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Disagreement and Antagonism in Signed Networks: A Survey

IEEE/CAA Journal of Automatica Sinica 2022年第7期9卷 1166-1187页

作者： Yuxin Wu Deyuan Meng Zheng-Guang Wu Seventh Research Division Beihang University(BUAA)and also with the School of Automation Science and Electrical EngineeringBeihang University(BUAA)Beijing 100191China National Laboratory of Industrial Control Techno-logy Institute of Cyber-Systems and ControlZhejiang UniversityHangzhou 310027China IEEE

Signed networks refer to a class of network systems including not only cooperative but also antagonistic interactions among *** to the existence of antagonistic interactions in signed networks,the agreement of nodes may not be established,instead of which disagreement behaviors generally *** paper reviews several different disagreement behaviors in signed networks under the single-integrator linear dynamics,where two classes of topologies,namely,the static topology and the dynamic topology,are *** the static signed networks with the adjacency weights as(time-varying)scalars,we investigate the convergence behaviors and the fluctuation behaviors with respect to fixed topologies and switching topologies,respectively,and give some brief introductions on the disagreement behaviors of general time-varying signed ***,several classes of behavior analysis approaches are also *** the dynamic signed networks with the adjacency weights as transfer functions or linear time-invariant systems,we show the specific descriptions and characteristics of them such that the disagreement behaviors can be obtained by resorting to the derived static signed ***,we give their applications to the behavior analysis of static signed networks in the presence of high-order dynamics or communication delays.

关键词： Antagonistic interaction disagreement behavior dynamic topology signed network static topology

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When Does Sora Show:The Beginning of TAO to Imaginative Intelligence and Scenarios engineering

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IEEE/CAA Journal of Automatica Sinica 2024年第4期11卷 809-815页

作者： Fei-Yue Wang Qinghai Miao Lingxi Li Qinghua Ni Xuan Li Juanjuan Li Lili Fan Yonglin Tian Qing-Long Han School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190China Faculty of Innovation Engineering Macao University of Science and TechnologyMacao 999078China Department of Electrical and Computer Engineering Indiana University-Purdue University IndianapolisIndianapolisIN 46202USA Faculty of Innovation Engineering Macao University of Science and TechnologyMacao 999078China Virtual Reality Fundamental Research Laboratory Department of Mathematics and TheoriesPeng Cheng LaboratoryShenzhen 518000China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China School of Information and Electronics Beijing Institute of TechnologyBeijing 100081China School of Science Computing and Engineering TechnologiesSwinburne University of TechnologyMelbourneVIC 3122Australia

DURING our discussion at workshops for writing“What Does ChatGPT Say:The DAO from Algorithmic Intelligence to Linguistic Intelligence”[1],we had expected the next milestone for Artificial Intelligence(AI)would be in the direction of Imaginative Intelligence(II),i.e.,something similar to automatic wordsto-videos generation or intelligent digital movies/theater technology that could be used for conducting new“Artificiofactual Experiments”[2]to replace conventional“Counterfactual Experiments”in scientific research and technical development for both natural and social studies[2]-[6].Now we have OpenAI’s Sora,so soon,but this is not the final,actually far away,and it is just the beginning.

关键词： something Intelligence replace

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Optimal Linear Deception Attacks on Remote State Estimation with Constrained Alarm Rates: A Low-Dimensional Case 63

Optimal Linear Deception Attacks on Remote State Estimation ...

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63rd IEEE Conference on Decision and control, CDC 2024

作者： Shang, Jun Zhang, Hanwen Zhou, Jing Chen, Tongwen Tongji University Shanghai Research Institute for Intelligent Autonomous Systems National Key Laboratory of Autonomous Intelligent Unmanned Systems Frontiers Science Center for Intelligent Autonomous Systems Department of Control Science and Engineering Shanghai200092 China University of Science and Technology Beijing Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education School of Automation and Electrical Engineering Beijing100083 China University of Alberta Department of Electrical and Computer Engineering EdmontonABT6G 1H9 Canada

