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Set Stabilization of Large-Scale Stochastic Boolean Networks:A Distributed Control Strategy

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IEEE/CAA Journal of Automatica Sinica 2024年第3期11卷 806-808页

作者： Lin Lin jinde cao Jianquan Lu Leszek Rutkowski the Department of Mechanical Engineering the University of Hong KongHong Kong China the School of Mathematics Southeast UniversityNanjing 210096China IEEE the School of Mathematics and the Frontiers Science Center for Mobile Information Communication and Security Southeast UniversityNanjing 210096China the School of Mathematics the Southeast UniversityNanjing 210096 the School of Electronic Information and Electrical Engineering Chengdu UniversityChengdu 610106China the Systems Research Institute of the Polish Academy of Sciences Warsaw 01-447 the Institute of Computer Science AGH University of Science and TechnologyKraków 30-059 the Information Technology Institute University of Social SciencesŁódź90-113Poland

Dear Editor,This letter deals with the set stabilization of stochastic Boolean control networks(SBCNs)by the pinning control strategy,which is to realize the full control for systems by imposing control inputs on a fr... 详细信息

关键词： Boolean stabilization letter

Distributed generalized Nash equilibrium seeking:event-triggered coding-decoding-based secure communication

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Science China(Information Sciences) 2024年第7期67卷 271-284页

作者： Shaofu YANG Wenying XU Wangli HE jinde cao School of Computer Science and Engineering Southeast University School of Mathematics Southeast University Key Laboratory of Advanced Control and Optimization for Chemical Processes East China University of Science and Technology

In this paper, we consider the distributed generalized Nash equilibrium(GNE) seeking problem in strongly monotone games. The transmission among players is implemented through a digital communication network with limited bandwidth. For improving communication efficiency or/and security, an event-triggered coding-decoding-based communication is first proposed, where the data(decision variable) are first mapped to a series of finite-level codewords and, only when an event condition is satisfied, then sent to the neighboring agents. Moreover, a distributed communication-efficient GNE seeking algorithm is constructed accordingly,and the overrelaxation scheme is further taken into consideration. Through primal-dual analysis, the proposed algorithm is proven to converge to a variational GNE with fixed step-sizes by recasting it as an inexact forward-backward iteration. Finally, numerical simulations illustrate the benefit of the proposed algorithms in terms of saving communication resources.

关键词： noncooperative games event-triggered communication coding-decoding quantization

Detection and Defense Method Against False Data Injection Attacks for Distributed Load Frequency Control System in Microgrid

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Journal of Modern Power Systems and Clean Energy 2024年第3期12卷 913-924页

作者： Zhixun Zhang Jianqiang Hu Jianquan Lu Jie Yu jinde cao Ardak Kashkynbayev the School of Cyber Science and Engineering Southeast University the School of Mathematics Southeast University School of Electronic Information and Electrical Engineering Chengdu University School of Electrical Engineering Southeast University the Yonsei Frontier Laboratory Yonsei University the Department of Mathematics Nazarbayev University

In the realm of microgrid(MG), the distributed load frequency control(LFC) system has proven to be highly susceptible to the negative effects of false data injection attacks(FDIAs). Considering the significant responsibility of the distributed LFC system for maintaining frequency stability within the MG, this paper proposes a detection and defense method against unobservable FDIAs in the distributed LFC system. Firstly, the method integrates a bi-directional long short-term memory(Bi LSTM) neural network and an improved whale optimization algorithm(IWOA) into the LFC controller to detect and counteract FDIAs. Secondly, to enable the Bi LSTM neural network to proficiently detect multiple types of FDIAs with utmost precision, the model employs a historical MG dataset comprising the frequency and power variances. Finally, the IWOA is utilized to optimize the proportional-integral-derivative(PID) controller parameters to counteract the negative impacts of FDIAs. The proposed detection and defense method is validated by building the distributed LFC system in Simulink.

关键词： Power system stability Frequency control Renewable energy sources Neural networks Power generation Stability criteria Microgrids

Fixed-Time Gradient Flows for Solving Constrained Optimization:A Unified Approach

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IEEE/CAA Journal of Automatica Sinica 2024年第8期 1849-1864页

作者： Xinli Shi Xiangping Xu Guanghui Wen jinde cao IEEE the School of Cyber Science and Engineering Southeast University the School of Mathematics Southeast University

The accelerated method in solving optimization problems has always been an absorbing topic. Based on the fixedtime(FxT) stability of nonlinear dynamical systems, we provide a unified approach for designing FxT gradient flows(FxTGFs).First, a general class of nonlinear functions in designing FxTGFs is provided. A unified method for designing first-order FxTGFs is shown under Polyak-?jasiewicz inequality assumption, a weaker condition than strong convexity. When there exist both bounded and vanishing disturbances in the gradient flow, a specific class of nonsmooth robust FxTGFs with disturbance rejection is presented. Under the strict convexity assumption, Newton-based FxTGFs is given and further extended to solve time-varying optimization. Besides, the proposed FxTGFs are further used for solving equation-constrained optimization. Moreover, an FxT proximal gradient flow with a wide range of parameters is provided for solving nonsmooth composite optimization. To show the effectiveness of various FxTGFs, the static regret analyses for several typical FxTGFs are also provided in detail. Finally, the proposed FxTGFs are applied to solve two network problems, i.e., the network consensus problem and solving a system linear equations, respectively, from the perspective of optimization. Particularly, by choosing component-wisely sign-preserving functions,these problems can be solved in a distributed way, which extends the existing results. The accelerated convergence and robustness of the proposed FxTGFs are validated in several numerical examples stemming from practical applications.

