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
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
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
For multi-vehicle networks,Cooperative Positioning(CP)technique has become a promising way to enhance vehicle positioning accuracy.Especially,the CP performance could be further improved by introducing Sensor-Rich Veh...For multi-vehicle networks,Cooperative Positioning(CP)technique has become a promising way to enhance vehicle positioning accuracy.Especially,the CP performance could be further improved by introducing Sensor-Rich Vehicles(SRVs)into CP networks,which is called SRV-aided CP.However,the CP system may split into several sub-clusters that cannot be connected with each other in dense urban environments,in which the sub-clusters with few SRVs will suffer from degradation of CP performance.Since Unmanned Aerial Vehicles(UAVs)have been widely used to aid vehicular communications,we intend to utilize UAVs to assist sub-clusters in CP.In this paper,a UAV-aided CP network is constructed to fully utilize information from SRVs.First,the inter-node connection structure among the UAV and vehicles is designed to share available information from SRVs.After that,the clustering optimization strategy is proposed,in which the UAV cooperates with the high-precision sub-cluster to obtain available information from SRVs,and then broadcasts this positioning-related information to other low-precision sub-clusters.Finally,the Locally-Centralized Factor Graph Optimization(LC-FGO)algorithm is designed to fuse positioning information from cooperators.Simulation results indicate that the positioning accuracy of the CP system could be improved by fully utilizing positioning-related information from SRVs.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
This paper analyzes the humorous effects generated through the non-observance of Grice’s Cooperative Principle(CP)in the Chinese crosstalk Learning Manchu.Focusing on violations of the Quantity,Quality,Relation,and M...This paper analyzes the humorous effects generated through the non-observance of Grice’s Cooperative Principle(CP)in the Chinese crosstalk Learning Manchu.Focusing on violations of the Quantity,Quality,Relation,and Manner maxims,it examines how deliberate pragmatic deviations create comedy.The study also incorporates the unique crosstalk mechanism of“Baofu”(packaging and delivering jokes)and emphasizes the essential role of audience cooperation in humor reception.It argues that humor in crosstalk arises not only from performers’non-cooperation but also from active audience engagement within a shared cultural context.展开更多
System upgrades in unmanned systems have made Unmanned Aerial Vehicle(UAV)-based patrolling and monitoring a preferred solution for ocean surveillance.However,dynamic environments and large-scale deployments pose sign...System upgrades in unmanned systems have made Unmanned Aerial Vehicle(UAV)-based patrolling and monitoring a preferred solution for ocean surveillance.However,dynamic environments and large-scale deployments pose significant challenges for efficient decision-making,necessitating a modular multiagent control system.Deep Reinforcement Learning(DRL)and Decision Tree(DT)have been utilized for these complex decision-making tasks,but each has its limitations:DRL is highly adaptive but lacks interpretability,while DT is inherently interpretable but has limited adaptability.To overcome these challenges,we propose the Adaptive Interpretable Decision Tree(AIDT),an evolutionary-based algorithm that is both adaptable to diverse environmental settings and highly interpretable in its decision-making processes.We first construct a Markov decision process(MDP)-based simulation environment using the Cooperative Submarine Search task as a representative scenario for training and testing the proposed method.Specifically,we use the heat map as a state variable to address the issue of multi-agent input state proliferation.Next,we introduce the curiosity-guiding intrinsic reward to encourage comprehensive exploration and enhance algorithm performance.Additionally,we incorporate decision tree size as an influence factor in the adaptation process to balance task completion with computational efficiency.To further improve the generalization capability of the decision tree,we apply a normalization method to ensure consistent processing of input states.Finally,we validate the proposed algorithm in different environmental settings,and the results demonstrate both its adaptability and interpretability.展开更多
