To address the charging infrastructure challenges associated with slow electric vehicle(EV)industry growth,this study investigates the collaboration between private charging-pile-sharing platforms struggling with prof...To address the charging infrastructure challenges associated with slow electric vehicle(EV)industry growth,this study investigates the collaboration between private charging-pile-sharing platforms struggling with profitability and automotive companies.This collaboration is crucial,as it demands a balanced price and service quality management due to consumer expectations.This paper introduces a Stackelberg game model to explore the relationship between a charging platform and an automotive company.Through numerical analysis,we assess how this cooperation might improve the platform’s efficiency and benefit society,potentially overcoming existing industry hurdles.Our findings indicate that such partnerships could benefit all parties involved,despite possible negative environmental impacts.However,after collaborat-ing,platforms may increase consumer prices and payments to suppliers,potentially lowering service quality for brand-associated consumers due to a compromise between shorter waiting times and service quality.This research offers valu-able insights for stakeholders on the effects of cooperation,enabling better strategic decisions in the EV charging sector.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
When performing tasks,unmanned clusters often face a variety of strategy choices.One of the key issues in unmanned cluster tasks is the method through which to design autonomous collaboration and cooperative evolution...When performing tasks,unmanned clusters often face a variety of strategy choices.One of the key issues in unmanned cluster tasks is the method through which to design autonomous collaboration and cooperative evolution mechanisms that allow for unmanned clusters to maximize their overall task effective-ness under the condition of strategic diversity.This paper ana-lyzes these task requirements from three perspectives:the diver-sity of the decision space,information network construction,and the autonomous collaboration mechanism.Then,this paper pro-poses a method for solving the problem of strategy selection diversity under two network structures.Next,this paper presents a Moran-rule-based evolution dynamics model for unmanned cluster strategies and a vision-driven-mechanism-based evolu-tion dynamics model for unmanned cluster strategy in the con-text of strategy selection diversity according to various unmanned cluster application scenarios.Finally,this paper pro-vides a simulation analysis of the effects of relevant parameters such as the payoff factor and cluster size on cooperative evolu-tion in autonomous cluster collaboration for the two types of models.On this basis,this paper presents advice for effectively addressing diverse choices in unmanned cluster tasks,thereby providing decision support for practical applications of unmanned cluster tasks.展开更多
A situation maintenance-based cooperative guidance strategy is proposed to intercept a high-speed and high-maneuverability target via inferior missiles.Reachability and relative motion analyses are conducted to develo...A situation maintenance-based cooperative guidance strategy is proposed to intercept a high-speed and high-maneuverability target via inferior missiles.Reachability and relative motion analyses are conducted to develop and pursue virtual targets,respectively.A two-stage guidance strategy under nonlinear kinematics is developed on the basis of virtual targets.The first stage optimizes the coverage and collision situation by pursuing virtual targets under specific angular constraints.The second stage subsequently intercepts the superior target based on the handover condition optimized by the first stage.Numerical simulation results are provided to compare the effectiveness and superiority of the proposed strategy with those of the reachability-based cooperative strategy(RCS),coverage-based cooperative guidance(CBCG)and augmented proportional navigation(APN)under various maneuvering modes.展开更多
This paper presents a mode-switching collaborative defense strategy for spacecraft pursuit-evasiondefense scenarios.In these scenarios,the pursuer tries to avoid the defender while capturing the evader,while the evade...This paper presents a mode-switching collaborative defense strategy for spacecraft pursuit-evasiondefense scenarios.In these scenarios,the pursuer tries to avoid the defender while capturing the evader,while the evader and defender form an alliance to prevent the pursuer from achieving its goal.First,the behavioral modes of the pursuer,including attack and avoidance modes,were established using differential game theory.These modes are then recognized by an interactive multiple model-matching algorithm(IMM),that uses several smooth variable structure filters to match the modes of the pursuer and update their probabilities in real time.Based on the linear-quadratic optimization theory,combined with the results of strategy identification,a two-way cooperative optimal strategy for the defender and evader is proposed,where the evader aids the defender to intercept the pursuer by performing luring maneuvers.Simulation results show that the interactive multi-model algorithm based on several smooth variable structure filters perform well in the strategy identification of the pursuer,and the cooperative defense strategy based on strategy identification has good interception performance when facing pursuers,who are able to flexibly adjust their game objectives.展开更多
