This paper studies cooperative robust parallel operation of multiple actuators over an undirected communication graph.The plant is modeled as an uncertain linear system,and the actuators are linear and identical.Based...This paper studies cooperative robust parallel operation of multiple actuators over an undirected communication graph.The plant is modeled as an uncertain linear system,and the actuators are linear and identical.Based on the internal model principle,a distributed dynamic output feedback control law is proposed to achieve both robust output regulation of the closed-loop system and plant input sharing among the actuators.A practical example of five motors cooperatively driving an uncertain shaft under an external load torque is presented to show the effectiveness of the proposed control law.展开更多
This paper addresses the three-dimensional(3-D)approach angle constrained cooperative guidance problem for speed-varying missiles against maneuvering targets.First,the guidance problem is formulated in a relative refe...This paper addresses the three-dimensional(3-D)approach angle constrained cooperative guidance problem for speed-varying missiles against maneuvering targets.First,the guidance problem is formulated in a relative reference frame and a virtual control input is selected.Then,the cooperative guidance law is designed on the basis of a prediction-correction framework.The time-to-go under the baseline command is estimated by an efficient prediction method with a realistic aerodynamic model and a biased command is developed by utilizing the time-to-go predictions for synchronizing different missiles'impact times.The design of the biased command is decoupled into the individual design of its direction and magnitude.It is proved that the designed cooperative guidance law can make the time-to-go consensus error converge to zero before interception.Finally,the designed guidance law is validated through a series of numerical simulations.展开更多
Cooperative multi-UAV search requires jointly optimizing wide-area coverage,rapid target discovery,and endurance under sensing and motion constraints.Resolving this coupling enables scalable coordination with high dat...Cooperative multi-UAV search requires jointly optimizing wide-area coverage,rapid target discovery,and endurance under sensing and motion constraints.Resolving this coupling enables scalable coordination with high data efficiency and mission reliability.We formulate this problem as a discounted Markov decision process on an occupancy grid with a cellwise Bayesian belief update,yielding a Markov state that couples agent poses with a probabilistic target field.On this belief–MDP we introduce a segment-conditioned latent-intent framework,in which a discrete intent head selects a latent skill every K steps and an intra-segment GRU policy generates per-step control conditioned on the fixed intent;both components are trained end-to-end with proximal updates under a centralized critic.On the 50×50 grid,coverage and discovery convergence times are reduced by up to 48%and 40%relative to a flat actor-critic benchmark,and the aggregated convergence metric improves by about 12%compared with a stateof-the-art hierarchical method.Qualitative analyses further reveal stable spatial sectorization,low path overlap,and fuel-aware patrolling,indicating that segment-conditioned latent intents provide an effective and scalable mechanism for coordinated multi-UAV search.展开更多
NiFe layered double hydroxide(NiFe LDH)has emerged as a promising catalyst for the oxygen evolution reaction(OER);however,its hydrogen evolution reaction(HER)activity remains suboptimal due to unfavorable electronic s...NiFe layered double hydroxide(NiFe LDH)has emerged as a promising catalyst for the oxygen evolution reaction(OER);however,its hydrogen evolution reaction(HER)activity remains suboptimal due to unfavorable electronic structures,particularly the d-electron density of metal sites,which impede water dissociation and lead to poor hydrogen adsorption/desorption capabilities.Herein,we introduce an efficient cooperative d-electron density regulation(CDDR)engineering to comprehensively optimize the delectron density of NiFe LDH by grafting MoO_(x) -modified NiFe LDH nanosheets onto porous nickel particles(PNPs).The PNPs facilitate d-electron density modulation along the edges of the nanosheets,while the MoO_(x) species enable d-electron density modulation across the plane of the nanosheets,thus cooperatively constructing enriched d-electron density in NiFe LDH.Theoretical studies validate the CDDR process and reveal that the enriched d-electron density accelerates water dissociation and optimizes the hydrogen adsorption behavior of NiFe LDH.As a result,the engineered catalyst exhibits significantly improved HER activity,achieving an ultra-low overpotential of 38 mV at 10 mA cm^(-2)in 1 M KOH.Additionally,the CDDR-optimized catalyst also exhibits good OER performance,demonstrating excellent bifunctional performance for overall water splitting in both alkaline freshwater and seawater electrolytes.This work presents a novel CDDR strategy for engineering NiFe LDH into efficient HER catalysts without compromising its OER activity,potentially paving the way for the development of active and robust electrocatalysts for sustainable energy applications.展开更多
In recent years,unmanned aerial vehicles(UAVs)cooperative path planning is attracting more and more research attention.For the multi-UAV cooperative path planning problem,the path planning problem in three-dimensional...In recent years,unmanned aerial vehicles(UAVs)cooperative path planning is attracting more and more research attention.For the multi-UAV cooperative path planning problem,the path planning problem in three-dimensional(3D)environment is transformed into an optimization problem by introducing the fitness function and constraints such as minimizing path length,maintaining a low and stable flight altitude,and avoiding threat zones.A multi-strategy hybrid grey wolf optimization(MSHGWO)algorithm is proposed to address this problem.Firstly,a chaotic Cubic mapping is introduced to initialize the grey wolf positions to make its initial position distribution more uniform.Secondly,an adaptive adjustment weight factor is designed,which can adjust the movement weight based on the rate of fitness value decrease within a unit Euclidean distance,thereby improving the quality of the population.Finally,an elite opposition-based learning strategy is introduced to improve the population diversity so that the population jumps out of the local optimum.Simulation results indicate that the MSHGWO is capable of generating constraint-compliant paths for each UAV in complex 3D environments.Furthermore,the MSHGWO outperforms other algorithms in terms of convergence speed and solution quality.Meanwhile,flight experiments were conducted to validate the path planning capability of MSHGWO in real-world obstacle environments,further demonstrating the feasibility of the proposed multi-UAV cooperative path planning approach.展开更多
