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TOGA-Based Fuzzy Grey Cognitive Map for Spacecraft Debris Avoidance

IEEE Transactions on Fuzzy systems 2025年第6期33卷 1793-1802页

作者： Qin, Chenhui Liu, Yuanshi Wang, Tong Qiu, Jianbin Li, Min Harbin Institute of Technology Research Institute of Intelligent Control and Systems Harbin150080 China Beijing Institute of Control Engineering Beijing100094 China

The optimization of fuzzy grey cognitive map (FGCM) can enhance the decision quality of the system in managing uncertainties and incomplete information. Addressing this issue requires a method that effectively balances the competing demands of the speed and precision in the optimization process. Therefore, a trade-off genetic algorithm (TOGA) is proposed to refine the FGCM optimization process in this paper. Firstly, a modified fitness function with a penalty term is designed to improve the convergence rate, which can drive the FGCM population to obtain the optimal solution during the evolutionary process. Secondly, an adaptive genetic mechanism based on horizontal comparison and longitudinal assessment, is designed to strike a balance between accelerating convergence and avoiding the dilemma of falling into local optima. Finally, in the simulation section, the effectiveness of the proposed method is validated by optimizing FGCM using synthetic datasets and applying to spacecraft debris threat avoidance scenario. © 1993-2012 IEEE.

关键词： Space debris

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Resilient sliding mode control for 2D CPSs under denial-of-service attacks

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Science China(Information Sciences) 2024年第6期67卷 262-278页

作者： Lingling LI Rongni YANG Zhiguang FENG Ligang WU College of Intelligent Systems Science and Engineering Harbin Engineering University School of Control Science and Engineering Shandong University School of Astronautics Harbin Institute of Technology

This study addresses the resilient sliding mode control(SMC) problem for two-dimensional cyber-physical systems(2D CPSs) characterized by the Roesser model under denial-of-service attack(DoSA), which can interfere with signal transmission over the communication network. First, the DoS-A model is established by introducing constraints on the Do S frequency and duration. Then, based on active or silent attack situations, the considered system is described as a switched mode. Furthermore, together with Lyapunov theory, the average dwell time technique is employed to deduce sufficient criteria that assure the existence of the desired sliding mode controller. Finally, verification examples are provided to show the validity of the established SMC scheme.

关键词： two-dimensional systems cyber-physical systems denial-of-service attack resilient sliding mode control

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Internal and external disturbances aware motion planning and control for quadrotors

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IET Cyber-systems and Robotics 2024年第3期6卷 23-30页

作者： Xiaobin Zhou Miao Wang Can Cui Yongchao Wang Chao Xu Fei Gao Institute of Cyber‐Systems and Control College of Control Science and EngineeringZhejiang UniversityHangzhouChina Huzhou Institute Zhejiang UniversityHuzhouChina

Resilient motion planning and control,without prior knowledge of disturbances,are crucial to ensure the safe and robust flight of *** development of a motion planning and control architecture for quadrotors,considering both internal and external disturbances(i.e.,motor damages and suspended payloads),is ***,the authors introduce the use of exponential functions to formulate trajectory *** choice is driven by its ability to predict thrust responses with minimal computational ***,a reachability analysis is incorporated for error dynamics resulting from multiple *** analysis sits at the interface between the planner and controller,contributing to the generation of more robust and safe spatial–temporal ***,the authors employ a cascade controller,with the assistance of internal and external loop observers,to further enhance resilience and compensate the *** authors’benchmark experiments demonstrate the effectiveness of the proposed strategy in enhancing flight safety,particularly when confronted with motor damages and payload disturbances.

关键词： Internal and external disturbances reachability analysis resilient motion planning and tracking

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Networked dynamic systems with higher-order interactions: stability versus complexity

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National Science Review 2024年第9期11卷 291-301页

作者： Ye Wang Aming Li Long Wang Center for Systems and Control College of Engineering Peking University Center for Multi-Agent Research Institute for Artificial IntelligencePeking University

The stability of complex systems is profoundly affected by underlying structures, which are often modeled as networks where nodes indicate system components and edges indicate pairwise interactions between nodes. However, such networks cannot encode the overall complexity of networked systems with higher-order interactions among more than two nodes. Set structures provide a natural description of pairwise and higher-order interactions where nodes are grouped into multiple sets based on their shared traits. Here we derive the stability criteria for networked systems with higher-order interactions by employing set structures. In particular, we provide a simple rule showing that the higher-order interactions play a double-sided role in community stability—networked systems with set structures are stabilized if the expected number of common sets for any two nodes is less than one. Moreover, although previous knowledge suggests that more interactions(i.e. complexity) destabilize networked systems, we report that,with higher-order interactions, networked systems can be stabilized by forming more local sets. Our findings are robust with respect to degree heterogeneous structures, diverse equilibrium states and interaction types.

