| The cooperative control problem of multi-agent systems has attracted a great deal of attention in the last few decades,attributed to its practical application in a wide range of fields such as sensor networks,smart grids,aerospace,and UAV swarms.The main idea of cooperative control is to develop distributed control algorithms through local communication information between agents so that a group of agents can agree on the state or output of the agents.In practical applications,many real systems are characterized by nonlinearities,such as parameter linearization and unknown nonlinearities,and adaptive control and neural networks have good approximation and processing effects on nonlinear functions,which provide effective control methods to solve nonlinear terms in systems.In addition,since the communication of the multi-agent systems depends on the embedded digital microprocessor,how to reduce the communication channel overload and avoid continuous communication,event-triggered control is proposed as an important method.In this paper,the event-triggered adaptive cooperative control problem is investigated for several classes of typical nonlinear multi-agent systems under the framework of adaptive control,backstepping technique,and cooperative control with three main aspects as follows.First,the distributed event-triggered containment control problem for a class of nonlinear multi-agent systems with unknown nonlinearities and external disturbances is considered.Neural networks can effectively approximate the unknown nonlinear functions in the system model,while a discontinuous term is introduced in the controller to compensate for the external disturbances and approximation errors.By designing the composite adaptive event-triggered mechanism,the event-triggered controller is updated in a non-periodic manner during sampling,thus saving computational resources and transmission load.Based on the neural network-based adaptive control and event-triggered control strategy,the containment control of nonlinear multi-agent systems can be achieved.In addition,the Zeno behavior is shown to be excluded.Finally,the effectiveness and advantages of the proposed distributed control scheme are verified using simulation.Next,the event-triggered output-feedback consensus tracking control problem is considered for a class of nonlinear parametric strict feedback multi-agent systems subject to unknown sensor failures.Unlike the existing state observers,a new gain-adaptive state observer is designed to simultaneously estimate the unmeasurable states and sensor failures.Based on the adaptive observer,a sensor failure compensator is constructed to adaptively eliminate the effects of sensor failures.Additionally,the designed switching threshold event-triggered strategy effectively reduces the communication burden while balancing the system performance.Finally,simulations verify the effectiveness of the proposed failure compensator and output tracking algorithm.Finally,the event-triggered synchronization control problem for networked parabolic partial differential equation(PDE)system with uncertain nonlinear actuator dynamics is investigated.In contrast to the existing networked PDE systems,the control input occurs in the ordinary differential equation(ODE)subsystem rather than in the PDE subsystem.Furthermore,the unknown parameters affecting the interior of the PDE domain are considered.A novel passive identifier is constructed to estimate the system state and the unknown parameters.Based on the designed passive identifier and Lyapunov method,a novel synchronization controller is proposed to achieve synchronization control and the boundedness of all closed-loop signals.Finally,the validity of the obtained results is illustrated using simulations. |