Owing to their global search capabilities and gradient-free operation,metaheuristic algorithms are widely applied to a wide range of optimization problems.However,their computational demands become prohibitive when ta...Owing to their global search capabilities and gradient-free operation,metaheuristic algorithms are widely applied to a wide range of optimization problems.However,their computational demands become prohibitive when tackling high-dimensional optimization challenges.To effectively address these challenges,this study introduces cooperative metaheuristics integrating dynamic dimension reduction(DR).Building upon particle swarm optimization(PSO)and differential evolution(DE),the proposed cooperative methods C-PSO and C-DE are developed.In the proposed methods,the modified principal components analysis(PCA)is utilized to reduce the dimension of design variables,thereby decreasing computational costs.The dynamic DR strategy implements periodic execution of modified PCA after a fixed number of iterations,resulting in the important dimensions being dynamically identified.Compared with the static one,the dynamic DR strategy can achieve precise identification of important dimensions,thereby enabling accelerated convergence toward optimal solutions.Furthermore,the influence of cumulative contribution rate thresholds on optimization problems with different dimensions is investigated.Metaheuristic algorithms(PSO,DE)and cooperative metaheuristics(C-PSO,C-DE)are examined by 15 benchmark functions and two engineering design problems(speed reducer and composite pressure vessel).Comparative results demonstrate that the cooperative methods achieve significantly superior performance compared to standard methods in both solution accuracy and computational efficiency.Compared to standard metaheuristic algorithms,cooperative metaheuristics achieve a reduction in computational cost of at least 40%.The cooperative metaheuristics can be effectively used to tackle both high-dimensional unconstrained and constrained optimization problems.展开更多
Robust cooperative unmanned aerial vehicle(UAV)formation in complex 3D environments is hampered by reward sparsity and inefficient collaboration.To address this,we propose context-aware relational agent learning(CORAL...Robust cooperative unmanned aerial vehicle(UAV)formation in complex 3D environments is hampered by reward sparsity and inefficient collaboration.To address this,we propose context-aware relational agent learning(CORAL),a novel multi-agent deep reinforcement learning framework.CORAL synergistically integrates two modules:(1)a novelty-based intrinsic reward module to drive efficient exploration and(2)an explicit relational learning module that allows agents to predict peer intentions and enhance coordination.Built on a multi-agent Actor-Critic architecture,CORAL enables agents to balance self-interest with group objectives.Comprehensive evaluations in a high-fidelity simulation show that our method significantly outperforms state-of-theart baselines like multi-agent deep deterministic policy gradient(MADDPG)and monotonic value function factorisation for deep multi-agent reinforcement learning(QMIX)in path planning efficiency,collision avoidance,and scalability.展开更多
To solve the problem of in-flight actuator faults and parameter uncertainties for multiple Unmanned Aerial Vehicles(UAVs),and reduce the communication and computational resource consumption of multiple UAVs,a Fraction...To solve the problem of in-flight actuator faults and parameter uncertainties for multiple Unmanned Aerial Vehicles(UAVs),and reduce the communication and computational resource consumption of multiple UAVs,a Fraction-Order(FO)sliding-mode Fault-Tolerant Cooperative Control(FTCC)strategy is proposed for multiple UAVs based on Event-Triggered Communication Mechanism(ET-COM-M)and Event-Triggered Control Mechanism(ET-CON-M).First,by considering the limited communication bandwidth of multiple UAVs in formation,an ET-COM-M is designed to significantly reduce communication times.Then,a distributed observer is skillfully constructed to estimate the reference signals for follower UAVs.Moreover,the adaptive strategy is incorporated into the Radial Basis Function Neural Network(RBFNN)to learn the lumped unknown terms for handling bias actuator faults and parameter uncertainties.Besides,the Nussbaum method is used to deal with the loss-of-effectiveness faults.To further achieve the refined control performance against faults,FO calculus is artfully integrated into the sliding-mode control protocol with ET-CON-M.Finally,Zeno behavior is excluded by rigorous theoretical analysis and Lyapunov stability is proved to show the effectiveness of the designed FTCC strategy.Simulation results show that the designed FTCC strategy with Event-Triggered Mechanism(ETM)can guarantee the safety of multiple UAVs and simultaneously reduce the communication and control frequencies,making the developed control scheme applicable in engineering.展开更多
In the lush heart of Uganda’s Busoga sub-region,Isaac Imaka is charting a new course for rural development.After seven years in national media,he left the newsroom and stepped into the soil.The former reporter with t...In the lush heart of Uganda’s Busoga sub-region,Isaac Imaka is charting a new course for rural development.After seven years in national media,he left the newsroom and stepped into the soil.The former reporter with the Daily Monitor was driven by the belief that communities like his in Jinja North deserved more than chronic poverty and hand-to-mouth survival.展开更多