关键词： networked system set structure higher-order interaction stability criteria

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Cooperative decision-making algorithm with efficient convergence for UCAV formation in beyond-visual-range air combat based on multi-agent reinforcement learning

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Chinese Journal of Aeronautics 2024年第8期37卷 311-328页

作者： Yaoming ZHOU Fan YANG Chaoyue ZHANG Shida LI Yongchao WANG School of Aeronautic Science and Engineering Beihang UniversityBeijing 100191China Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and ControlZhejiang UniversityHangzhou 310027China

Highly intelligent Unmanned Combat Aerial Vehicle(UCAV)formation is expected to bring out strengths in Beyond-Visual-Range(BVR)air *** Multi-Agent Reinforcement Learning(MARL)shows outstanding performance in cooperative decision-making,it is challenging for existing MARL algorithms to quickly converge to an optimal strategy for UCAV formation in BVR air combat where confrontation is complicated and reward is extremely sparse and *** to solve this problem,this paper proposes an Advantage Highlight Multi-Agent Proximal Policy Optimization(AHMAPPO)***,at every step,the AHMAPPO records the degree to which the best formation exceeds the average of formations in parallel environments and carries out additional advantage sampling according to ***,the sampling result is introduced into the updating process of the actor network to improve its optimization ***,the simulation results reveal that compared with some state-of-the-art MARL algorithms,the AHMAPPO can obtain a more excellent strategy utilizing fewer sample episodes in the UCAV formation BVR air combat simulation environment built in this paper,which can reflect the critical features of BVR air *** AHMAPPO can significantly increase the convergence efficiency of the strategy for UCAV formation in BVR air combat,with a maximum increase of 81.5%relative to other algorithms.

关键词： Unmanned combat aerial vehicle(UCAV)formation Decision-making Beyond-visual-range(BVR)air combat Advantage highlight Multi-agent reinforcement learning(MARL)

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Real-time drone detection framework based on advanced texture feature extraction and pattern recognition model using GUI

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Neural Computing and Applications 2025年第5期37卷 3435-3454页

作者： Hussen, Noha Salem, Mofreh Eldesouky, Ali I. Sakr, Noha Elghamrawy, Sally Computers and Control Systems Engineering Department Mansoura University Mansoura Egypt Computer Engineering Department Misr Higher Institute for Engineering and Technology Mansoura Egypt

The increasing prevalence of drones has raised significant concerns regarding their potential for misuse in activities such as smuggling, terrorism, and unauthorized access to restricted airspace. Consequently, the development of robust and efficient drone detection systems has become paramount. Traditional detection methods such as radar and acoustic sensors have limitations in detecting small drones and can be costly to implement. This can lead to lower detection rates and increased security breaches and safety concerns. However, prevailing methodologies often falter in achieving real-time detection with requisite precision and efficacy, particularly within complex operational environments. Motivated by the imperative to surmount these challenges, our research endeavors to introduce a pioneering real-time drone detection framework. Our study encapsulates several seminal advancements. Firstly, we proffer a groundbreaking framework that synergizes advanced integration technique based on texture feature extraction and pattern recognition techniques for real-time drone detection to increase accuracy to detect drones in different conditions such as bad weather and low resolution. Secondly, we introduce an intuitive graphical user interface, enhancing the usability and accessibility of the system in real-time scenario. Lastly, through exhaustive evaluation and comparative analysis, we substantiate the superior performance of our framework in terms of accuracy, precision, and real-time detection capabilities compared to conventional DDS methodologies. Its stability and effectiveness render it a compelling solution for security-focused entities, notably those within air force and military systems. Our experimental results reveal a commendable accuracy rate of 97%, affirming the reliability and precision 98% and recall parameter 98% of our framework in accurately identifying and detecting drones, thus surpassing recent models in the field. © The Author(s), under exclusive

关键词： Graphical user interfaces

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Coalition formation problem: a capability-centric analysis and general model

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Science China(Information Sciences) 2024年第11期67卷 180-193页

作者： Jie CHEN Miao GUO Bin XIN Qing WANG Shengyu LU Yipeng WANG Yulong DING School of Automation Beijing Institute of Technology National Key Lab of Autonomous Intelligent Unmanned Systems Department of Control Science and Engineering Tongji University

Coalition formation(CF) refers to reasonably organizing robots and/or humans to form coalitions that can satisfy mission requirements, attracting more and more attention in many fields such as multirobot collaboration and human-robot collaboration. However, the analysis on CF problems remains *** provide a valuable study reference for researchers interested in CF, this paper proposed a capabilitycentric analysis of the CF problem. The key problem elements of CF are firstly extracted by referencing the concepts of the 5W1H method. That is, objects(who) form coalitions(what) to accomplish missions(why) by aggregating capabilities(how) in a specific environment(where-when). Then, a multi-view analysis of these elements and their correlation in terms of capabilities is proposed through various logic diagrams, structure charts, etc. Finally, to facilitate a deeper understanding of capability-centric CF, a general mathematical model is constructed, demonstrating how the different concepts discussed in this analysis contribute to the overall model.

