the FN attacks. If a device’s detection index is out of well-defined thresholds, its neighbors can perform a majority vote to decide whether it is malicious. We theoretically prove the detection effect of FNAD against three representative attacks in the literature and analyze the advantages of FNAD compared with the traditional methods. The effectiveness of FNAD is demonstrated by extensive simulations.

关键词：

A Learner Model Integrating Cognitive and Metacognitive And Its Application on Scratch Programming Projects

学校读者我要写书评

暂无评论

IFAC-PapersOnLine 2020年第5期53卷 644-649页

作者： Sifeng Jing Ying Tang Xiwei Liu Xiaoyan Gong The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China Institute of Smart Education Systems Qingdao Academy of Intelligent Industries Qingdao 266044 China Department of Electrical and Computer Engineering Rowan University Glassboro NJ 08028 USA

learner’s cognitive and metacognitive are key personal profile for individualized teaching. To evaluate learner’s comprehensive characteristics, existing learner model were reviewed. Two challenges of constructing an accurate and comprehensive learner model integrating cognitive and metacognitive were summarized. A plan of constructing a comprehensive learner model was made based on analysis of existing massive online learning environment, sensor information technology and educational data-mining. As a case study, a method of how to map learning data onto learners’ cognitive and metacognitive was proposed based on an analysis of a number of pupils’ Scratch projects. Three mapping table were established. Pupil’s cognitive skill could be evaluated from technology shown from Scratch project, namely, data structure, algorithm, computational practices and overall evaluation. Content shown from Scratch project were used to infer pupil’s cognitive style. Meta-cognitive ability can be measured from computational practices and behavior in programming process.

关键词： learner model cognitive state metacognitive ability individualized teaching

Resonant beam communications with echo interference elimination

学校读者我要写书评

暂无评论

arXiv 2021年

作者： Xiong, Mingliang Liu, Qingwen Wang, Gang Giannakis, Georgios B. Zhang, Sihai Zhu, Jinkang Huang, Chuan College of Electronics and Information Engineering Tongji University Shanghai201804 China State Key Lab of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing100081 China Department of Electrical and Computer Engineering University of Minnesota MinneapolisMN55455 United States Key Lab of Wireless-Optical Communications University of Science and Technology of China Hefei Anhui230026 China School of Science and Engineering Chinese University of Hong Kong Shenzhen Guangdong518172 Hong Kong

Resonant beam communications (RBCom) is capable of providing wide bandwidth when using light as the carrier. Besides, the RBCom system possesses the characteristics of mobility, high signal-to-noise ratio (SNR), and multiplexing. Nevertheless, the channel of the RBCom system is distinct from other light communication technologies due to the echo interference issue. In this paper, we reveal the mechanism of the echo interference and propose the method to eliminate the interference. Moreover, we present an exemplary design based on frequency shifting and optical filtering, along with its mathematic model and performance analysis. The numerical evaluation shows that the channel capacity is greater than 15 bit/s/Hz. Copyright © 2021, The Authors. All rights reserved.

关键词： Internet of things

Linear System Identification Under Multiplicative Noise from Multiple Trajectory Data

学校读者我要写书评

暂无评论

Linear System Identification Under Multiplicative Noise from...

American control Conference

作者： Yu Xing Ben Gravell Xingkang He Karl Henrik Johansson Tyler Summers Key Lab of Systems and Control Academy of Mathematics and Systems Science Chinese Academy of Sciences and School of Mathematical Sciences University of Chinese Academy of Sciences Beijing P. R. China Department of Mechanical Engineering The University of Texas at Dallas Richardson TX USA Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden

ISBN: (数字)9781538682661

ISBN: (纸本)9781538682678

The study of multiplicative noise models has a long history in control theory but is re-emerging in the context of complex networked systems and systems with learning-based control. We consider linear system identification with multiplicative noise from multiple state-input trajectory data. We propose exploratory input signals along with a least-squares algorithm to simultaneously estimate nominal system parameters and multiplicative noise covariance matrices. The asymptotic consistency of the least-squares estimator is demonstrated by analyzing first and second moment dynamics of the system. The results are illustrated by numerical simulations.