For the problem of cooperative strike against multiple maneuvering targets,in order to improve the detection efficiency of multi-missile systems,this paper proposes a Group Cooperative Midcourse Guidance Law(GCMGL)for...For the problem of cooperative strike against multiple maneuvering targets,in order to improve the detection efficiency of multi-missile systems,this paper proposes a Group Cooperative Midcourse Guidance Law(GCMGL)for heterogeneous missile formation with optimal detection efficiency.Firstly,considering the adverse impact of target maneuvering on the guidance system,a Super-Twisting Disturbance Observer(STDO)is introduced to estimate target acceleration.Secondly,to avoid chattering in the system,a reaching law is combined with the design of the midcourse guidance law and cooperative detection control law for the leader missiles.This approach provides reference information for follower missiles and forms an optimal detection formation.Then,to achieve cooperative engagement of targets by follower missiles in groups,a group consensus protocol is introduced in the Line-of-Sight(LOS)direction to design the GCMGL.Simultaneously,in the direction normal to the LOS,when follower missiles cannot obtain the LOS angle combination information from the leader missiles,a distributed extended state observer is introduced to estimate it.Finally,a time-varying LOS angle Formation Tracking Midcourse Guidance Law(FTMGL)is designed based on this estimated information.The guidance law’s stability is validated using Lyapunov theory,and simulation experiments are performed to confirm its effectiveness and advantages.展开更多
In this paper,we propose a hybrid decode-and-forward and soft information relaying(HDFSIR)strategy to mitigate error propagation in coded cooperative communications.In the HDFSIR approach,the relay operates in decode-...In this paper,we propose a hybrid decode-and-forward and soft information relaying(HDFSIR)strategy to mitigate error propagation in coded cooperative communications.In the HDFSIR approach,the relay operates in decode-and-forward(DF)mode when it successfully decodes the received message;otherwise,it switches to soft information relaying(SIR)mode.The benefits of the DF and SIR forwarding strategies are combined to achieve better performance than deploying the DF or SIR strategy alone.Closed-form expressions for the outage probability and symbol error rate(SER)are derived for coded cooperative communication with HDFSIR and energy-harvesting relays.Additionally,we introduce a novel normalized log-likelihood-ratio based soft estimation symbol(NL-SES)mapping technique,which enhances soft symbol accuracy for higher-order modulation,and propose a model characterizing the relationship between the estimated complex soft symbol and the actual high-order modulated symbol.Further-more,the hybrid DF-SIR strategy is extended to a distributed Alamouti space-time-coded cooperative network.To evaluate the~performance of the proposed HDFSIR strategy,we implement extensive Monte Carlo simulations under varying channel conditions.Results demonstrate significant improvements with the hybrid technique outperforming individual DF and SIR strategies in both conventional and distributed Alamouti space-time coded cooperative networks.Moreover,at a SER of 10^(-3),the proposed NL-SES mapping demonstrated a 3.5 dB performance gain over the conventional averaging one,highlighting its superior accuracy in estimating soft symbols for quadrature phase-shift keying modulation.展开更多
With the deepening of vocational education reform,the teaching work of computer majors in higher vocational colleges should be further optimized.Teachers should actively introduce new educational concepts and educatio...With the deepening of vocational education reform,the teaching work of computer majors in higher vocational colleges should be further optimized.Teachers should actively introduce new educational concepts and education methods,to better arouse students’interest,strengthen their understanding and application of the knowledge,and improve the education effect.School-enterprise collaboration,as a popular education concept at present,can greatly enrich the teaching content of computer majors,broaden the path of education,and greatly promote the more comprehensive development of students.Given this,this paper will carry out an analysis of school-enterprise collaborative education for computer majors,and put forward some strategies for other colleagues’reference.展开更多
Orbital angular momentum(OAM)can achieve multifold increase of spectrum efficiency,but the hollow divergence characteristic and Line-of-Sight(LoS)path requirement impose the crucial challenges for vortex wave communic...Orbital angular momentum(OAM)can achieve multifold increase of spectrum efficiency,but the hollow divergence characteristic and Line-of-Sight(LoS)path requirement impose the crucial challenges for vortex wave communications.For air-to-ground vortex wave communications,where there exists the LoS path,this paper proposes a multi-user cooperative receive(MUCR)scheme to break through the communication distance limitation caused by the characteristic of vortex wave hollow divergence.In particular,we derive the optimal radial position corresponding to the maximum intensity,which is used to adjust the waist radius.Based on the waist radius and energy ring,the cooperative ground users having the minimum angular square difference are selected.Also,the signal compensation scheme is proposed to decompose OAM signals in air-to-ground vortex wave communications.Simulation results are presented to verify the superiority of our proposed MUCR scheme.展开更多
