Study On Event-triggered Based Leader-following Formation Control Of Second-order Nonlinear Multi-agent Systems

In recent years,with the progress of industrial technology and the need for intelligence in the industrial field,multi-agent systems have been widely used in military surveillance and reconnaissance,environmental hazard detection,spacecraft formation flying,and other fields,which has led to the vigorous development of research on multi-agent systems.Multi-agent system refers to a group system composed of multiple agents,whose goal is to complete specific tasks through mutual communication and interaction among agents within the system.The leader following method is a common method for multi-agent systems to collaborate to complete tasks.Leader following consistency refers to the control problem where the follower agent achieves the same state as the leader agent under the influence of control algorithms,while leader following formation control refers to the process of multiple followers moving towards a specific target or direction under the leadership of a leader,maintaining a predetermined geometric shape(i.e.,formation)with each other.At the same time,it is necessary to adapt to the control problem of environmental constraints(such as avoiding obstacles).In practical systems,the computing resources and communication bandwidth of agent groups are often limited and often affected by external disturbances.Designing appropriate control strategies to save system resources and prevent external disturbances has important practical significance.Based on the above reasons,this paper studies the issue of event-triggered consistency and event-triggered formation control in multi-agent systems.For second-order systems with nonlinear dynamics,different distributed control strategies are designed to achieve different convergence effects.The research contents of this paper are as follows:(1)Aiming at the leader-followering consistency problem of second-order nonlinear multiagent systems,a fixed-time event-triggered control algorithm is designed to make the follower state agree with the leader state in a fixed time.At the same time,the introduction of event triggering strategy also effectively reduces the information exchange frequency between agents in the system,and ensures the rational use of communication resources in the process of multiagent systems scale expansion.The fixed time convergence of the algorithm was verified using Lyapunov functions,and the effectiveness of the algorithm was verified through simulation comparisons of different states of the same system.(2)For the leader-following formation control problem of second-order multi-agent systems with Lipschitz nonlinear characteristics and external disturbances,the leader following strategy is adopted to set virtual leaders for multi-agent groups,and set distance errors around them to form the desired formation target.For the collision problem that may occur between intelligent agent groups and external obstacles during the movement process,an improved artificial potential field method is adopted to establish virtual potential fields for each intelligent agent and obstacle respectively,ensuring that the intelligent agent can perform repulsive reactions when entering the repulsive potential field range,thereby ensuring the safe movement of the system as a whole;For the communication problem between intelligent agents,considering the changes in the complex external environment,a bidirectional communication and eventtriggered communication mechanism between intelligent agents is adopted to ensure that the intelligent agent group achieves stable formation while saving communication resources.The convergence analysis shows that the event triggering algorithm can make the multi-agent systems complete formation in a limited time,and the numerical simulation further demonstrates the effectiveness of the algorithm.(3)Aiming at the problem of leader following formation control of second-order multiagent systems with unknown nonlinear characteristics and external disturbance,considering the influence of external disturbance,an adaptive formation control method based on radial basis function neural network fitting nonlinear function is adopted to design an adaptive control algorithm and analyze the conditions to ensure system convergence,so as to achieve the goal of stabilizing formation.For obstacle avoidance and collision avoidance issues in the system,an improved artificial potential field method is also used to design a virtual potential field to solve them.The introduction of event triggering strategy effectively reduces the update frequency of the controller and reduces the number of communication between intelligent agents,saving resources.Through convergence analysis and simulation verification,the event-triggered adaptive algorithm achieves asymptotic time formation convergence and has strong adaptability to external environmental changes.Finally,the paper summarizes the research work and looks forward to the future research.