关键词： Trajectory Covariance matrices Linear systems Heuristic algorithms Optimal control Mathematical model

Simultaneously Transmitting and Reflecting Reconfigurable Intelligent Surface Assisted NOMA Networks

学校读者我要写书评

暂无评论

arXiv 2021年

作者： Yue, Xinwei Xie, Jin Liu, Yuanwei Han, Zhihao Liu, Rongke Ding, Zhiguo The Key Laboratory of Information and Communication Systems Ministry of Information Industry China The Key Laboratory of Modern Measurement & Control Technology Ministry of Education Beijing Information Science and Technology University Beijing100101 China The School of Electronic Engineering and Computer Science Queen Mary University of London LondonE1 4NS United Kingdom The School of Electronic and Information Engineering Beihang University Beijing100191 China The Department of Electrical Engineering Princeton University Princeton United States The School of Electrical and Electronic Engineering The University of Manchester Manchester United Kingdom

Simultaneously transmitting/refracting and reflecting reconfigurable intelligent surface (STAR-RIS) has been introduced to achieve full coverage area. This paper investigate the performance of STAR-RIS assisted non-orthogonal multiple access (NOMA) networks over Rician fading channels, where the incidence signals sent by base station are reflected and transmitted to the nearby user and distant user, respectively. To evaluate the performance of STAR-RIS-NOMA networks, we derive new approximate expressions of outage probability and ergodic rate for a pair of users, in which the imperfect successive interference cancellation (ipSIC) and perfect SIC (pSIC) schemes are taken into consideration. Based on the asymptotic expressions, the diversity orders of the nearby user with ipSIC/pSIC and distant user are achieved carefully. The high signal-to-noise ratio slopes of ergodic rates for nearby user with pSIC and distant user are equal to one and zero, respectively. In addition, the system throughput of STAR-RIS-NOMA is discussed in delay-limited and delay-tolerant modes. Simulation results are provided to verify the accuracy of the theoretical analyses and demonstrate that: 1) The outage probability of STAR-RIS-NOMA outperforms that of STAR-RIS assisted orthogonal multiple access (OMA) and conventional cooperative communication systems;2) With the increasing of reflecting elements K and Rician factor κ, the STAR-RIS-NOMA networks are capable of attaining the enhanced performance;and 3) The ergodic rates of STAR-RIS-NOMA are superior to that of STAR-RIS-OMA. Copyright © 2021, The Authors. All rights reserved.

关键词： Signal to noise ratio

Convex relaxation of combined heat and power dispatch

学校读者我要写书评

暂无评论

arXiv 2020年

作者： Jiang, Yibao Wan, Can Botterud, Audun Song, Yonghua Shahidehpour, Mohammad College of Electrical Engineering Zhejiang University Hangzhou310027 China Laboratory for Information and Decision Systems Massachusetts Institute of Technology CambridgeMA02139 United States State Key Laboratory of Internet of Things for Smart City University of Macau Taipa China Electrical and Computer Engineering Department Illinois Institute of Technology ChicagoIL60616 United States

Combined heat and power dispatch promotes interactions and synergies between electric power systems and district heating systems. However, nonlinear and nonconvex heating flow imposes significant challenges on finding qualified solutions efficiently. Most existing methods rely on constant flow assumptions to derive a linear heating flow model, sacrificing optimality for computational simplicity. This paper proposes a novel convex combined heat and power dispatch model based on model simplification and constraint relaxation, which improves solution quality and avoids assumptions on operating regimes of district heating systems. To alleviate mathematical complexity introduced by the commonly used node method, a simplified thermal dynamic model is proposed to capture temperature changes in networked pipelines. Conic and polyhedral relaxations are then applied to convexify the original problems with bilinear and quadratic equality constraints. Furthermore, an adaptive solution algorithm is proposed to successively reduce relaxation gaps based on dynamic bivariate partitioning, improving solution optimality with desirable computational efficiency. The proposed method is verified on a 33-bus electric power system integrated with a 30-node district heating system and compared to nonlinear programming solvers and constant-flow-based solutions. Copyright © 2020, The Authors. All rights reserved.

关键词： Integer programming

State estimation for a class of linear systems with quadratic output

学校读者我要写书评

暂无评论

arXiv 2020年

作者： Theodosis, Dionysios Berkane, Soulaimane Dimarogonas, Dimos V. Dynamic Systems and Simulation Laboratory School of Production Engineering and Management Technical University of Crete Greece Département d’informatique et d’ingénierie Université du Québec en Outaouis GatineauQC Canada Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Sweden

This paper deals with the problem of state estimation for a class of linear time-invariant systems with quadratic output measurements. An immersion-type approach is presented that transforms the system into a state-affine system by adding a finite number of states to the original system. Under suitable persistence of excitation conditions on the input and its higher derivatives, global state estimation is exhibited by means of a Kalman-type observer. A numerical example is provided to illustrate the applicability of the proposed observer design for the problem of position and velocity estimation for a vehicle navigating in the n−dimensional Euclidean space using a single position range measurement. Copyright © 2020, The Authors. All rights reserved.