With the advancement of surgical techniques and enhanced management of early gastric cancer(EGC),minimally invasive function-preserving surgical approaches have emerged as a common goal for patients and clinicians.Lap...With the advancement of surgical techniques and enhanced management of early gastric cancer(EGC),minimally invasive function-preserving surgical approaches have emerged as a common goal for patients and clinicians.Laparoscopic-endoscopic cooperative surgery combined with sentinel lymph node navigation surgery(LECSSNNS)has drawn increasing interest because of its dual benefits of minimal invasiveness and organ function preservation.However,robust evidence-based support for guiding clinical implementation remains limited.To address this gap,we systematically evaluated available studies on the clinical application of LECS-SNNS in EGC and integrated expert insights to formulate 20 recommendations.These included preoperative assessment,surgical techniques,intraoperative endoscopic procedures,pathological evaluation,postoperative care,and follow-up.This consensus aimed to provide comprehensive guidance for the standardized application of LECS-SNNS,thereby advancing precise,minimally invasive,and function-preserving treatment for EGC.展开更多
As we enter the year 2026,the international system continues to receive shocks from Donald Trump,arguably the 21st century’s most disruptive US leader.His return to the White House in 2025 coincided with the 80th ann...As we enter the year 2026,the international system continues to receive shocks from Donald Trump,arguably the 21st century’s most disruptive US leader.His return to the White House in 2025 coincided with the 80th anniversary of the defeat of fascism and the establishment of the United Nations,the multilateral platform that carried the world’s hope for peace,restraint and collective security.The coincidence was unsettling.A world order designed to limit power now confronts a moment in which power is exercised openly,transactionally and unapologetically.展开更多
This study constructs a reflective feedback model based on a pedagogical agent(PA)and explores its impact on students’problem-solving ability and cognitive load.A quasi-experimental design was used in the study,with ...This study constructs a reflective feedback model based on a pedagogical agent(PA)and explores its impact on students’problem-solving ability and cognitive load.A quasi-experimental design was used in the study,with 84 students from a middle school selected as the research subjects(44 in the experimental group and 40 in the control group).The experimental group used the reflective feedback model,while the control group used the factual feedback model.The results show that,compared with factual feedback,the reflective feedback model based on the pedagogical agent significantly improves students’problem-solving ability,especially at the action and thinking levels.In addition,this model effectively reduces students’cognitive load,especially in terms of internal and external load.展开更多
Cooperative guidance is a method for achieving combat objectives through information sharing and cooperative effects,and has emerged as a significant research area in the fields of missile guidance and systematic warf...Cooperative guidance is a method for achieving combat objectives through information sharing and cooperative effects,and has emerged as a significant research area in the fields of missile guidance and systematic warfare.This study presents a systematic review and analysis of current research on cooperative guidance.First,a bibliometric analysis is conducted on 513 articles using the Scopus database and CiteSpace software to assess keyword clustering,keyword cooccurrence,and keyword burst,and to later visualize the results.Second,fundamental theories of cooperative guidance,including relative motion modeling methods,algebraic graph theory,and multi-agent consensus theory,are summarized.Subsequently,an overview of current cooperative laws and corresponding analysis methods is provided,with categorization based on the cooperative structure and convergence performance.Finally,we summarize current research developments based on five perspectives and propose a developmental framework based on five layers(cyber,physical,decision,information,and system),discussing potential future advancements in cooperative terminal guidance.This framework emphasizes five key areas of research:networked,heterogeneous,integrated,intelligent,and group cooperations,with the goal of offering trends and insights for futurework.展开更多
To address the problem of multi-missile cooperative interception against maneuvering targets at a prespecified impact time and desired Line-of-Sight(LOS)angles in ThreeDimensional(3D)space,this paper proposes a 3D lea...To address the problem of multi-missile cooperative interception against maneuvering targets at a prespecified impact time and desired Line-of-Sight(LOS)angles in ThreeDimensional(3D)space,this paper proposes a 3D leader-following cooperative interception guidance law.First,in the LOS direction of the leader,an impact time-controlled guidance law is derived based on the fixed-time stability theory,which enables the leader to complete the interception task at a prespecified impact time.Next,in the LOS direction of the followers,by introducing a time consensus tracking error function,a fixed-time consensus tracking guidance law is investigated to guarantee the consensus tracking convergence of the time-to-go.Then,in the direction normal to the LOS,by combining the designed global integral sliding mode surface and the second-order Sliding Mode Control(SMC)theory,an innovative 3D LOS-angle-constrained interception guidance law is developed,which eliminates the reaching phase in the traditional sliding mode guidance laws and effectively saves energy consumption.Moreover,it effectively suppresses the chattering phenomenon while avoiding the singularity issue,and compensates for unknown interference caused by target maneuvering online,making it convenient for practical engineering applications.Finally,theoretical proof analysis and multiple sets of numerical simulation results verify the effectiveness,superiority,and robustness of the investigated guidance law.展开更多