Flexible lander,composed of multiple nodes connected by flexible material,can reducethe bouncing and overturning during the asteroid landing.To satisfy the complex constraints inthe node cooperation of the flexible la...Flexible lander,composed of multiple nodes connected by flexible material,can reducethe bouncing and overturning during the asteroid landing.To satisfy the complex constraints inthe node cooperation of the flexible landing,an intelligent cooperative guidance method is pro-posed.The method consists of a double-layer cooperative guidance structure,a guidance parameterdetermination approach,and an action priority strategy.The double-layer contains a basic guid-ance used to satisfy the terminal state constraints,and a compensatory guidance used to satisfythe lander's attitude constraint.For the compensatory guidance,the parameters are determinedby multi-agent system,which are trained according to the performance index of flexible landing tra-jectories.The action priority strategy is used to reduce the detrimental effect of parameter inconsis-tency on the node cooperation.The simulation of flexible landing shows that the cooperativeguidance method is effective in improving the landing accuracy while satisfying the constraints.Meanwhile,the method is robust to the disturbance in the navigation and control.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
With the rapid development of renewable energy,the Microgrid Coalition(MGC)has become an important approach to improving energy utilization efficiency and economic performance.To address the operational optimization p...With the rapid development of renewable energy,the Microgrid Coalition(MGC)has become an important approach to improving energy utilization efficiency and economic performance.To address the operational optimization problem inmulti-microgrid cooperation,a cooperative game strategy based on the Nash bargainingmodel is proposed,aiming to enable collaboration among microgrids to maximize overall benefits while considering energy trading and cost optimization.First,each microgrid is regarded as a game participant,and a multi-microgrid cooperative game model based on Nash bargaining theory is constructed,targeting the minimization of total operational cost under constraints such as power balance and energy storage limits.Second,the Nash bargaining solution is introduced as the benefit allocation scheme to ensure individual rationality and coalition stability.Finally,theAlternating Direction Method of Multipliers(ADMM)is employed to decompose the centralized optimization problem into distributed subproblems for iterative solution,thereby reducing communication burden and protecting privacy.Case studies reveal that the operational costs of the threemicrogrids are reduced by 26.28%,19.00%,and 17.19%,respectively,and the overall renewable energy consumption rate is improved by approximately 66.11%.展开更多
With the rapid development of medical data sharing,issues of privacy and ownership have become prominent,which have limited the scale of data sharing.To address the above challenges,we propose a blockchainbased data-s...With the rapid development of medical data sharing,issues of privacy and ownership have become prominent,which have limited the scale of data sharing.To address the above challenges,we propose a blockchainbased data-sharing framework to ensure data security and encourage data owners to actively participate in sharing.We introduce a reliable attribute-based searchable encryption scheme that enables fine-grained access control of encrypted data and ensures secure and efficient data sharing.The revenue distribution model is constructed based on Shapley value to motivate participants.Additionally,by integrating the smart contract technology of blockchain,the search operation and incentive mechanism are automatically executed.Through revenue distribution analysis,the incentive effect and rationality of the proposed scheme are verified.Performance evaluation shows that,compared with traditional data-sharing models,our proposed framework not only meets data security requirements but also incentivizes more participants to actively participate in data sharing.展开更多
This paper proposes a mixed game with finitely many leaders and follower populations.In such a game,two types of equilibria are defined.First,a Nash equilibrium is introduced for the scenario in which leaders and foll...This paper proposes a mixed game with finitely many leaders and follower populations.In such a game,two types of equilibria are defined.First,a Nash equilibrium is introduced for the scenario in which leaders and follower populations are in perfect competition,each maximizing its own payoff.Second,a cooperative equilibrium is proposed for the case where leaders and follower populations,respectively,form coalitions and cooperate.Moreover,the existence of both Nash and cooperative equilibria is proved under the condition that the payoff functions are continuous and quasi-concave.Finally,we demonstrate the generic stability of cooperative equilibria in mixed games.More concretely,in the sense of Baire category,the cooperative equilibria in most mixed games are stable under perturbations of the payoff functions.In short,this paper presents two main contributions.On the one hand,we provide a novel mixed-game framework,which differs from both classical leader-follower games and leader-follower population games.On the other hand,the Nash and cooperative equilibria in our mixed games are distinct from those in existing leader-follower population games.The results are further illustrated with examples.展开更多
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.
