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Distributed Secondary Control and Optimal Power Sharing in Microgrids

IEEE/CAA Journal of Automatica Sinica 2015年第3期2卷 304-312页

作者： Gang Chen Ening Feng the Key Laboratory of Dependable Service Computing in Cyber Physical Society of Ministry of Education and the College of Automation Chongqing University

We address the control problem of microgrids and present a fully distributed control system which consists of primary controller, secondary controller, and optimal active power sharing controller. Different from the existing control structure in microgrids, all these controllers are implemented as local controllers at each distributed generator. Thus, the requirement for a central controller is obviated. The performance analysis of the proposed control systems is provided, and the finite-time convergence properties for distributed secondary frequency and voltage controllers are achieved. Moreover, the distributed control system possesses the optimal active power sharing property. In the end, a microgrid test system is investigated to validate the effectiveness of the proposed control strategies. © 2014 Chinese Association of Automation.

关键词： Control system analysis Control systems Distributed parameter control systems Distributed parameter networks Electric power distribution

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Load-redistribution strategy based on time-varying load against cascading failure of complex network

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Chinese Physics B 2015年第7期24卷 371-377页

作者：刘军熊庆宇石欣王楷石为人 School of Automation Chongqing University Key Laboratory of Dependable Service Computing in Cyber Physical Society Ministry of Education School of Software Engineering Chongqing University

Cascading failure can cause great damage to complex networks, so it is of great significance to improve the network robustness against cascading failure. Many previous existing works on load-redistribution strategies require global information, which is not suitable for large scale networks, and some strategies based on local information assume that the load of a node is always its initial load before the network is attacked, and the load of the failure node is redistributed to its neighbors according to their initial load or initial residual capacity. This paper proposes a new load-redistribution strategy based on local information considering an ever-changing load. It redistributes the loads of the failure node to its nearest neighbors according to their current residual capacity, which makes full use of the residual capacity of the network. Experiments are conducted on two typical networks and two real networks, and the experimental results show that the new load-redistribution strategy can reduce the size of cascading failure efficiently.

关键词： load redistribution time-varying load cascading failure complex networks

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ATHENA: An In-vehicle CAN Intrusion Detection Framework Based on physical Characteristics of Vehicle Systems

arXiv

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arXiv 2025年

作者： Wang, Kai Sun, Zhen Wang, Bailing Fan, Qilin Li, Ming Zhang, Hongke School of Computer Science and Technology Harbin Institute of Technology Weihai China Shandong Key Laboratory of Industrial Network Security China School of Big Data and Software Engineering Chongqing University Chongqing China Key Laboratory of Dependable Service Computing in Cyber Physical Society of Ministry of Education Chongqing University Chongqing China Jinan Key Laboratory of Distributed Databases Shandong Inspur Database Technology Co. Ltd Jinan China School of Electronic and Information Engineering Beijing Jiaotong University Beijing China

With the growing interconnection between In-Vehicle Networks (IVNs) and external environments, intelligent vehicles are increasingly vulnerable to sophisticated external network attacks. This paper proposes ATHENA, the first IVN intrusion detection framework that adopts a vehicle-cloud integrated architecture to achieve better security performance for the resource-constrained vehicular environment. Specifically, in the cloud with sufficient resources, ATHENA uses the clustering method of multi-distribution mixture model combined with deep data mining technology to generate the raw Payload Rule Bank of IVN CAN messages, and then improves the rule quality with the help of exploitation on the first-principled physical knowledge of the vehicle system, after which the payload rules are periodically sent to the vehicle terminal. At the vehicle terminal, a simple LSTM component is used to generate the Time Rule Bank representing the long-term time series dependencies and the periodic characteristics of CAN messages, but not for any detection tasks as in traditional usage scenarios, where only the generated time rules are the candidates for further IVN intrusion detection tasks. Based on both the payload and time rules generated from cloud and vehicle terminal, ATHENA can achieve efficient intrusion detection capability by simple rule-base matching operations, rather than using complex black-box reasoning of resource-intensive neural network models, which is in fact only used for rule logic generation phase instead of the actual intrusion detection phase in our framework. Comparative experimental results on the ROAD dataset, which is current the most outstanding real-world in-vehicle CAN dataset covering new instances of sophisticated and stealthy masquerade attacks, demonstrate ATHENA significantly outperforms the state-of-the-art IVN intrusion detection methods in detecting complex attacks. We make the code availab.e at https://***/wangkai-tech23/ATHENA. Copyright