A centralized-distributed scheduling strategy for distribution networks based on multi-temporal and hierarchical cooperative game is proposed to address the issues of difficult operation control and energy optimizatio...A centralized-distributed scheduling strategy for distribution networks based on multi-temporal and hierarchical cooperative game is proposed to address the issues of difficult operation control and energy optimization interaction in distribution network transformer areas,as well as the problem of significant photovoltaic curtailment due to the inability to consume photovoltaic power locally.A scheduling architecture combiningmulti-temporal scales with a three-level decision-making hierarchy is established:the overall approach adopts a centralized-distributed method,analyzing the operational characteristics and interaction relationships of the distribution network center layer,cluster layer,and transformer area layer,providing a“spatial foundation”for subsequent optimization.The optimization process is divided into two stages on the temporal scale:in the first stage,based on forecasted electricity load and demand response characteristics,time-of-use electricity prices are utilized to formulate day-ahead optimization strategies;in the second stage,based on the charging and discharging characteristics of energy storage vehicles and multi-agent cooperative game relationships,rolling electricity prices and optimal interactive energy solutions are determined among clusters and transformer areas using the Nash bargaining theory.Finally,a distributed optimization algorithm using the bisection method is employed to solve the constructed model.Simulation results demonstrate that the proposed optimization strategy can facilitate photovoltaic consumption in the distribution network and enhance grid economy.展开更多
Wireless communication-enabled Cooperative Adaptive Cruise Control(CACC)is expected to improve the safety and traffic capacity of vehicle platoons.Existing CACC considers a conventional communication delay with fixed ...Wireless communication-enabled Cooperative Adaptive Cruise Control(CACC)is expected to improve the safety and traffic capacity of vehicle platoons.Existing CACC considers a conventional communication delay with fixed Vehicular Communication Network(VCN)topologies.However,when the network is under attack,the communication delay may be much higher,and the stability of the system may not be guaranteed.This paper proposes a novel communication Delay Aware CACC with Dynamic Network Topologies(DADNT).The main idea is that for various communication delays,in order to maximize the traffic capacity while guaranteeing stability and minimizing the following error,the CACC should dynamically adjust the VCN network topology to achieve the minimum inter-vehicle spacing.To this end,a multi-objective optimization problem is formulated,and a 3-step Divide-And-Conquer sub-optimal solution(3DAC)is proposed.Simulation results show that with 3DAC,the proposed DADNT with CACC can reduce the inter-vehicle spacing by 5%,10%,and 14%,respectively,compared with the traditional CACC with fixed one-vehicle,two-vehicle,and three-vehicle look-ahead network topologies,thereby improving the traffic efficiency.展开更多
Purpose–This study aims to propose a cooperative adhesion control method for trains with multiple motors electric locomotives.The method is intended to optimize the output torque of each motor,maximize the utilizatio...Purpose–This study aims to propose a cooperative adhesion control method for trains with multiple motors electric locomotives.The method is intended to optimize the output torque of each motor,maximize the utilization of train adhesion within the total torque command,reduce the train skidding/sliding phenomenon and achieve optimal adhesion utilization for each axle,thus realizing the optimal allocation of the multi-motor electric locomotives.Design/methodology/approach–In this study,a model predictive control(MPC)-based cooperative maximum adhesion tracking control method for multi-motor electric locomotives is presented.Firstly,train traction system with multiple motors is constructed in accordance with Newton’s second law.These equations include the train dynamics equations,the axle dynamics equations,and the wheel-rail adhesion coefficient equations.Then,a new MPC-based multi-axle adhesion co-optimization method is put forward.This method calculates the optimal output torque through real-time iteration based on the known reference slip speed to achieve multi-axle co-optimization under different circumstances.Findings–This paper presents a MPC system designed for the cooperative control of multi-axle adhesion.The results indicate that the proposed control system is able to optimize the adhesion of multiple axles under numerous different conditions and achieve the optimal power distribution based on the reduction of train skidding/sliding.Originality/value–This study presents a novel cooperative adhesion tracking control scheme.It is designed for multi-motor electric locomotives,which has rarely been studied before.And simulations are carried out in different conditions,including variable surfaces and motor failing.展开更多
基金Supported by the Shenzhen Key Laboratory of Control Theory and Intelligent Systems (ZDSYS20220330161800001)the National Natural Science Foundation of China (62303207)the Guangdong Basic and Applied Basic Research Foundation (2024A1515010725)。
文摘This paper studies cooperative robust parallel operation of multiple actuators over an undirected communication graph.The plant is modeled as an uncertain linear system,and the actuators are linear and identical.Based on the internal model principle,a distributed dynamic output feedback control law is proposed to achieve both robust output regulation of the closed-loop system and plant input sharing among the actuators.A practical example of five motors cooperatively driving an uncertain shaft under an external load torque is presented to show the effectiveness of the proposed control law.