This paper presents a fixed-time cooperative gui-dance method with impact angle constraints for multiple flight vehicles (MFV) to address the challenges of intercepting large maneuvering targets with difficulty and lo...This paper presents a fixed-time cooperative gui-dance method with impact angle constraints for multiple flight vehicles (MFV) to address the challenges of intercepting large maneuvering targets with difficulty and low precision. A coopera-tive guidance model is proposed, transforming the cooperative interception problem into a consensus problem based on the remaining flight time of the flight vehicles. First, the impact angle constraint is converted into the line of sight (LOS) angle con-straint, and a new fixed-time convergent non-singular terminal sliding surface is introduced, which resolves the singularity issue of the traditional sliding surfaces. With this approach, LOS angle rate and normal overloads can converge in fixed time, ensuring that the upper bound of the system convergence time is not affected by the initial value of the system. Furthermore, the maneuvering movement of the target is considered as a system disturbance, and an extended state observer is employed to estimate and compensate for it in the guidance law. Lastly, by applying consensus theory and distributed communication topology, the remaining flight time of each flight vehicle is syn-chronized to ensure that they intercept the target simulta-neously with different impact angles. Simulation experiments are conducted to validate the effectiveness of the proposed cooper-ative interception and guidance method.展开更多
In the realm of missile defense systems,the self-sufficient maneuver capacity of missile swarms is pivotal for their survival.Through the analysis of the missile dynamics model,a time-efficient cooperative attack stra...In the realm of missile defense systems,the self-sufficient maneuver capacity of missile swarms is pivotal for their survival.Through the analysis of the missile dynamics model,a time-efficient cooperative attack strategy for missile swarm is proposed.Based on the distribution of the attackers and defenders,the collision avoidance against the defenders is considered during the attack process.By analyzing the geometric relationship between the relative velocity vector and relative position vector of the attackers and defenders,the collision avoidance constrains of attacking swarm are redefined.The key point is on adjusting the relative velocity vectors to fall outside the collision cone.This work facilitates high-precision attack toward the target while keeping safe missing distance between other attackers during collision avoidance process.By leveraging an innovative repulsion artificial function,a time-efficient cooperative attack strategy for missile swarm is obtained.Through rigorous simulation,the effectiveness of this cooperative attack strategy is substantiated.Furthermore,by employing Monte Carlo simulation,the success rate of the cooperative attack strategy is assessesed and the optimal configuration for the missile swarm is deduced.展开更多
To solve the problem of providing the best initial situation for terminal guidance when multiple missiles intercept multiple targets,a group cooperative midcourse guidance law(GCMGL)considering time-to-go is proposed....To solve the problem of providing the best initial situation for terminal guidance when multiple missiles intercept multiple targets,a group cooperative midcourse guidance law(GCMGL)considering time-to-go is proposed.Firstly,a threedimensional(3D)guidance model is established and a cooperative trajectory shaping guidance law is given.Secondly,for estimating the unknown target maneuvering acceleration,an adaptive disturbance observer(ADO)is designed,combining finitetime theory with a radial basis function(RBF)neural network,and the convergence of the estimation error is proven using Lyapunov stability theory.Then,to ensure time-to-go cooperation among missiles within the same group and across different groups,the group consensus protocols of virtual collision point mean and the inter-group cooperative consensus protocol are designed respectively.Based on the group consensus protocols,the virtual collision point cooperative guidance law is given,and the finite-time convergence is proved by Lyapunov stability theory.Simultaneously,combined with trajectory shaping guidance law,virtual collision point cooperative guidance law and the intergroup cooperative consensus protocol,the design of GCMGL considering time-to-go is given.Finally,numerical simulation results show the effectiveness and the superiority of the proposed GCMGL.展开更多