ISBN: (纸本)9798350316339

This study addresses linear attacks on remote state estimation within the context of a constrained alarm rate. Smart sensors, which are equipped with local Kalman filters, transmit innovations instead of raw measurements through a wireless communication network. This transmission is vulnerable to malicious data interception and manipulation by attackers. The aim of this research is to identify the optimal attack strategy that degrades the system performance while adhering to stealthiness constraints. A notable innovation of this paper is the direct association of the attack's stealthiness with the alarm rate, diverging from traditional approaches that rely on the covariance of the innovation or the Kullback-Leibler divergence, which are conventional metrics that have been extensively explored in previous studies. Our findings reveal that the optimal attack strategy exhibits some structural characteristics in systems of low dimensions. The performance of the proposed attack strategy is demonstrated through numerical examples. © 2024 IEEE.

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Volt-Var control for Utility-scale Solar PV Plants to Replace SVCs 4

Volt-Var Control for Utility-scale Solar PV Plants to Replac...

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4th International Conference on High Voltage engineering and Power systems, ICHVEPS 2023

作者： Shimomukai, Ken Maeda, Haruka Fujita, Goro Shibaura Institute of Technology Functional Control Systems Graduate School of Engineering and Science Tokyo Japan Shibaura Institute of Technology Graduate School of Engineering and Science Department of Electrical Engineering and Computer Science Tokyo Japan Shibaura Institute of Technology Department of Electrical Engineering Tokyo Japan

ISBN: (纸本)9798350318678

One way to increase solar photovoltaic penetration in the grid is management of voltage fluctuations. This is because a photovoltaic plant cannot be interconnected to the grid if it causes voltage violations. Voltage violation is where voltage exceeds the acceptable range. Often, grid operators request photovoltaic plant owners to regulate voltage sufficiently with expensive and space-consuming static Var compensators. Unfortunately, this sometimes makes the project less feasible. This paper argues that there are better ways to regulate voltage. We ran a simulation with a 70 MWp photovoltaic plant as an addition to the grid. Without voltage regulation, voltage violations were found to be significant. This paper found that oversizing the inverter sufficiently would remove all voltage violations without deploying a static Var compensator. This is often a cheaper and space-saving solution for voltage management. This paper argues that economics and spatial efficiency of reactive power compensation devices is key to increasing photovoltaic penetration. © 2023 IEEE.

关键词： Reactive power

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Efficient and Safe Learning-based control of Piecewise Affine systems Using Optimization-Free Safety Filters 63

Efficient and Safe Learning-based Control of Piecewise Affin...

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63rd IEEE Conference on Decision and control, CDC 2024

作者： He, Kanghui Shi, Shengling Van Den Boom, Ton De Schutter, Bart Delft University of Technology Delft Center for Systems and Control Delft Netherlands Massachusetts Institute of Technology Department of Chemical Engineering CambridgeMA United States

ISBN: (纸本)9798350316339

control of piecewise affine (PWA) systems under complex constraints faces challenges in guaranteeing both safety and online computational efficiency. Learning-based methods can rapidly generate control signals with good performance, but rarely provide safety guarantees. A safety filter is a modular method to improve safety for any controller. When applied to PWA systems, a traditional safety filter usually need to solve a mixed-integer convex program, which reduces the computational benefit of learning-based controllers. We propose a novel optimization-free safety filter designed to handle state constraints that involve a combination of polyhedra and ellipsoids. The proposed safety filter only utilizes algebraic and min-max operations to determine safe control inputs. This offers a notable advantage compared with traditional safety filters by allowing for significantly more efficient computation of control signals. The proposed safety filter can be integrated into various function approximators, such as neural networks, enabling safe learning throughout the learning process. Simulation results on a bicycle model with PWA approximation validate the proposed method regarding constraint satisfaction, CPU time, and the preservation of sub-optimality. © 2024 IEEE.