关键词： Network intrusion

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A cooperative on-ramp merging strategy based on the hybrid of centralized and distributed interaction for heterogeneous vehicles

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Journal of Ambient Intelligence and Humanized computing 2023年第3期14卷 2385-2397页

作者： Wang, ShiHui Zhao, Min Sun, DiHua Liu, ZhongCheng Key Laboratory of Dependable Service Computing in the Cyber Physical Society of the Ministry of Education and School of Automation Chongqing University Chongqing China

The on-ramp merging on the freeway which causes reduced traffic efficiency, increased risks of collision, and more fuel consumption is one of the research hotspots. The mixed traffic made up of connected and autonomous vehicles (CAVs) and connected and human-driving vehicles (CHVs) is the trend of the future intelligent traffic. Therefore, to facilitate the on-ramp merging on the freeway in mixed traffic, this paper proposes a hybrid cooperative strategy to the heterogeneous vehicles in a merging zone. As a cyber-physical system, the on-ramp merging on the freeway in mixed traffic was divided into four types and analyzed. In this study, we proposed a synergetic merging framework based on the vehicle-infrastructure cooperative theory for the on-ramp merging to ensure successful merging of mixed traffic. For different types of vehicles in mixed traffic, we designed different control methods, respectively. For CHVs and CAVs, centralized induced control method (CICM) and distributed autonomous control method (DACM) were designed. When designing these two methods, we separately considered two classic and important human factors: the reaction time of drivers of CHVs and the comfort of CAVs’ passengers. Finally, the effectiveness of the proposed strategy and methods was validated through simulations. The proposed hybrid cooperative strategy can derive an optimal trajectory for each vehicle. The control method of CAVs can obtain the optimal trajectory while satisfy the comfort requirements of passengers. By analyzing results of simulations, it can be known that the reaction time of drivers has a certain effect on the state of the CHVs’ merging process. © 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： cyber physical System

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Density waves in a lattice hydrodynamic traffic flow model with the anticipation effect

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Chinese Physics B 2012年第4期21卷 619-624页

作者：赵敏孙棣华田川 College of Automation Chongqing UniversityChongqing 400030China Key Laboratory of Dependable Service Computing in Cyber Physical Society(Chongqing University) Ministry of EducationChongqing 400030China

By introducing the traffic anticipation effect in the real world into the original lattice hydrodynamic model, we present a new anticipation effect lattice hydrodynamic （AELH） model, and obtain the linear stability condition of the model by applying the linear stability theory. Through nonlinear analysis, we derive the Burgers equation and Korteweg-de Vries （KdV） equation, to describe the propagating behaviour of traffic density waves in the stable and the metastable regions, respectively. The good agreement between simulation results and analytical results shows that the stability of traffic flow can be enhanced when the anticipation effect is considered.

关键词： traffic flow lattice hydrodynamic model density waves anticipation effect

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A new coupled map car-following model considering drivers' steady desired speed

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Chinese Physics B 2014年第5期23卷 41-45页

作者：周桐孙棣华李华民刘卫宁 College of Automation Chongqing University Key Laboratory of Dependable Service Computing in Cyber Physical Society of Ministry of Education Chongqing University College of Computer Science Chongqing University

Based on the pioneering work of Konishi et al., in consideration of the influence of drivers＇ steady desired speed ef/ect on the traffic flow, we develop a new coupled map car-following model in the real world. By use of the control theory, the stability condition of our model is derived. The validity of the present theoretical scheme is verified via numerical simulation, confirming the correctness of our theoretical analysis.

关键词： traffic flow traffic congestion coupled map car-following model steady desired speed effect

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DGAN: Flight data anomaly detection based on dual-view graph attention network

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IEEE Sensors Journal 2025年

作者： Yan, Wenlong Li, Xu Zheng, Linjiang Shang, Jiaxing Wu, Lin Liu, Hongtao Li, Xiuyi Qian, Yu Chongqing University College of Computer Science Chongqing400044 China Chongqing University Key Laboratory of Dependable Service Computing in Cyber Physical Society Ministry of Education Chongqing400044 China Zhuhai Xiangyi Aviation Technology Co. Ltd Zhuhai519030 China Shanghai Jiaotong University School of Aeronautics and Astronautics Minhang District Shanghai200240 China Civil Aviation Flight University of China School of Flight Technology Guanghan618307 China