关键词： coalition formation capability aggregation capability metric mission requirement environmental effect

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Toward the minimum vertex cover of complex networks using distributed potential games

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Science China(Information Sciences) 2023年第1期66卷 244-263页

作者： Jie CHEN Xiang LI Adaptive Networks and Control Lab Department of Electronic Engineering Fudan University Institute of Complex Networks and Intelligent Systems Shanghai Research Institute for Intelligent Autonomous SystemsTongji University

Vertex cover of complex networks is essentially a major combinatorial optimization problem in network science, which has wide application potentials in engineering. To optimally cover the vertices of complex networks, this paper employs a potential game for the vertex cover problem, designs a novel cost function for network vertices, and proves that the solutions to the minimum value of the potential function are the minimum vertex covering(MVC) states of a general complex network. To achieve the optimal(minimum) covering states, we propose a novel distributed time-variant binary log-linear learning algorithm,and prove that the MVC state of a general complex network is attained under the proposed optimization algorithm. Furthermore, we estimate the upper bound of the convergence rate of the proposed algorithm,and show its effectiveness and superiority using numerical examples with representative complex networks and optimization algorithms.

关键词： minimum vertex cover Nash equilibrium convergence rate scale-free network random graph

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Data-driven output regulation control for constrained linear systems

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Science China(Information Sciences) 2025年第3期68卷 338-353页

作者： Chaoyu XIA Yi DONG Chaoli WANG Shengyuan XU Shanghai Research Institute for Intelligent Autonomous Systems Tongji University College of Electronic and Information Engineering Shanghai Research Institute for Intelligent Autonomous SystemsTongji University Department of Control Science and Engineering School of Optical-Electrical and Computer EngineeringUniversity of Shanghai for Science and Technology Department of Automation Nanjing University of Science and Technology

This study introduces a data-driven approach for state and output feedback control addressing the constrained output regulation problem in unknown linear discrete-time systems. Our method ensures effective tracking performance while satisfying the state and input constraints, even when system matrices are not available. We first establish a sufficient condition necessary for the existence of a solution pair to the regulator equation and propose a data-based approach to obtain the feedforward and feedback control gains for state feedback control using linear programming. Furthermore, we design a refined Luenberger observer to accurately estimate the system state, while keeping the estimation error within a predefined set. By combining output regulation theory, we develop an output feedback control strategy. The stability of the closed-loop system is rigorously proved to be asymptotically stable by further leveraging the concept of λ-contractive sets.

关键词： output regulation constrained system data-driven.

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Model-Free Current Predictive control for PMSMs With Ultralocal Model Employing Fixed-Time Observer and Extremum-Seeking Method

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IEEE Transactions on Power Electronics 2025年第8期40卷 10682-10693页

作者： Lin, Xinpo Liu, Jianxing Liu, Zhuang Gao, Yabin Peretti, Luca Wu, Ligang Harbin Institute of Technology Department of Control Science and Engineering Weihai264209 China Harbin Institute of Technology Department of Control Science and Engineering Harbin150001 China KTH Royal Institute of Technology Division of Electric Power and Energy Systems Stockholm10044 Sweden

Conventional model predictive current control of permanent magnet synchronous machines (PMSMs) relies heavily on a precise mathematical model, which may be challenging to obtain in certain cases. To address this issue, this article proposes a model-free predictive current controller for PMSMs. Specifically, the dynamic model of the motor currents is represented using two ultralocal models, which express the derivatives of a controlled output as the sum of an amplified control input and an unknown offset term. All system parameters, nonlinear terms, and unmodeled dynamics are encapsulated into two offset terms. Online estimation of these two offset terms is performed using a second-order fixed-time convergence observer without requiring exact knowledge of the system parameters in advance. In contrast to both the linear extended state observer and the super-twisting observer, the fixed-time observer enhances convergence speed while concurrently sustaining minimal chatting. To get rid of the need for model rated parameters, an extremum-seeking approach is utilized to tune the control gains in the ultralocal model, where the amplitude of the disturbance item in extremum-seeking approach is adaptively attenuated, resulting in effective reduction of the fluctuations of both the control gains and PMSM's currents in steady state. Subsequently, a predictive controller is designed using this ultralocal model. Finally, the effectiveness and advantages of the proposed control scheme are confirmed through experimental results. © 1986-2012 IEEE.

关键词： Permanent magnets

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