关键词： State estimation

Boost AI power: Data augmentation strategies with unlabelled data and conformal prediction, a case in alternative herbal medicine discrimination with electronic nose

学校读者我要写书评

暂无评论

arXiv 2021年

作者： Liu, Li Zhan, Xianghao Wu, Rumeng Guan, Xiaoqing Wang, Zhan Zhang, Wei Pilanci, Mert Wang, You Luo, Zhiyuan Li, Guang The State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou310027 China Department of Bioengineering Stanford University StanfordCA94305 United States The Computer Learning Research Center Royal Holloway University of London Egham Hill Surrey EghamTW20 0EX United Kingdom Department of Electrical Engineering Stanford University StanfordCA94305 United States

Electronic nose has been proven effective in alternative herbal medicine classification, but due to the nature of supervised learning, previous research heavily relies on the labelled training data, which are time-costly and labor-intensive to collect. To alleviate the critical dependency on the training data in real-world applications, this study aims to improve classification accuracy via data augmentation strategies. The effectiveness of five data augmentation strategies under different training data inadequacy are investigated in two scenarios: the noise-free scenario where different availabilities of unlabelled data were considered, and the noisy scenario where different levels of Gaussian noises and translational shift were added to represent sensor drifts. The five augmentation strategies, namely noise-adding data augmentation, semi-supervised learning, classifier-based online learning, Inductive Conformal Prediction (ICP) online learning and our novel ensemble ICP online learning (EICP) proposed in this study, are compared against supervised learning baselines, with Linear Discriminant Analysis (LDA) and Support Vector Machine (SVM) as the classifiers. This study provides a systematic analysis of different augmentation strategies. Our novel strategy, EICP, outperforms the others by showing non-decreasing classification accuracy on all tasks and a significant improvement on most simulated tasks (25 out of 36 tasks, p ≤ 0.05), which demonstrated both effectiveness and robustness in boosting the classification model generalizability. This strategy can be employed in other machine learning applications. Copyright © 2021, The Authors. All rights reserved.

关键词： Electronic nose

Current reversal and particle separation in Brownian transport

学校读者我要写书评

暂无评论

Physical Review Research 2021年第3期3卷 033162-033162页

作者： Hai-Wei Hu Lin Du Liang-Hui Qu Zi-Lu Cao Zi-Chen Deng Ying-Cheng Lai School of Mathematics and Statistics Northwestern Polytechnical University Xi'an 710072 China MIIT Key Laboratory of Dynamics and Control of Complex Systems Northwestern Polytechnical University Xi'an 710072 China School of Aeronautics Northwestern Polytechnical University Xi'an 710072 China School of Electrical Computer and Energy Engineering Arizona State University Tempe Arizona 85287 USA Department of Physics Arizona State University Tempe Arizona 85287 USA

In transport of micro- or nanosized particles through a confined structure driven by thermal fluctuations and external forcing—a situation that arises commonly in a variety of fields in physical and biological sciences, efficient and controllable separation of particles of different sizes is an important but challenging problem. We study, numerically and analytically, the diffusion dynamics of Brownian particles through the biologically relevant setting of a spatially periodic structure, subject to static and temporally periodic forcing. Molecular dynamical simulations reveal that the mean velocity in general depends sensitively on the particle size. The phenomenon of current reversal is uncovered, where particles larger than or smaller than a critical size diffuse in exactly opposite directions. This striking behavior occurs in a wide range of the forcing amplitude and provides a mechanism to separate the Brownian particles of different sizes. Besides the forcing amplitude, other parametric quantities characterizing the forcing profile, such as the temporal asymmetry, can also be exploited to modulate or control the transport dynamics of particles of different sizes. To gain a theoretical understanding, we exploit the Fick-Jacobs approximation to obtain a one-dimensional description of the diffusion problem, which enables key quantities characterizing the diffusion process, such as the mean velocity, to be predicted. In the regime of weak forcing, a reasonable agreement between theory and numerical results is achieved. Beyond the weakly forcing regime, the diffusion approximation breaks down, causing the theoretical predictions to deviate from the numerical results, into which we provide physical insights. Our findings have potential applications in optimizing transport in microfluidic devices or through biological channels.

关键词： Brownian motion Classical transport Brownian dynamics Langevin equation Stochastic differential equations