A large number of flight data is collected by various sensors during flight, including altitude, speed, pitch, etc. Flight unsafe events, such as hard landings, can be reflected in flight anomaly data. Thus, flight data anomaly detection is crucial for aviation safety, enabling the identification of deviations from normal operations. However, due to the complexity and high dimensionality of the flight data, existing methods often fail to adequately extract temporal and variable information. As a result, these methods exhibit poor detection performance, especially when the anomaly data is scarce. To address these issues, we propose a novel Dual-view Graph Attention Network (DGAN) model for flight data anomaly detection. Specifically, two parallel Graph Attention (GAT) layers are employed to create embeddings that are rich in temporal correlations and variable dependencies. And TCN-based autoencoder module is proposed for data augmentation on these embeddings to extract two views consistent with the underlying data patterns. Furthermore, DGAN constructs pairs of positive and negative samples both within a single view and between different views. A dual-view contrastive training strategy is proposed to construct contrastive loss, which can learn a good representation of flight sequence and ensure effective anomaly detection even in cases of scarce anomaly data. We conduct experiments on a dataset comprising 44,808 real-world flight samples from the Airbus A321. The results demonstrate that the performance of DGAN exceeds state-of-the-art (SOTA) models. Moreover, we examine the effectiveness of DGAN through further visualizations and case studies. © 2001-2012 IEEE.

关键词： Training aircraft

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Risk Status Identification During the Takeover of Conditionally Automated Vehicles 32

Risk Status Identification During the Takeover of Conditiona...

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第32届中国控制与决策会议

作者： Mao Peng Chen Jin Sun Dihua School of Automation Chongqing University Key Laboratory of Dependable Service Computing in Cyber Physical Society of Ministry of Education

ISBN: (数字)9781728158556

ISBN: (纸本)9781728158556;9781728158563

In order to identify the risk status during the takeover from automated driving to manual driving in dangerous traffic situations,this study investigated their performance during the takeover based on *** experiment invited 38 *** all held a valid driving license.A risk status identification model was proposed based on the information of vehicle status and traffic environment *** to the rate of electrocardiogram(ECG) and the performance of takeover,the risk status was classified into three *** Pearson correlation coefficient algorithm,seven factors were selected as the feature ***,the algorithm of Random Forest(RF) was employed to establish the takeover risk status identification *** results show that the accuracy of RF is 98.8%,increasing 10.4%,17.7% and 7.3% compared with Support Vector Machine(SVM),Classification and Regression Tree(CART) and Back Propagation Neural Network,and each risk level has good prediction ***,the results show that the space headway,longitudinal acceleration and lane departure have a great influence on the risk level,and the space headway has the strongest impact on the degree of danger during the takeover of control in Conditionally Automated Vehicles.

关键词： Automated Driving Experimental Research Takeover Risk Status Identification Driving Simulator

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Image Enhancement Algorithm for Highway Tunnel Based on Imaging Model Estimation 3

Image Enhancement Algorithm for Highway Tunnel Based on Imag...

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2017 IEEE 第3届信息技术与机电一体化工程国际学术会议(ITOEC 2017)

作者： Yongxue Li Min Zhao Dihua Sun College of Automation Chongqing University Key Laboratory of Dependable Service Computing in Cyber Physical Society of Ministry of Education

Highway tunnel environment is dim,with the interaction of multi-color light sources,which forms a light *** a complicated scene makes the image blurred and arouses difficulties in the image enha

ISBN: (纸本)9781509053643;9781509053636

Highway tunnel environment is dim,with the interaction of multi-color light sources,which forms a light *** a complicated scene makes the image blurred and arouses difficulties in the image enha

关键词： Estimation Image reconstruction Information entropy Parameter estimation

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Adaptive Fault-tolerant Control for Uncertain Nonlinear System with Guaranteed Pre-described Performance 29

Adaptive Fault-tolerant Control for Uncertain Nonlinear Syst...

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第29届中国控制与决策会议

作者： Zhiyuan Nie Yongduan Song Liu He Kai Zhao The Key Laboratory of Dependable Service Computing in Cyber Physical Society Ministry of EducationCollege of AutomationChongqing University

ISBN: (纸本)9781509046584

In this paper we present a computationally inexpensive adaptive control method for a class of single-input single-output(SISO) uncertain nonlinear dynamic system with actuator failure,modeling uncertainties and external *** blending system deep-rooted information into backstepping control design and with the help of Nussbaum gains,we develop a robust adaptive control scheme to deal with system uncertainties and actuation failures,which ensures pre-described performance specifications without involving complex online *** theoretical analysis and numerical simulation verify the effectiveness and benefits of the proposed method.

关键词： Adaptive control Fault-tolerant Pre-described performance Backstepping Nussbaum gain Deep-rooted information

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