Dear Editor,This letter presents a solution to the problem of seeking Nash equilibrium(NE)in a class of non-cooperative games of multi-agent systems(MASs)subject to the input disturbance and the networked communicatio...Dear Editor,This letter presents a solution to the problem of seeking Nash equilibrium(NE)in a class of non-cooperative games of multi-agent systems(MASs)subject to the input disturbance and the networked communication.To this end,a novel distributed robust predefined-time algorithm is proposed,which ensures the precise convergence of agent states to the NE within a settling time that can be directly determined by adjusting one or more parameters.The proposed algorithm employs an integral sliding mode strategy to effectively reject disturbances.Additionally,a consensus-based estimator is designed to overcome the challenge of limited information availability,where each agent can only access information from its directly connected neighbors,which conflicts with the computation of the cost function that requires information from all agents.Finally,a numerical example is provided to demonstrate the algorithm's effectiveness and performance.展开更多
Dear Editor,This letter addresses the robust predefined-time control challenge for leaderless optimal formation in networked mobile vehicle(NMV)systems.The aim is to minimize a composite global cost function derived f...Dear Editor,This letter addresses the robust predefined-time control challenge for leaderless optimal formation in networked mobile vehicle(NMV)systems.The aim is to minimize a composite global cost function derived from individual strongly convex functions of each agent,considering both input disturbances and network communication constraints.A novel predefined-time optimal formation control(PTOFC)algorithm is presented,ensuring agent state convergence to optimal formation positions within an adjustable settling time.Through the integration of an integral sliding mode technique,disturbances are effectively countered.A representative numerical example highlights the effectiveness and robustness of the developed approach.展开更多
基金supported by the National Natural Science Foundation of China(62373162,U24A20268,624B2055).
文摘Dear Editor,This letter presents a solution to the problem of seeking Nash equilibrium(NE)in a class of non-cooperative games of multi-agent systems(MASs)subject to the input disturbance and the networked communication.To this end,a novel distributed robust predefined-time algorithm is proposed,which ensures the precise convergence of agent states to the NE within a settling time that can be directly determined by adjusting one or more parameters.The proposed algorithm employs an integral sliding mode strategy to effectively reject disturbances.Additionally,a consensus-based estimator is designed to overcome the challenge of limited information availability,where each agent can only access information from its directly connected neighbors,which conflicts with the computation of the cost function that requires information from all agents.Finally,a numerical example is provided to demonstrate the algorithm's effectiveness and performance.
基金supported by the National Natural Science Foundation of China(62373162,U24A20268,624B2055)the Shenzhen Science and Technology Program(JCYJ 20240813114007010)the Knowledge Innovation Program of Wuhan-Basic Research(2023010201010100).
文摘Dear Editor,This letter addresses the robust predefined-time control challenge for leaderless optimal formation in networked mobile vehicle(NMV)systems.The aim is to minimize a composite global cost function derived from individual strongly convex functions of each agent,considering both input disturbances and network communication constraints.A novel predefined-time optimal formation control(PTOFC)algorithm is presented,ensuring agent state convergence to optimal formation positions within an adjustable settling time.Through the integration of an integral sliding mode technique,disturbances are effectively countered.A representative numerical example highlights the effectiveness and robustness of the developed approach.