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.
基金supported by the National Natural Science Foundation of China(No.62271399)the National Key Research and Development Program of China(No.2022YFB1807102)。
文摘For multi-vehicle networks,Cooperative Positioning(CP)technique has become a promising way to enhance vehicle positioning accuracy.Especially,the CP performance could be further improved by introducing Sensor-Rich Vehicles(SRVs)into CP networks,which is called SRV-aided CP.However,the CP system may split into several sub-clusters that cannot be connected with each other in dense urban environments,in which the sub-clusters with few SRVs will suffer from degradation of CP performance.Since Unmanned Aerial Vehicles(UAVs)have been widely used to aid vehicular communications,we intend to utilize UAVs to assist sub-clusters in CP.In this paper,a UAV-aided CP network is constructed to fully utilize information from SRVs.First,the inter-node connection structure among the UAV and vehicles is designed to share available information from SRVs.After that,the clustering optimization strategy is proposed,in which the UAV cooperates with the high-precision sub-cluster to obtain available information from SRVs,and then broadcasts this positioning-related information to other low-precision sub-clusters.Finally,the Locally-Centralized Factor Graph Optimization(LC-FGO)algorithm is designed to fuse positioning information from cooperators.Simulation results indicate that the positioning accuracy of the CP system could be improved by fully utilizing positioning-related information from SRVs.
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.
文摘This paper analyzes the humorous effects generated through the non-observance of Grice’s Cooperative Principle(CP)in the Chinese crosstalk Learning Manchu.Focusing on violations of the Quantity,Quality,Relation,and Manner maxims,it examines how deliberate pragmatic deviations create comedy.The study also incorporates the unique crosstalk mechanism of“Baofu”(packaging and delivering jokes)and emphasizes the essential role of audience cooperation in humor reception.It argues that humor in crosstalk arises not only from performers’non-cooperation but also from active audience engagement within a shared cultural context.
文摘System upgrades in unmanned systems have made Unmanned Aerial Vehicle(UAV)-based patrolling and monitoring a preferred solution for ocean surveillance.However,dynamic environments and large-scale deployments pose significant challenges for efficient decision-making,necessitating a modular multiagent control system.Deep Reinforcement Learning(DRL)and Decision Tree(DT)have been utilized for these complex decision-making tasks,but each has its limitations:DRL is highly adaptive but lacks interpretability,while DT is inherently interpretable but has limited adaptability.To overcome these challenges,we propose the Adaptive Interpretable Decision Tree(AIDT),an evolutionary-based algorithm that is both adaptable to diverse environmental settings and highly interpretable in its decision-making processes.We first construct a Markov decision process(MDP)-based simulation environment using the Cooperative Submarine Search task as a representative scenario for training and testing the proposed method.Specifically,we use the heat map as a state variable to address the issue of multi-agent input state proliferation.Next,we introduce the curiosity-guiding intrinsic reward to encourage comprehensive exploration and enhance algorithm performance.Additionally,we incorporate decision tree size as an influence factor in the adaptation process to balance task completion with computational efficiency.To further improve the generalization capability of the decision tree,we apply a normalization method to ensure consistent processing of input states.Finally,we validate the proposed algorithm in different environmental settings,and the results demonstrate both its adaptability and interpretability.
基金supported by the National Natural Science Foundation of China(Nos.61973253 and 62003264).