基金supported by Key R&D Program(Soft Science Project)of Shandong Province,China(No.2020CXGC011502)National Natural Science Foundation of China(Nos.62273043 and 62103049).
文摘This paper addresses the three-dimensional(3-D)approach angle constrained cooperative guidance problem for speed-varying missiles against maneuvering targets.First,the guidance problem is formulated in a relative reference frame and a virtual control input is selected.Then,the cooperative guidance law is designed on the basis of a prediction-correction framework.The time-to-go under the baseline command is estimated by an efficient prediction method with a realistic aerodynamic model and a biased command is developed by utilizing the time-to-go predictions for synchronizing different missiles'impact times.The design of the biased command is decoupled into the individual design of its direction and magnitude.It is proved that the designed cooperative guidance law can make the time-to-go consensus error converge to zero before interception.Finally,the designed guidance law is validated through a series of numerical simulations.
文摘Cooperative multi-UAV search requires jointly optimizing wide-area coverage,rapid target discovery,and endurance under sensing and motion constraints.Resolving this coupling enables scalable coordination with high data efficiency and mission reliability.We formulate this problem as a discounted Markov decision process on an occupancy grid with a cellwise Bayesian belief update,yielding a Markov state that couples agent poses with a probabilistic target field.On this belief–MDP we introduce a segment-conditioned latent-intent framework,in which a discrete intent head selects a latent skill every K steps and an intra-segment GRU policy generates per-step control conditioned on the fixed intent;both components are trained end-to-end with proximal updates under a centralized critic.On the 50×50 grid,coverage and discovery convergence times are reduced by up to 48%and 40%relative to a flat actor-critic benchmark,and the aggregated convergence metric improves by about 12%compared with a stateof-the-art hierarchical method.Qualitative analyses further reveal stable spatial sectorization,low path overlap,and fuel-aware patrolling,indicating that segment-conditioned latent intents provide an effective and scalable mechanism for coordinated multi-UAV search.
基金financially supported from the National Key Research and Development Program of China(2022YFB3803600)the National Natural Science Foundation of China(52301272,22309168,12564025,and 52472205)+7 种基金the Fundamental Research Funds for the Central Universities(CCNU25ZH006)the National College Student Innovation and Entrepreneurship Training Project(202510513082)the Research Program of HBNU(2025X082 and2025Y145)the Foundation of Hubei Key Laboratory of Photoelectric Materials and Devices(PMD202404)the General Program of Open Project of the State Key Laboratory of Precision Welding and Joining of Materials Structures(MSWJ-25M-18)the Key Research Project of Hubei Provincial Department of Education(No.D20252503)the Key Project of Hubei Provincial Natural Science Foundation of China(2025AFD002)the Foundation of National Laboratory of Solid State Microstructures(M37087)。
文摘NiFe layered double hydroxide(NiFe LDH)has emerged as a promising catalyst for the oxygen evolution reaction(OER);however,its hydrogen evolution reaction(HER)activity remains suboptimal due to unfavorable electronic structures,particularly the d-electron density of metal sites,which impede water dissociation and lead to poor hydrogen adsorption/desorption capabilities.Herein,we introduce an efficient cooperative d-electron density regulation(CDDR)engineering to comprehensively optimize the delectron density of NiFe LDH by grafting MoO_(x) -modified NiFe LDH nanosheets onto porous nickel particles(PNPs).The PNPs facilitate d-electron density modulation along the edges of the nanosheets,while the MoO_(x) species enable d-electron density modulation across the plane of the nanosheets,thus cooperatively constructing enriched d-electron density in NiFe LDH.Theoretical studies validate the CDDR process and reveal that the enriched d-electron density accelerates water dissociation and optimizes the hydrogen adsorption behavior of NiFe LDH.As a result,the engineered catalyst exhibits significantly improved HER activity,achieving an ultra-low overpotential of 38 mV at 10 mA cm^(-2)in 1 M KOH.Additionally,the CDDR-optimized catalyst also exhibits good OER performance,demonstrating excellent bifunctional performance for overall water splitting in both alkaline freshwater and seawater electrolytes.This work presents a novel CDDR strategy for engineering NiFe LDH into efficient HER catalysts without compromising its OER activity,potentially paving the way for the development of active and robust electrocatalysts for sustainable energy applications.
文摘In recent years,unmanned aerial vehicles(UAVs)cooperative path planning is attracting more and more research attention.For the multi-UAV cooperative path planning problem,the path planning problem in three-dimensional(3D)environment is transformed into an optimization problem by introducing the fitness function and constraints such as minimizing path length,maintaining a low and stable flight altitude,and avoiding threat zones.A multi-strategy hybrid grey wolf optimization(MSHGWO)algorithm is proposed to address this problem.Firstly,a chaotic Cubic mapping is introduced to initialize the grey wolf positions to make its initial position distribution more uniform.Secondly,an adaptive adjustment weight factor is designed,which can adjust the movement weight based on the rate of fitness value decrease within a unit Euclidean distance,thereby improving the quality of the population.Finally,an elite opposition-based learning strategy is introduced to improve the population diversity so that the population jumps out of the local optimum.Simulation results indicate that the MSHGWO is capable of generating constraint-compliant paths for each UAV in complex 3D environments.Furthermore,the MSHGWO outperforms other algorithms in terms of convergence speed and solution quality.Meanwhile,flight experiments were conducted to validate the path planning capability of MSHGWO in real-world obstacle environments,further demonstrating the feasibility of the proposed multi-UAV cooperative path planning approach.