How multi-unmanned aerial vehicles(UAVs)carrying a payload pass an obstacle-dense environment is practically important.Up to now,there have been few results on safe motion planning for the multi-UAVs cooperative trans...How multi-unmanned aerial vehicles(UAVs)carrying a payload pass an obstacle-dense environment is practically important.Up to now,there have been few results on safe motion planning for the multi-UAVs cooperative transportation system(CTS)to pass through such an environment.The prob-lem is challenging because it is difficult to analyze and explicitly take into account the swing motion of the payload in planning.In this paper,a modeling method of virtual tube is proposed by fus-ing the advantages of the existing modeling algorithm for regu-lar virtual tube and the expansion environment method.The pro-posed method can not only generate a safe and smooth tube for UAVs,but also ensure the payload stays away from the dense obstacles.Simulation results show the effectiveness of the method and the safety of the planned tube.展开更多
Partial cooperation models are studied for many years to solve the bilevel programming problems where the follower’s optimal reaction is not unique. However, in these existed models, the follower’s cooperation level...Partial cooperation models are studied for many years to solve the bilevel programming problems where the follower’s optimal reaction is not unique. However, in these existed models, the follower’s cooperation level does not depend on the leader’s decision. A new model is proposed to solve this deficiency. It is proved the feasibility of the new model when the reaction set of the lower level is lower semicontinuous. And the numerical results show that the new model has optimal solutions when the reaction set of the lower level is discrete, lower semi-continuous and non-lower semi-continuous.展开更多
KD(D&K) (Synthesized Knowledge Discovery System based on Database and KnowledgeBase Cooperating Mechanism) is first advanced in this paper on the basis of KDD (KnowledgeDiscovery System based on Database) and KDK ...KD(D&K) (Synthesized Knowledge Discovery System based on Database and KnowledgeBase Cooperating Mechanism) is first advanced in this paper on the basis of KDD (KnowledgeDiscovery System based on Database) and KDK (Knowledge Discovery System based on KnowledgeBase). KD (D&K) is not simple addition of KDD and KDK but a new system with absolutelynew character and essential development, which is distinct from KDD and KDK and includes them.Not only the generalized structural frame of control rules KD (D&K) acquiring method is proposed,but also the theoretical basis of its key technical problem--don ble-bases cooperating mechanism isdiscussed according to the original academic idea to restrict KDD by basic knowledge base.展开更多
基金supported by the National Natural Science Foundation of China(72474034,72104034)Humanities and Social Science Fund of the Ministry of Education of China(21YJC630037,22XJC910001)China Postdoctoral Science Foundation(2022T150072)。
文摘To address the charging infrastructure challenges associated with slow electric vehicle(EV)industry growth,this study investigates the collaboration between private charging-pile-sharing platforms struggling with profitability and automotive companies.This collaboration is crucial,as it demands a balanced price and service quality management due to consumer expectations.This paper introduces a Stackelberg game model to explore the relationship between a charging platform and an automotive company.Through numerical analysis,we assess how this cooperation might improve the platform’s efficiency and benefit society,potentially overcoming existing industry hurdles.Our findings indicate that such partnerships could benefit all parties involved,despite possible negative environmental impacts.However,after collaborat-ing,platforms may increase consumer prices and payments to suppliers,potentially lowering service quality for brand-associated consumers due to a compromise between shorter waiting times and service quality.This research offers valu-able insights for stakeholders on the effects of cooperation,enabling better strategic decisions in the EV charging sector.
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(72471240).
文摘When performing tasks,unmanned clusters often face a variety of strategy choices.One of the key issues in unmanned cluster tasks is the method through which to design autonomous collaboration and cooperative evolution mechanisms that allow for unmanned clusters to maximize their overall task effective-ness under the condition of strategic diversity.This paper ana-lyzes these task requirements from three perspectives:the diver-sity of the decision space,information network construction,and the autonomous collaboration mechanism.Then,this paper pro-poses a method for solving the problem of strategy selection diversity under two network structures.Next,this paper presents a Moran-rule-based evolution dynamics model for unmanned cluster strategies and a vision-driven-mechanism-based evolu-tion dynamics model for unmanned cluster strategy in the con-text of strategy selection diversity according to various unmanned cluster application scenarios.Finally,this paper pro-vides a simulation analysis of the effects of relevant parameters such as the payoff factor and cluster size on cooperative evolu-tion in autonomous cluster collaboration for the two types of models.On this basis,this paper presents advice for effectively addressing diverse choices in unmanned cluster tasks,thereby providing decision support for practical applications of unmanned cluster tasks.
