Study On The Airspace Conflict Resolution Problem Of Unmanned Aerial Vehicle Swarm Systems

The Unmanned Aerial Vehicles(UAVs)swarm would be an important application mode in both military and civilian field in the future.This thesis studies on the airspace conflict resolution problem of UAVs swarm systems.The primary model of UAVs airspace conflict resolution is studied.Three different conflict resolution modes are proposed with regarding to the control and management structure of the swarm systems,namely,centralized conflict resolution problem in one swarm,distributed cooperative conflict resolution problem in one swarm and distributed rule based conflict resolution problem when UAVs are not belonging to one swarm.This thesis studies on the conflict resolution algorithms when UAVs prefer to take heading change,velocity change and altitude change.The achievements of this thesis are summarized as below:Firstly,the primary airspace conflict resolution model of UAVs swarm systems is established.The speed change strategy and the dubins curve based heading change method are proposed based on the studying of the kinematics model of UAVs.The air traffic safety related models and algorithms are studied,such as the safe region model,the conflict detection algorithm and the safe separation constraints.The conflict avoidance maneuver evaluation functions are designed,which focuses on reducing the impacts on UAVs tasks and fuel consumptions.Secondly,the centralized algorithm that deals with the conflict resolution of UAVs in one swarm is proposed.The two-layered conflict resolution mechanism is proposed.In the first layer,conflicts among UAVs are checked and maneuver types are determined.In the second layer,the optimal conflict-free solutions are calculated by combining the speed change and heading change strategies.The heading change based conflict resolution algorithm and the speed change based algorithm are studied.The piecewise monotonicity of the heading change based safe separation constraints are proved.As the safe separation constraints are coupled when multiple UAVs are involving with the conflict,a two-step strategy is proposed.In the first step,the feasible solutions are obtained by using the vectorized stochastic parallel gradient descent method(V-SPGD).In the second step,the Sequential Quadric Programming(SQP)method is applied to find the local optimal solution based on the feasible solutions.This method improves the computation efficiency.A mixed integer linear programming(MILP)model is established to find the speed change safe separation solutions.According to the feature of the safe separation constraint,the period based regional searching method is proposed.Comparing with the existing algorithm,our speed change algorithm reduces the number of feasible sub regions to 2c~n times lower,where _cn is the number of pairwise conflicts,which reduces the time consumption dramatically.In a further step,this thesis discusses on the features of safe separation constraints in the three-dimensional space.The heading change based algorithm is extended to the 3-D space.Thirdly,the satisfying game theory and distributed optimization method based approach is proposed to deal with the distributed conflict resolution problem of UAVs in one swarm.This thesis proves the lipschitz continuity of safe separation constraint functions.According to the monotonicity of the safe separation constraint and the objective function,the distributed optimization method is applied to search the conflict free solutions.The algorithm is departed into two steps,to search the initial feasible solution in the first step and to find the local optimal solution in the second step.Different utility functions are defined in these two steps.The self-improving mechanism is proposed to enhance the usage efficiency of exchanged data among UAVs.UAVs could find out feasible solutions with limited number of handovers.Therefore,the algorithm is available in the inperferct communication environment.The proposed virtue control based optimization strategy improves the distributed coordination between UAVs efficiently.The distributed optimization algorithm in 3-D space is proposed.The numerical simulations are presented to demonstrate the validity of the distributed optimization algorithm.With considering the performance of the distributed algorithm in dealing with the conflict of large swarm of UAVs,this thesis proposes that the overall costs would be substantially reduced if each UAV chooses the heading maneuver direction with regarding the whole motion trend of the swarm.Fourthly,distributed rule based conflict resolution algorithm is proposed based on the space mapping method.This thesis analyzes the features of the tangent safe separation constraint and establishes a linear safe separation constraint from the nonlinear safe separation constraint by using the space mapping method.A consensus-guaranteed conflict avoidance tasks allocation rule is designed.According to the proposed rule,each UAV determines the constraints on its speed or heading by itself.Therefore,they find the optimal conflict free solutions individually.The numerical simulations are presented to demonstrate the validity of the proposed space mapping method and the distributed algorithm in the environment that with and without time delay.