Research On Formation Control Of Fixed-wing UAV Swarms In Complex Enivronments

In recent years,swarms of unmanned aerial vehicles(UAVs)have gradually come into reality.This dissertation focuses on the warms of miniature fixed-wing UAVs,and investigate their formation control problems in complex environments.More specifically,to handle the challenges including limited communications,constrained inputs,scalability,etc.,we carry out theoretical research and develop key techniques on survivable topologies,nonlinear formation control laws,and group-based hierarchical architectures,whose effectiveness is corroborated by hardware-in-the-loop(HIL)simulations as well as field tests.The proposed methods systematically solve the precise and robust formation pattern preserving problem and the formation reconfiguration problem for large swarms of UAVs in complex environments.The main work and contributions of this dissertation are summarized as follows:(1)Output consensus protocols for the undirected/directed nonlinear networks of maximal equilibrium-independent passive(MEIP)objects are proposed,and topological conditions to achieve consensus are provided.It generalizes the stability analysis of nonlinear networked systems.In contrast to the traditional linear systems,essential nonlinearity,brings huge theoretical challenges to swarm coordinations,especially the relationship between the topology and the stability.In this dissertation,the networks comprised of MEIP objects are used to model the UAV swarms and their topology.For an undirected network,the dissertation proves that when the network is connected,the input-strictly passive protocol guarantees the network output consensus.For a directed network with a class of MEIP objects,the dissertation proves that when the network contains a directed spanning tree,the classical consensus protocol,which is a special case of the input-strictly passive protocol,makes the network achieve output consensus.(2)The concept of survivable topology in the sense of swarm control,as well as the algorithms to derive k edge/vertex survivable topologies are proposed,which solves the problem of pre-establishing swarm topologies in the presence of potential accidents including the failure of communication links and the damage of some UAV platforms in complex environments.Based on the undirected/directed topological conditions to reach consensus,the dissertation proposes the survivability definition for undirected and directed topologies.For the undirected topology,the dissertation builds a connection between the survivability and connectivity of the network;for the directed topology,the dissertation analyzes the property of such networks,and proposes the algorithms to design the edge/vertex survivable topology satisfying the given constraints.(3)The dissertation proposes the hybrid coordinated path following control algorithm based on invariant set theory,and achieves precise and stable formation pattern preserving and pattern reconfiguration of UAV swarms under control constraints.A novel framework is designed,which can achieve pattern preserving and pattern reconfiguration of UAV swarms based on coordinated path following.The dissertation simultaneously considers the velocity constraints as well as the heading rate constraints during the whole coordinated path following process.The corresponding coordinated path following control law is proposed based on invariant set,and the stability of the closed-loop is analyzed.In terms of the pattern preserving problem,the proposed control law guarantees that all the UAVs converge to the desired path,while the interUAV arc distances converge to the desired value.In terms of the pattern reconfiguration problem,the proposed control law guarantees that all the UAVs' velocities converge to the desired cruise speed,while the whole swarm reconfigure to the new formation pattern.HIL simulation and field test results validate the effectiveness of the proposed methods.(4)Robust coordinated path following control law is designed,and stability conditions of closed-loop system are provided.The redesigned control law tackles the challenges brought by the unknown bounded wind disturbances.By introducing the virtual target point(VTP),a novel path following control law without relying on the UAVs' closest projection points is presented,and coordination of the UAV swarm is achieved by synchronizing the UAVs' VTPs.Without estimating the wind disturbances,sufficient conditions to achieve coordinated path following are derived,where the upper bounds of the location errors are established.With estimating the wind disturbances,the dissertation proposes the coordinated path following control law by incorporating the wind estimation term,and theoretically proves the asymptotic stability of the closed-loop with zero estimation error,as well as the boundedness of the location errors with bounded estimation error.HIL simulation results validate the effectiveness of the redesigned robust control law.(5)Group-based hierarchical control architecture as well as strategies to handle unexpected accidents is proposed,such that the coordination control problem of large UAV swarms in complex environments is solved.By combining survivable topology with the coordinated path following control law,a group-based hierarchical control architecture for large swarms is established.The leader UAV in each group executes the coordinated path following control law,while the follower UAVs execute the leaderfollowing control law.Survivable topology which takes each leader UAV as vertex,is established among each group to improve the topology robustness.To handle the failure of some communication links and the damage of some UAV platforms,on the one hand,the survivable topology is developed to improve the fault tolerance of the whole swarm;on the other hand,strategies of topology reconfiguration and formation pattern reconfiguration are proposed,and thus the reliability of the swarm in the presence of unexpected accidents is further improved.Numerical simulations consisting of 100 UAVs in a whole mission process,as well as the field tests made up of 21 actual UAV platforms are conducted,which corroborate the effectiveness of the proposed control methods for large swarms.