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Event-triggered impulsive synchronization of heterogeneous neural networks

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Science China(Information Sciences) 2024年第2期67卷 331-332页

作者： Zhengxin WANG Chongfang JIN Wangli HE Min XIAO Guo-Ping JIANG jinde cao College of Science Nanjing University of Posts and Telecommunications Jiangsu Engineering Lab for IOT Intelligent Robots (IOTRobot) Nanjing University of Posts and Telecommunications Key Laboratory of Smart Manufacturing in Energy Chemical Process Ministry of EducationEast China University of Science and Technology School of Automation Nanjing University of Posts and Telecommunications School of Mathematics Southeast University Yonsei Frontier Lab Yonsei University

Synchronization is one of the most important dynamics in neural networks. Several scholars have studied the quasi-synchronization of heterogeneous neural networks [1],wherein external controllers play a significant role. Impulsive control, a kind of energy-saving control, is activated instantaneously only at specific discrete moments.

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Systems science in the new era: intelligent systems and big data

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Science China(Information Sciences) 2024年第3期67卷 308-310页

作者： Wenwu YU Duxin CHEN Hongzhe LIU He WANG jinde cao Zengru DI Xiaojun DUAN Bin JIA Xiaodong DING Yiguang HONG School of Mathematics Southeast University Purple Mountain Laboratories International Academic Center of Complex Systems Beijing Normal University College of Science National University of Defense Technology School of Systems Science Beijing Jiaotong University Business School University of Shanghai for Science and Technology Department of Control Science and Engineering Tongji University

This study introduces the emergence, research challenges,and future development of intelligent systems and big data(ISBD) and discusses the significance of ISBD to systems science. To this end, an overview of systems science is first presented, followed by the conclusion that the development of artificial intelligence(AI) has promoted the derivation and development of intelligent systems(ISs).

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Exponential Convergence of Primal-Dual Dynamical System for Linear Constrained Optimization

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IEEE/CAA Journal of Automatica Sinica 2022年第4期9卷 745-748页

作者： Luyao Guo Xinli Shi jinde cao the School of Mathematics Southeast University IEEE School of Cyber Science&Engineering Southeast University School of Mathematics Frontiers Science Center for Mobile Information Communication and SecuritySoutheast University Purple Mountain Laboratories Yonsei Frontier Laboratory Yonsei University

Dear editor,Primal-dual dynamics(PDD)and its variants are prominent first-order continuous-time algorithms to determine the primal and dual solutions of a constrained optimization problem(COP).Due to the simple structure,they have received widespread attention in various fields,such as distributed optimization[1],power systems[2],and wireless communication[3].In view of their wide applications,there are numerous theoretic studies on the convergence properties of PDD and its variants,including the exponential stability analysis[4]-[9].

关键词： Primal optimization Convergence

SSL-WAEIE:Self-Supervised Learning With Weighted Auto-Encoding and Information Exchange for Infrared and Visible Image Fusion

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IEEE/CAA Journal of Automatica Sinica 2022年第9期9卷 1694-1697页

作者： Gucheng Zhang Rencan Nie jinde cao the School of Information Science and Engineering Yunnan UniversityKunming 650500China the School of Information Science and Engineering Yunnan UniversityKunming 650500 Yunnan Key Laboratory of Intelligent Systems and Computing Kunming 650500and also with the School of AutomationSoutheast UniversityNanjing 210096China the School of Mathematics Southeast UniversityNanjing 210096China Yonsei Frontier Laboratory Yonsei UniversitySeoul 03722South Korea

Dear editor,Infrared and visible image fusion(IVIF)technologies are to extract complementary information from source images and generate a single fused result[1],which is widely applied in various high-level visual ta... 详细信息

关键词： editor SSL Image Exchange

Complex network approach for the evaluation of asphalt pavement design and construction: a longitudinal study

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Science China(Information Sciences) 2022年第7期65卷 210-224页

作者： Hanjie LIU jinde cao Wei HUANG Xinli SHI Xudong WANG School of Mathematics Southeast University Jiangsu Provincial Key Laboratory of Networked Collective Intelligence Southeast University Research Institute of Highway Ministry of Transport Intelligent Transportation System Research Center Southeast University School of Cyber Science and Engineering Southeast University

The assessment of asphalt pavement structures with diversified designs and constructions has been a critical challenge due to the practical limitations in testing and methodology. Here, we propose a complex network approach to the evaluation of longitudinal asphalt pavement performances in the Research Institute of Highway Ministry of Transport track(RIOHTrack). We add to the growing field in which network approaches are employed and indicate the profound application in understanding pavement structures.Specifically, similar and disparate pavement performances are revealed regardless of their predefined design and construction categories. Evidence shows that short-term pavement performance depends on the strength of the subbase structure, whereas long-term performance relies on the thickness of the asphalt layer. In addition, our results indicate that recycling materials could be an important substitute for reducing the thickness of asphalt concrete and maintaining a healthy service life.

关键词： complex network Complex network asphalt pavement structure evaluation longitudinal RIOHTrack