基金supported by the National Natural Science Foundation of China(Grant No.62203362)the Natural Science Basic Research Program of Shaanxi(Grant No.2023-JC-QN-0569)。
文摘A situation maintenance-based cooperative guidance strategy is proposed to intercept a high-speed and high-maneuverability target via inferior missiles.Reachability and relative motion analyses are conducted to develop and pursue virtual targets,respectively.A two-stage guidance strategy under nonlinear kinematics is developed on the basis of virtual targets.The first stage optimizes the coverage and collision situation by pursuing virtual targets under specific angular constraints.The second stage subsequently intercepts the superior target based on the handover condition optimized by the first stage.Numerical simulation results are provided to compare the effectiveness and superiority of the proposed strategy with those of the reachability-based cooperative strategy(RCS),coverage-based cooperative guidance(CBCG)and augmented proportional navigation(APN)under various maneuvering modes.
基金the Science and Technology Department,Heilongjiang Province under Grant Agreement No JJ2022LH0315。
文摘This paper presents a mode-switching collaborative defense strategy for spacecraft pursuit-evasiondefense scenarios.In these scenarios,the pursuer tries to avoid the defender while capturing the evader,while the evader and defender form an alliance to prevent the pursuer from achieving its goal.First,the behavioral modes of the pursuer,including attack and avoidance modes,were established using differential game theory.These modes are then recognized by an interactive multiple model-matching algorithm(IMM),that uses several smooth variable structure filters to match the modes of the pursuer and update their probabilities in real time.Based on the linear-quadratic optimization theory,combined with the results of strategy identification,a two-way cooperative optimal strategy for the defender and evader is proposed,where the evader aids the defender to intercept the pursuer by performing luring maneuvers.Simulation results show that the interactive multi-model algorithm based on several smooth variable structure filters perform well in the strategy identification of the pursuer,and the cooperative defense strategy based on strategy identification has good interception performance when facing pursuers,who are able to flexibly adjust their game objectives.
基金supported by the National Natural Science Foundation of China(61903099)the Natural Science Foundation of Heilongjiang Province(LH2020F025)+2 种基金the Project of Science and Technology Research Program of Chongqing Education Commission of China(KJZD-K20200470)the Postdoctoral Science Foundation of China(2021M690812)the Postdoctoral Science Fund of Heilongjiang Province(LBH-Z21048).
文摘This paper presents a fixed-time cooperative gui-dance method with impact angle constraints for multiple flight vehicles (MFV) to address the challenges of intercepting large maneuvering targets with difficulty and low precision. A coopera-tive guidance model is proposed, transforming the cooperative interception problem into a consensus problem based on the remaining flight time of the flight vehicles. First, the impact angle constraint is converted into the line of sight (LOS) angle con-straint, and a new fixed-time convergent non-singular terminal sliding surface is introduced, which resolves the singularity issue of the traditional sliding surfaces. With this approach, LOS angle rate and normal overloads can converge in fixed time, ensuring that the upper bound of the system convergence time is not affected by the initial value of the system. Furthermore, the maneuvering movement of the target is considered as a system disturbance, and an extended state observer is employed to estimate and compensate for it in the guidance law. Lastly, by applying consensus theory and distributed communication topology, the remaining flight time of each flight vehicle is syn-chronized to ensure that they intercept the target simulta-neously with different impact angles. Simulation experiments are conducted to validate the effectiveness of the proposed cooper-ative interception and guidance method.
基金supported by the Intelligent Aerospace System Leading Innovation Team Program of Zhejiang(2022R01003).