基金funded by National Natural Science Foundation of China(Nos.12402142,11832013 and 11572134)Natural Science Foundation of Hubei Province(No.2024AFB235)+1 种基金Hubei Provincial Department of Education Science and Technology Research Project(No.Q20221714)the Opening Foundation of Hubei Key Laboratory of Digital Textile Equipment(Nos.DTL2023019 and DTL2022012).
文摘Owing to their global search capabilities and gradient-free operation,metaheuristic algorithms are widely applied to a wide range of optimization problems.However,their computational demands become prohibitive when tackling high-dimensional optimization challenges.To effectively address these challenges,this study introduces cooperative metaheuristics integrating dynamic dimension reduction(DR).Building upon particle swarm optimization(PSO)and differential evolution(DE),the proposed cooperative methods C-PSO and C-DE are developed.In the proposed methods,the modified principal components analysis(PCA)is utilized to reduce the dimension of design variables,thereby decreasing computational costs.The dynamic DR strategy implements periodic execution of modified PCA after a fixed number of iterations,resulting in the important dimensions being dynamically identified.Compared with the static one,the dynamic DR strategy can achieve precise identification of important dimensions,thereby enabling accelerated convergence toward optimal solutions.Furthermore,the influence of cumulative contribution rate thresholds on optimization problems with different dimensions is investigated.Metaheuristic algorithms(PSO,DE)and cooperative metaheuristics(C-PSO,C-DE)are examined by 15 benchmark functions and two engineering design problems(speed reducer and composite pressure vessel).Comparative results demonstrate that the cooperative methods achieve significantly superior performance compared to standard methods in both solution accuracy and computational efficiency.Compared to standard metaheuristic algorithms,cooperative metaheuristics achieve a reduction in computational cost of at least 40%.The cooperative metaheuristics can be effectively used to tackle both high-dimensional unconstrained and constrained optimization problems.
基金supported by the STI 2030 Major Projects(No.2022ZD0208804)the National Natural Science Foundation of China(No.62473017)。
文摘Robust cooperative unmanned aerial vehicle(UAV)formation in complex 3D environments is hampered by reward sparsity and inefficient collaboration.To address this,we propose context-aware relational agent learning(CORAL),a novel multi-agent deep reinforcement learning framework.CORAL synergistically integrates two modules:(1)a novelty-based intrinsic reward module to drive efficient exploration and(2)an explicit relational learning module that allows agents to predict peer intentions and enhance coordination.Built on a multi-agent Actor-Critic architecture,CORAL enables agents to balance self-interest with group objectives.Comprehensive evaluations in a high-fidelity simulation show that our method significantly outperforms state-of-theart baselines like multi-agent deep deterministic policy gradient(MADDPG)and monotonic value function factorisation for deep multi-agent reinforcement learning(QMIX)in path planning efficiency,collision avoidance,and scalability.
基金supported in part by National Natural Science Foundation of China(Nos.62373188,62003162)the Natural Science Foundation of Jiangsu Province of China(Nos.BK20240182,BK20222012)+2 种基金the Industry-University Research Innovation Foundation for the Chinese Ministry of Education(No.2021ZYA02005)the Aeronautical Science Foundation of China(Nos.20220007052003,20200007018001)the Fundamental Research Funds for the Central Universities,China(Nos.NE2024004,NI2024001)。
文摘To solve the problem of in-flight actuator faults and parameter uncertainties for multiple Unmanned Aerial Vehicles(UAVs),and reduce the communication and computational resource consumption of multiple UAVs,a Fraction-Order(FO)sliding-mode Fault-Tolerant Cooperative Control(FTCC)strategy is proposed for multiple UAVs based on Event-Triggered Communication Mechanism(ET-COM-M)and Event-Triggered Control Mechanism(ET-CON-M).First,by considering the limited communication bandwidth of multiple UAVs in formation,an ET-COM-M is designed to significantly reduce communication times.Then,a distributed observer is skillfully constructed to estimate the reference signals for follower UAVs.Moreover,the adaptive strategy is incorporated into the Radial Basis Function Neural Network(RBFNN)to learn the lumped unknown terms for handling bias actuator faults and parameter uncertainties.Besides,the Nussbaum method is used to deal with the loss-of-effectiveness faults.To further achieve the refined control performance against faults,FO calculus is artfully integrated into the sliding-mode control protocol with ET-CON-M.Finally,Zeno behavior is excluded by rigorous theoretical analysis and Lyapunov stability is proved to show the effectiveness of the designed FTCC strategy.Simulation results show that the designed FTCC strategy with Event-Triggered Mechanism(ETM)can guarantee the safety of multiple UAVs and simultaneously reduce the communication and control frequencies,making the developed control scheme applicable in engineering.