文摘For the problem of cooperative strike against multiple maneuvering targets,in order to improve the detection efficiency of multi-missile systems,this paper proposes a Group Cooperative Midcourse Guidance Law(GCMGL)for heterogeneous missile formation with optimal detection efficiency.Firstly,considering the adverse impact of target maneuvering on the guidance system,a Super-Twisting Disturbance Observer(STDO)is introduced to estimate target acceleration.Secondly,to avoid chattering in the system,a reaching law is combined with the design of the midcourse guidance law and cooperative detection control law for the leader missiles.This approach provides reference information for follower missiles and forms an optimal detection formation.Then,to achieve cooperative engagement of targets by follower missiles in groups,a group consensus protocol is introduced in the Line-of-Sight(LOS)direction to design the GCMGL.Simultaneously,in the direction normal to the LOS,when follower missiles cannot obtain the LOS angle combination information from the leader missiles,a distributed extended state observer is introduced to estimate it.Finally,a time-varying LOS angle Formation Tracking Midcourse Guidance Law(FTMGL)is designed based on this estimated information.The guidance law’s stability is validated using Lyapunov theory,and simulation experiments are performed to confirm its effectiveness and advantages.
基金funded by the Deanship of Graduate Studies and Scientific Research at Jouf University under grant No.(DGSSR-2024-02-02160).
文摘In this paper,we propose a hybrid decode-and-forward and soft information relaying(HDFSIR)strategy to mitigate error propagation in coded cooperative communications.In the HDFSIR approach,the relay operates in decode-and-forward(DF)mode when it successfully decodes the received message;otherwise,it switches to soft information relaying(SIR)mode.The benefits of the DF and SIR forwarding strategies are combined to achieve better performance than deploying the DF or SIR strategy alone.Closed-form expressions for the outage probability and symbol error rate(SER)are derived for coded cooperative communication with HDFSIR and energy-harvesting relays.Additionally,we introduce a novel normalized log-likelihood-ratio based soft estimation symbol(NL-SES)mapping technique,which enhances soft symbol accuracy for higher-order modulation,and propose a model characterizing the relationship between the estimated complex soft symbol and the actual high-order modulated symbol.Further-more,the hybrid DF-SIR strategy is extended to a distributed Alamouti space-time-coded cooperative network.To evaluate the~performance of the proposed HDFSIR strategy,we implement extensive Monte Carlo simulations under varying channel conditions.Results demonstrate significant improvements with the hybrid technique outperforming individual DF and SIR strategies in both conventional and distributed Alamouti space-time coded cooperative networks.Moreover,at a SER of 10^(-3),the proposed NL-SES mapping demonstrated a 3.5 dB performance gain over the conventional averaging one,highlighting its superior accuracy in estimating soft symbols for quadrature phase-shift keying modulation.
基金Study on Long-Term Mechanism of School-Enterprise Cooperation in Vocational Education-Taking Private Schools as an Example(Project No.NY202304)。
文摘With the deepening of vocational education reform,the teaching work of computer majors in higher vocational colleges should be further optimized.Teachers should actively introduce new educational concepts and education methods,to better arouse students’interest,strengthen their understanding and application of the knowledge,and improve the education effect.School-enterprise collaboration,as a popular education concept at present,can greatly enrich the teaching content of computer majors,broaden the path of education,and greatly promote the more comprehensive development of students.Given this,this paper will carry out an analysis of school-enterprise collaborative education for computer majors,and put forward some strategies for other colleagues’reference.
基金supported in part by National Natural Science Foundation of China under Grant 62441115 and 62201427in part by the Ministry of Industry and Information Technology of the People’s Republic of China under Grant CBG01N23-01-04.
文摘Orbital angular momentum(OAM)can achieve multifold increase of spectrum efficiency,but the hollow divergence characteristic and Line-of-Sight(LoS)path requirement impose the crucial challenges for vortex wave communications.For air-to-ground vortex wave communications,where there exists the LoS path,this paper proposes a multi-user cooperative receive(MUCR)scheme to break through the communication distance limitation caused by the characteristic of vortex wave hollow divergence.In particular,we derive the optimal radial position corresponding to the maximum intensity,which is used to adjust the waist radius.Based on the waist radius and energy ring,the cooperative ground users having the minimum angular square difference are selected.Also,the signal compensation scheme is proposed to decompose OAM signals in air-to-ground vortex wave communications.Simulation results are presented to verify the superiority of our proposed MUCR scheme.