关键词： Integer programming

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Concept of Cognitive Cargo Port Risk Management 8

Concept of Cognitive Cargo Port Risk Management

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8th International Conference on Information, control, and Communication Technologies, ICCT 2024

作者： Bondareva, Irina Khanova, Anna Protalinskiy, Oleg Astrakhan State Technical University Department of Applied Informatics Astrakhan Russia Moscow Power Engineering Institute Department of Automated Control Systems of Thermal Processes Moscow Russia

ISBN: (纸本)9798331517564

Any business processes in an enterprise are associated with the need to periodically assess possible risk situations. Today, assessing risks in order to control them is not enough. It is necessary to continuously, cyclically and on an ongoing basis carry out risk management, which has already become an integral part of the management of the organization. However, the complexity of assessing and analyzing events associated with an unfavorable outcome dictates to organizational systems, which include the subject area considered in the work - a cargo port, the need to develop and use tools that allow for a comprehensive assessment of activities from the point of view of possible risks, including the possibility of cognitive evaluation of each of the results obtained. Risks are considered as situations of failure to meet goals, as well as target standards. The developed balanced scorecard (BS) contains a set of goals and indicators that complement them. In addition to this, through multi-level hybrid and scenario LP risk models of a cargo port, logical and probabilistic connections between goals, indicators and risks arising at all three levels of management are formulated. The basis of the ontological model is knowledge about the above-mentioned connections, the integrated use of which through appropriate queries allows you to choose ways to bypass risk situations under the existing specified conditions. The query results form experimental scenarios with a multi-approach simulation model and allow you to obtain quantitative estimates of indicators, goals and risks. Taking into account all available stochastic characteristics, influencing factors, and also based on information about the results of the experiment, the decision maker formulates the values of the parameters of the original organizational system necessary to adjust in order to prevent the development and aggravation of risk events. © 2024 IEEE.

关键词： Stochastic systems

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Outlier Treatment and Adaptive Signal Conditioning of Wheel Speed Measurement for Antilock Brake System 16

Outlier Treatment and Adaptive Signal Conditioning of Wheel ...

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16th International Conference on COMmunication systems and NETworkS, COMSNETS 2024

作者： Rajesh, R. Gaurkar, Pavel Vijay Vivekanandan, Gunasekaran Sivaram, Sriram Subramanian, Shankar C. Indian Institute of Technology Madras Department of Engineering Design Chennai India Madras Engineering Industries Private Ltd. Air Brake Control Systems Chennai India Madras Engineering Industries Private Ltd. Chennai India

ISBN: (纸本)9798350383119

Wheel speed is an important physical quantity used to implement an Antilock Brake System (ABS) in vehicles. This study uses a Variable Reluctance - Wheel Speed Sensor (VR - WSS) for wheel speed measurement, which is commonly used in Heavy Commercial Road Vehicles (HCRVs). However, wheel speed measurement from in-vehicle experiment results was affected by various time-varying attributes such as noise and outliers. The abovementioned physical measurement considerations are characterized through statistical measures to analyze the consequences on ABS performance. Further, these have been programmed in IPG TruckMaker®, a vehicle dynamics simulation software and experimentally demonstrated using an HCRV Hardware-in-the-Loop (HiL) setup with ABS algorithm. The experimental results showed that the ABS performance is degraded in terms of braking distance and braking efficiency due to these practical considerations. Therefore, this study proposes an adaptive signal conditioning algorithm to address these physical considerations. It consists of an outlier treatment to handle non-synchronized arbitrary data points and an adaptive filter to handle time-varying noise signals in the measurement. The outcomes of the closed-loop HiL evaluation of the ABS algorithm integrated with the signal conditioning algorithm confirmed that the proposed method retained the ABS performance while addressing practical measurement considerations. © 2024 IEEE.

关键词： Antilock brake system Outlier treatment Signal conditioning Wheel speed measurement

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Boosting Explore-Exploit Behavior for Navigating Vehicle by Maintaining Informative Topological Frontier

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on Intelligent Vehicles 2024年 1-11页

作者： Liu, Qiming Cui, Xinru Liu, Zhe Wang, Hesheng Department of Automation Shanghai Jiao Tong University Shanghai China MoE Key Lab of Artificial Intelligence AI Institute Shanghai Jiao Tong University Shanghai China Department of Automation 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 China