文摘In the lush heart of Uganda’s Busoga sub-region,Isaac Imaka is charting a new course for rural development.After seven years in national media,he left the newsroom and stepped into the soil.The former reporter with the Daily Monitor was driven by the belief that communities like his in Jinja North deserved more than chronic poverty and hand-to-mouth survival.
基金supported by National Key Research and Development Program of China(No.2023YFC2507406)National Natural Science Foundation of China(No.82300646)+6 种基金Beijing Natural Science Foundation(No.7232334)Beijing Municipal Administration of Hospitals Incubating Program(No.PX2024002,PX2020001)Capital Fund for Health Development Scientific Research(No.2024-2-2028)Beijing Municipal Science&Technology Commission AI+Health Collaborative Innovation Cultivation Project(No.Z241100007724004)Research Ward Excellence Program of Beijing Municipal Health Commission(No.BRWEP2024W162020100,BRWEP2024W162020112,BRWEP2024W162020114)Excellent Plan for Capital Medicine Scientific and Technological Innovation Achievement Transformation Promotion Plan(No.YC202401QX0824)Clinical Scientific Research Fund of Beijing Integrated Medical Association[No.ZHKY-2025-1869(B012)]。
文摘With the advancement of surgical techniques and enhanced management of early gastric cancer(EGC),minimally invasive function-preserving surgical approaches have emerged as a common goal for patients and clinicians.Laparoscopic-endoscopic cooperative surgery combined with sentinel lymph node navigation surgery(LECSSNNS)has drawn increasing interest because of its dual benefits of minimal invasiveness and organ function preservation.However,robust evidence-based support for guiding clinical implementation remains limited.To address this gap,we systematically evaluated available studies on the clinical application of LECS-SNNS in EGC and integrated expert insights to formulate 20 recommendations.These included preoperative assessment,surgical techniques,intraoperative endoscopic procedures,pathological evaluation,postoperative care,and follow-up.This consensus aimed to provide comprehensive guidance for the standardized application of LECS-SNNS,thereby advancing precise,minimally invasive,and function-preserving treatment for EGC.
文摘As we enter the year 2026,the international system continues to receive shocks from Donald Trump,arguably the 21st century’s most disruptive US leader.His return to the White House in 2025 coincided with the 80th anniversary of the defeat of fascism and the establishment of the United Nations,the multilateral platform that carried the world’s hope for peace,restraint and collective security.The coincidence was unsettling.A world order designed to limit power now confronts a moment in which power is exercised openly,transactionally and unapologetically.
基金023 Zhejiang Provincial Department of Education General Project:Research on an interdisciplinary teaching model to promote the development of computational thinking in the context of the new curriculum standards[Grant NO:Y202351596]Key Project of Zhejiang Provincial Education Science Planning:Research on an interdisciplinary teaching model to promote students’computational thinking from multiple analytical perspectives[Grant NO:2025SB103].
文摘This study constructs a reflective feedback model based on a pedagogical agent(PA)and explores its impact on students’problem-solving ability and cognitive load.A quasi-experimental design was used in the study,with 84 students from a middle school selected as the research subjects(44 in the experimental group and 40 in the control group).The experimental group used the reflective feedback model,while the control group used the factual feedback model.The results show that,compared with factual feedback,the reflective feedback model based on the pedagogical agent significantly improves students’problem-solving ability,especially at the action and thinking levels.In addition,this model effectively reduces students’cognitive load,especially in terms of internal and external load.
基金supported by the National Natural Science Foundation of China(No.62173274)the National Key R&D Program of China(No.2019YFA0405300)+4 种基金the Natural Science Foundation of Hunan Province of China(Nos.2021JJ10045 and 2025JJ60072)the Open Research Subject of State Key Laboratory of Intelligent Game(No.ZBKF-24-01)the Postdoctoral Fellowship Program of CPSF(No.GZB20240989)the China Postdoctoral Science Foundation(No.2024M754304)the Aeronautical Science Foundation of China(No.2023Z005030001).
文摘Cooperative guidance is a method for achieving combat objectives through information sharing and cooperative effects,and has emerged as a significant research area in the fields of missile guidance and systematic warfare.This study presents a systematic review and analysis of current research on cooperative guidance.First,a bibliometric analysis is conducted on 513 articles using the Scopus database and CiteSpace software to assess keyword clustering,keyword cooccurrence,and keyword burst,and to later visualize the results.Second,fundamental theories of cooperative guidance,including relative motion modeling methods,algebraic graph theory,and multi-agent consensus theory,are summarized.Subsequently,an overview of current cooperative laws and corresponding analysis methods is provided,with categorization based on the cooperative structure and convergence performance.Finally,we summarize current research developments based on five perspectives and propose a developmental framework based on five layers(cyber,physical,decision,information,and system),discussing potential future advancements in cooperative terminal guidance.This framework emphasizes five key areas of research:networked,heterogeneous,integrated,intelligent,and group cooperations,with the goal of offering trends and insights for futurework.
