Distributed Dynamic Formation Control Based On Holographic States Estimation Of Leader

Compared with single-agent systems,multi-agent systems have received extensive attention from scholars from all walks of life because of their better task execution capabilities and efficiency.Formation control,as one of the important research branches of multi-agent systems,has broad application prospects in military and civilian fields,such as precise military operations,fixed-point handling of heavy objects,etc.,which requires the formation system to have better control accuracy and robustness.In practical systems,due to factors such as unstable communication,system personality,environmental obstacles,etc.,it is difficult for traditional formation systems to meet the requirements of control accuracy and robustness at the same time.Therefore,this paper focuses on the design of the leader state estimator and the tracking controller,and designs a distributed multi-agent formation system with both control accuracy and robustness.The specific research contents are:A distributed formation control architecture based on leader holographic state estimator is proposed.A leader holographic state estimator is designed to convert the complex formation control strategy based on graph theory into a leader-following control strategy.At this time,the optimal controller with obstacle avoidance ability can be independently designed according to the individual characteristics,so that the system has both control accuracy and robustness.Then,the influence of leader information on formation system dynamics is theoretically analyzed,and it is proved that the distributed formation system can achieve the formation accuracy of the centralized system when the followers all know the leader information.Due to the limitation of wireless communication distance,each follower cannot directly obtain the accurate holographic state of the leader.Therefore,based on the sliding mode control theory,this paper designs a model-independent leader holographic state estimator.The convergence of the holographic state estimator is analyzed by applying Lyapunov stability theory.Through simulation experiments,it is verified that under the condition of random communication topology,each follower can quickly and accurately estimate the leader’s state information and control information through the estimator.In order to improve the robustness of the formation system and make the heterogeneous system have good formation performance in a dynamic environment,a state tracking controller with obstacle avoidance capability is designed for each follower based on the model predictive control theory.Taking the four-wheel differential intelligent vehicle as the object,the dynamic model is established and linearized.By establishing the analytical relationship between the leader’s holographic state and the follower’s desired state,the obstacle avoidance constraint based on the collision risk model is constructed,the state tracking controller is designed,and the formation accuracy and robustness of the heterogeneous system are verified by simulation.In order to verify the effectiveness of the proposed system in a wide range of scenarios,a MATLAB/Simulink simulation model is built to compare and analyze the formation performance of the system in this paper,the centralized system and other distributed systems.Further,an experimental platform is built based on the Raspberry Pi differential smart car to verify the system and compare it with the H＿∞ distributed system.Comprehensive experimental results show that under the conditions of unstable communication,system personality,and environmental obstacles,the system proposed in this paper can have both formation control accuracy and robustness.