Target search in unknown environments places high demands not only on an autonomous vehicle's ability to perceive and interpret target cues, but also on its conscious of collecting these cues by active exploration. While existing navigation methods have successfully built target-driven policies by maintaining memory of explored areas, there has been a lack of focus on facilitating target-aware exploration-the informative frontier information at unexplored yet visible areas is often overlooked. In this paper, we introduce a novel topology-based memory structure, Frontier-enhanced Topological Memory (FTM), and a Hierarchical Topology Encoding and Extraction (HTEE) module, fostering the autonomous vehicle's awareness of both environmental exploration and target approach. Specifically, FTM innovatively incorporates informative ghost nodes on traditional topological map to represent unexplored yet visible regions. We leverage an online-trained implicit scene representation to estimate the positions and generate features of these ghost nodes. The HTEE then employs implicit graph convolutions and attention mechanisms to extract cognitive information from FTM, taking into account the hierarchical memory structure, target cues, and current state. Our design bolsters cognitive navigation decisions. The experiments in the high-fidelity environments, including performance tests, visualizations, and interpretability experiments, validate the effectiveness of our approach in enhancing the vehicle's exploratory behavior. The improved exploration awareness for target cue collection, in turn, enhances the success rate and path efficiency of target search. Furthermore, we demonstrate the adaptability of our algorithm in real-world physical environments. IEEE

关键词： Data mining

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Probabilistic Model-based Motion Accuracy Analysis of RVABI 29

Probabilistic Model-based Motion Accuracy Analysis of RVABI

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29th ISSAT International Conference on Reliability and Quality in Design, RQD 2024

作者： Wang, Yanze Tian, Zihan Yin, Xiaowei Wang, Lei Qian, Wenxue School of Mechanical Engineering and Automation Northeastern University Shenyang110819 China School of Mechanical Shenyang Institute of Engineering Shenyang110136 China Key Laboratory of Vibration and Control of Aero-Propulsion Systems Ministry of Education of China Northeastern University Shenyang110819 China

ISBN: (纸本)9798986576138

In order to study the motion accuracy of the RVABI (Rear Variable Area Bypass Injector) under various error-related influences, the motion analysis model of the RVABI with clearance error is established based on the screw theory. The interaction between different types of errors and calculation methods is discussed. Additionally, in combination with the Monte Carlo sampling method, the influence of each error on the working position of the fan blade is calculated. By sampling a large amount of data, the maximum positioning error of the fan blade for a period of operation is obtained. This paper proposes the concept of "error surface sampling" and discusses the interaction between various errors. It effectively solves the problem of analyzing the correlation between various errors under simultaneous action in mechanism error analysis and improves the accuracy of the analysis. © Conference Proceedings of the 29th ISSAT International Conference on Reliability and Quality in Design, RQD 2024.

关键词： Fans

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Real-time Pricing Mechanism for V2G Using Distributed Bilevel Optimization 63

Real-time Pricing Mechanism for V2G Using Distributed Bileve...

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63rd IEEE Conference on Decision and control, CDC 2024

作者： You, Jiawei Dai, Xinliang Jiang, Yuning Yin, Haoyu Shi, Yuanming Jones, Colin N. ShanghaiTech University School of Information Science and Technology China Epfl Switzerland Karlsruhe Institute of Technology Institute for Automation and Applied Informatics Germany Epfl Automatic Control Laboratory Switzerland Washington University in St. Louis Department of Electrical and Systems Engineering United States

ISBN: (纸本)9798350316339

This paper explores the impact of the burgeoning electric vehicle (EV) presence on distribution grid operations, highlighting the challenges they present to conventional pricing strategies due to their dual role as power consumers and suppliers, coupled with their energy storage capabilities. We propose an advanced real-time pricing model for the electricity market, employing a novel distributed bilevel optimization framework. This framework distinguishes between the distribution system operator (DSO) at the upper level and the EVs at the lower level, each aiming to optimize profit margins. The optimization includes power flow constraints at the upper level to ensure efficient operation within safe system limits, while model predictive control (MPC) is used to optimize lower-level EV responses. Additionally, we provide a rigorous convergence analysis of the proposed bilevel optimization method. Detailed convergence studies and simulation results demonstrate the effectiveness and superiority of the proposed algorithm. © 2024 IEEE.

关键词： Predictive control systems

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