文摘To address the problem of multi-missile cooperative interception against maneuvering targets at a prespecified impact time and desired Line-of-Sight(LOS)angles in ThreeDimensional(3D)space,this paper proposes a 3D leader-following cooperative interception guidance law.First,in the LOS direction of the leader,an impact time-controlled guidance law is derived based on the fixed-time stability theory,which enables the leader to complete the interception task at a prespecified impact time.Next,in the LOS direction of the followers,by introducing a time consensus tracking error function,a fixed-time consensus tracking guidance law is investigated to guarantee the consensus tracking convergence of the time-to-go.Then,in the direction normal to the LOS,by combining the designed global integral sliding mode surface and the second-order Sliding Mode Control(SMC)theory,an innovative 3D LOS-angle-constrained interception guidance law is developed,which eliminates the reaching phase in the traditional sliding mode guidance laws and effectively saves energy consumption.Moreover,it effectively suppresses the chattering phenomenon while avoiding the singularity issue,and compensates for unknown interference caused by target maneuvering online,making it convenient for practical engineering applications.Finally,theoretical proof analysis and multiple sets of numerical simulation results verify the effectiveness,superiority,and robustness of the investigated guidance law.
基金funded by the Jilin Province Science and Technology Development Plan Project(20230101344JC).
文摘A centralized-distributed scheduling strategy for distribution networks based on multi-temporal and hierarchical cooperative game is proposed to address the issues of difficult operation control and energy optimization interaction in distribution network transformer areas,as well as the problem of significant photovoltaic curtailment due to the inability to consume photovoltaic power locally.A scheduling architecture combiningmulti-temporal scales with a three-level decision-making hierarchy is established:the overall approach adopts a centralized-distributed method,analyzing the operational characteristics and interaction relationships of the distribution network center layer,cluster layer,and transformer area layer,providing a“spatial foundation”for subsequent optimization.The optimization process is divided into two stages on the temporal scale:in the first stage,based on forecasted electricity load and demand response characteristics,time-of-use electricity prices are utilized to formulate day-ahead optimization strategies;in the second stage,based on the charging and discharging characteristics of energy storage vehicles and multi-agent cooperative game relationships,rolling electricity prices and optimal interactive energy solutions are determined among clusters and transformer areas using the Nash bargaining theory.Finally,a distributed optimization algorithm using the bisection method is employed to solve the constructed model.Simulation results demonstrate that the proposed optimization strategy can facilitate photovoltaic consumption in the distribution network and enhance grid economy.
基金supported by the National Natural Science Foundation of China under Grant U21A20449in part by Jiangsu Provincial Key Research and Development Program under Grant BE2021013-2。
文摘Wireless communication-enabled Cooperative Adaptive Cruise Control(CACC)is expected to improve the safety and traffic capacity of vehicle platoons.Existing CACC considers a conventional communication delay with fixed Vehicular Communication Network(VCN)topologies.However,when the network is under attack,the communication delay may be much higher,and the stability of the system may not be guaranteed.This paper proposes a novel communication Delay Aware CACC with Dynamic Network Topologies(DADNT).The main idea is that for various communication delays,in order to maximize the traffic capacity while guaranteeing stability and minimizing the following error,the CACC should dynamically adjust the VCN network topology to achieve the minimum inter-vehicle spacing.To this end,a multi-objective optimization problem is formulated,and a 3-step Divide-And-Conquer sub-optimal solution(3DAC)is proposed.Simulation results show that with 3DAC,the proposed DADNT with CACC can reduce the inter-vehicle spacing by 5%,10%,and 14%,respectively,compared with the traditional CACC with fixed one-vehicle,two-vehicle,and three-vehicle look-ahead network topologies,thereby improving the traffic efficiency.
基金supported by Scientific Research Projects of China Association of Metros(CAMET-KY-2022039)State Key Laboratory of Traction and Control System of EMU and Locomotive(2023YJ386).
文摘Purpose–This study aims to propose a cooperative adhesion control method for trains with multiple motors electric locomotives.The method is intended to optimize the output torque of each motor,maximize the utilization of train adhesion within the total torque command,reduce the train skidding/sliding phenomenon and achieve optimal adhesion utilization for each axle,thus realizing the optimal allocation of the multi-motor electric locomotives.Design/methodology/approach–In this study,a model predictive control(MPC)-based cooperative maximum adhesion tracking control method for multi-motor electric locomotives is presented.Firstly,train traction system with multiple motors is constructed in accordance with Newton’s second law.These equations include the train dynamics equations,the axle dynamics equations,and the wheel-rail adhesion coefficient equations.Then,a new MPC-based multi-axle adhesion co-optimization method is put forward.This method calculates the optimal output torque through real-time iteration based on the known reference slip speed to achieve multi-axle co-optimization under different circumstances.Findings–This paper presents a MPC system designed for the cooperative control of multi-axle adhesion.The results indicate that the proposed control system is able to optimize the adhesion of multiple axles under numerous different conditions and achieve the optimal power distribution based on the reduction of train skidding/sliding.Originality/value–This study presents a novel cooperative adhesion tracking control scheme.It is designed for multi-motor electric locomotives,which has rarely been studied before.And simulations are carried out in different conditions,including variable surfaces and motor failing.