文摘In the realm of missile defense systems,the self-sufficient maneuver capacity of missile swarms is pivotal for their survival.Through the analysis of the missile dynamics model,a time-efficient cooperative attack strategy for missile swarm is proposed.Based on the distribution of the attackers and defenders,the collision avoidance against the defenders is considered during the attack process.By analyzing the geometric relationship between the relative velocity vector and relative position vector of the attackers and defenders,the collision avoidance constrains of attacking swarm are redefined.The key point is on adjusting the relative velocity vectors to fall outside the collision cone.This work facilitates high-precision attack toward the target while keeping safe missing distance between other attackers during collision avoidance process.By leveraging an innovative repulsion artificial function,a time-efficient cooperative attack strategy for missile swarm is obtained.Through rigorous simulation,the effectiveness of this cooperative attack strategy is substantiated.Furthermore,by employing Monte Carlo simulation,the success rate of the cooperative attack strategy is assessesed and the optimal configuration for the missile swarm is deduced.
基金supported by the National Natural Science Foundation of China(62003264).
文摘To solve the problem of providing the best initial situation for terminal guidance when multiple missiles intercept multiple targets,a group cooperative midcourse guidance law(GCMGL)considering time-to-go is proposed.Firstly,a threedimensional(3D)guidance model is established and a cooperative trajectory shaping guidance law is given.Secondly,for estimating the unknown target maneuvering acceleration,an adaptive disturbance observer(ADO)is designed,combining finitetime theory with a radial basis function(RBF)neural network,and the convergence of the estimation error is proven using Lyapunov stability theory.Then,to ensure time-to-go cooperation among missiles within the same group and across different groups,the group consensus protocols of virtual collision point mean and the inter-group cooperative consensus protocol are designed respectively.Based on the group consensus protocols,the virtual collision point cooperative guidance law is given,and the finite-time convergence is proved by Lyapunov stability theory.Simultaneously,combined with trajectory shaping guidance law,virtual collision point cooperative guidance law and the intergroup cooperative consensus protocol,the design of GCMGL considering time-to-go is given.Finally,numerical simulation results show the effectiveness and the superiority of the proposed GCMGL.
基金supported by the National Natural Science Foundation of China(6237338661973327).
文摘How multi-unmanned aerial vehicles(UAVs)carrying a payload pass an obstacle-dense environment is practically important.Up to now,there have been few results on safe motion planning for the multi-UAVs cooperative transportation system(CTS)to pass through such an environment.The prob-lem is challenging because it is difficult to analyze and explicitly take into account the swing motion of the payload in planning.In this paper,a modeling method of virtual tube is proposed by fus-ing the advantages of the existing modeling algorithm for regu-lar virtual tube and the expansion environment method.The pro-posed method can not only generate a safe and smooth tube for UAVs,but also ensure the payload stays away from the dense obstacles.Simulation results show the effectiveness of the method and the safety of the planned tube.
基金supported by the National Natural Science Foundationof China (70771080)the National Science Foundation of Hubei Province(20091107)Hubei Province Key Laboratory of Systems Science in Metallurgical Process (B201003)
文摘Partial cooperation models are studied for many years to solve the bilevel programming problems where the follower’s optimal reaction is not unique. However, in these existed models, the follower’s cooperation level does not depend on the leader’s decision. A new model is proposed to solve this deficiency. It is proved the feasibility of the new model when the reaction set of the lower level is lower semicontinuous. And the numerical results show that the new model has optimal solutions when the reaction set of the lower level is discrete, lower semi-continuous and non-lower semi-continuous.
文摘KD(D&K) (Synthesized Knowledge Discovery System based on Database and KnowledgeBase Cooperating Mechanism) is first advanced in this paper on the basis of KDD (KnowledgeDiscovery System based on Database) and KDK (Knowledge Discovery System based on KnowledgeBase). KD (D&K) is not simple addition of KDD and KDK but a new system with absolutelynew character and essential development, which is distinct from KDD and KDK and includes them.Not only the generalized structural frame of control rules KD (D&K) acquiring method is proposed,but also the theoretical basis of its key technical problem--don ble-bases cooperating mechanism isdiscussed according to the original academic idea to restrict KDD by basic knowledge base.