基金supported by the National Key Research and Development Program of China(No.2019YFA0706500)。
文摘Flexible lander,composed of multiple nodes connected by flexible material,can reducethe bouncing and overturning during the asteroid landing.To satisfy the complex constraints inthe node cooperation of the flexible landing,an intelligent cooperative guidance method is pro-posed.The method consists of a double-layer cooperative guidance structure,a guidance parameterdetermination approach,and an action priority strategy.The double-layer contains a basic guid-ance used to satisfy the terminal state constraints,and a compensatory guidance used to satisfythe lander's attitude constraint.For the compensatory guidance,the parameters are determinedby multi-agent system,which are trained according to the performance index of flexible landing tra-jectories.The action priority strategy is used to reduce the detrimental effect of parameter inconsis-tency on the node cooperation.The simulation of flexible landing shows that the cooperativeguidance method is effective in improving the landing accuracy while satisfying the constraints.Meanwhile,the method is robust to the disturbance in the navigation and control.
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funded by StateGrid Beijing Electric PowerCompany Technology Project,grant number 520210230004.
文摘With the rapid development of renewable energy,the Microgrid Coalition(MGC)has become an important approach to improving energy utilization efficiency and economic performance.To address the operational optimization problem inmulti-microgrid cooperation,a cooperative game strategy based on the Nash bargainingmodel is proposed,aiming to enable collaboration among microgrids to maximize overall benefits while considering energy trading and cost optimization.First,each microgrid is regarded as a game participant,and a multi-microgrid cooperative game model based on Nash bargaining theory is constructed,targeting the minimization of total operational cost under constraints such as power balance and energy storage limits.Second,the Nash bargaining solution is introduced as the benefit allocation scheme to ensure individual rationality and coalition stability.Finally,theAlternating Direction Method of Multipliers(ADMM)is employed to decompose the centralized optimization problem into distributed subproblems for iterative solution,thereby reducing communication burden and protecting privacy.Case studies reveal that the operational costs of the threemicrogrids are reduced by 26.28%,19.00%,and 17.19%,respectively,and the overall renewable energy consumption rate is improved by approximately 66.11%.
基金supported by the Natural Science Foundation of Hebei Province of China(F2021201052).
文摘With the rapid development of medical data sharing,issues of privacy and ownership have become prominent,which have limited the scale of data sharing.To address the above challenges,we propose a blockchainbased data-sharing framework to ensure data security and encourage data owners to actively participate in sharing.We introduce a reliable attribute-based searchable encryption scheme that enables fine-grained access control of encrypted data and ensures secure and efficient data sharing.The revenue distribution model is constructed based on Shapley value to motivate participants.Additionally,by integrating the smart contract technology of blockchain,the search operation and incentive mechanism are automatically executed.Through revenue distribution analysis,the incentive effect and rationality of the proposed scheme are verified.Performance evaluation shows that,compared with traditional data-sharing models,our proposed framework not only meets data security requirements but also incentivizes more participants to actively participate in data sharing.
基金supported by the National Natural Science Foundation of China(Grant No.11271098)the Guizhou Provincial Basic Research Program(Grant No.MS[2025]676)。
文摘This paper proposes a mixed game with finitely many leaders and follower populations.In such a game,two types of equilibria are defined.First,a Nash equilibrium is introduced for the scenario in which leaders and follower populations are in perfect competition,each maximizing its own payoff.Second,a cooperative equilibrium is proposed for the case where leaders and follower populations,respectively,form coalitions and cooperate.Moreover,the existence of both Nash and cooperative equilibria is proved under the condition that the payoff functions are continuous and quasi-concave.Finally,we demonstrate the generic stability of cooperative equilibria in mixed games.More concretely,in the sense of Baire category,the cooperative equilibria in most mixed games are stable under perturbations of the payoff functions.In short,this paper presents two main contributions.On the one hand,we provide a novel mixed-game framework,which differs from both classical leader-follower games and leader-follower population games.On the other hand,the Nash and cooperative equilibria in our mixed games are distinct from those in existing leader-follower population games.The results are further illustrated with examples.
