Flocking Control For Multi-agent Systems Based On Inclusion Principle

For many decades,flocking problems of multi-agents have received a great deal of attention from researchers in control science,physics,biology,robotics,computer science,and artificial intelligence,and so on,due to its board applications in cooperative control for unmanned aerial vehicles,formation control for swarm robots,and multi-target tracking for mobile sensor networks.The so-called flocking control is to design control protocols or algorithms suitable for interaction between individuals,such that the multi-agent system can emerge stable,complex yet order collective behavior through simple local information exchange between neighboring agents.Motivated by the existing researches,this paper focuses on the flocking control for multi-agents with different social distances under the action of single/multiple virtual leaders.The main contributions and innovations of this work are given below.(1)Based on the inclusion principle and its extended pair-wise decomposition,a novel distributed flocking model is proposed.First,a complex multi-agent system is decomposed into multiple independent pair-wise subsystems.Then,the flocking control for the whole system is realized through the parallel coordinated control of these pair-wise subsystems,thereby simplifying the analysis and design of flocking control for such complex systems.(2)According to the proposed flocking model,this paper investigates the flocking problem of multi-agents with local information exchange,which means that only partial,but not all,of the agents are informed of the group objective.Furthermore,to reduce the communication energy consumption during the flocking process,an improved flocking algorithm based on the model is designed to achieve stable flocking for all the agents.The stability analysis of the multi-agent system is then established,with the help of the Lyapunov stability theorem and La Salle's invariance principle.Especially,considering the individual heterogeneity in both nature and engineering applications,we also investigate the flocking problem of multi-agents with different sensing radiuses and social distancing.Finally,two special kinds of simulation examples are conducted to demonstrate the effectiveness of the proposed algorithm and results.(3)On the basis of the above flocking model,this paper investigates the flocking problem of different subgroups of multi-agents.In other words,considering the difference in social distancing among individuals,according to the extent of social distancing,a group composed of N mobile agents is divided into multiple different subgroups.Especially,from the perspective of differential game theory,the flocking problem of different subgroups can be regarded as collision avoidance between neighboring agents,or obstacle avoidance between agents and virtual static/dynamic obstacles.To explore the internal mechanism of this interesting problem,a novel flocking algorithm with multiple virtual leaders is designed.The proposed algorithm is a modified version of the traditional flocking and semi-flocking algorithms.The stability of the multi-agent system is then proven,with the help of Lyapunov stability theorem and LaSalle's invariance principle.Furthermore,considering the complex environment that unmanned aerial vehicles or swarm robots may face when performing military missions such as surveillance,reconnaissance,and rescue,etc.,we also explore the flocking problem of multi-agents in both virtual static and dynamic obstacles environment.Finally,three special kinds of simulation examples are designed to demonstrate the feasibility of the proposed theory results.