Research On Multi-UCAV Cooperative Route Planning Considering Weapon Configuration And Allocation

With the rapid development of modern information technology,artificial intelligence and new materials,and widely used in the flight control of aircraft,the development of UAV is changing rapidly.UCAV has developed from reconnaissance,evaluation,monitoring and early warning support equipment,and has become an important operational equipment that can carry out ground attack and even to air combat tasks,and will eventually become an important force affecting the operational process.The current mainstream attack drones,such as "Rainbow-5","Pterodactyl-?" and"Predator",have been greatly improved in terms of endurance and load capacity,and can mount more kinds of weapons and attack many different kinds of targets.At this time,the commander not only wants to plan the flight path of the UCAV to strike the target,but also needs to optimize the type and quantity of weapons mounted by the UCAV.The two kinds of decisions affect each other,making the planning of the UCAV operational task more complicated.In view of this,based on the characteristics of multiple UCAV target task planning,this dissertation constructs a series of mathematical optimization models of multi-UCAV cooperative path Planning considering the configuration of airborne weapons under different operational scenarios,and designs a series of constructional heuristic algorithms for fast solving and adaptive large neighborhood heuristics for improving the feasible solution.The main work and innovation of this dissertation are as follows:Firstly,according to the characteristics of multiple UCAV path planning problem considering weapon resource allocation,the basic process of path planning is analyzed.Then,this dissertation studies the different combat task scenes of multiple UCAV attack,and refines four typical combat styles of multiple UCAV combat.Subsequently,according to the characteristics of each kind of combat style,the concept model and modeling method of multiple UCAV path planning are put forward.Finally,this dissertation summarizes the solution algorithm of multi UCAV path planning,and based on this,determines the whole algorithm solution framework and framework.Second,the problem of multi-UCAV cooperative path planning for single depot considering the configuration of weapons is studied.In view of the operational characteristics of a single depot with multiple UCAV participation in target strike action,an integer programming model is constructed with integer programming modeling technology,and a heuristic initial solution construction algorithm based on loop segmentation is designed to construct a better initial feasible solution.Then two adaptive large neighborhood search algorithms are proposed,and 7 neighborhood structures are designed.In the iterative process,the adaptive learning of the weights is called through the neighborhood structure operator to improve the search efficiency of the improved initial feasible solution.Finally,through the experiments of 10,20,50,and 100 targets,the performance of the algorithm is compared and analyzed,and the validity of the model and algorithm is verified by comparison with CPLEX.Thirdly,the problem of multi-UCAV cooperative path planning in single depot considering weapon configuration and attacking time window is studied.A mixed integer programming model is established to solve the combat characteristics of single depot multiple UCAV participating in fixed time sensitive target.A heuristic initial solution construction algorithm based on path merging is designed to construct a better initial feasible solution for the problem after adding time window.Then,based on the adaptive large-domain heuristic search algorithm framework,6 neighborhood structure operators are designed for the time window feature,and the delete and insert operations such as random deletion,sub-loop deletion,and greedy insertion are combined with the operator's self.Adapt to the learning strategy,continuously improve the initial feasible solution,and finally get the optimal solution(or approximate optimal solution).Finally,the computational efficiency and solution effect of the heuristic algorithm and the adaptive Large neighborhood heuristic search algorithm are validated by contrast experiments of small,medium and large scale.Fourthly,the multi-depot multi-UCAV cooperative path planning problem considering the weapon configuration is studied.For the multi-depot multi-UCAV cooperative operation characteristics,an integer programming model of the problem was established.According to the characteristics of the model,a heuristic algorithm based on target clustering algorithm was proposed to construct a better initial feasible solution.Then,the adaptive large neighborhood heuristic search algorithm framework is given,and a number of neighborhood structures are designed to evolve the initial feasible solution and obtain the final solution on the basis of the previous chapters.Finally,a set of experiments is carried out to verify the model and algorithm.Fifth,the multi-depot multi-UCAV cooperative path planning problem considering the weapon configuration and strike time window is studied.The mixed integer programming modeling technique is used to build a mixed integer programming mathematical model for the multi-station and multi-station UCAV to participate in the cooperative combat characteristics of fixed time sensitive targets.Then,a heuristic initial solution construction algorithm based on capability partition is proposed to construct a better initial feasible solution quickly.Then,the adaptive large neighborhood heuristic search algorithm framework is presented,which is used to optimize the initial feasible solution and get the final solution.Finally,the mathematical model and the algorithm are validated by the experiments of different scale in an experimental case.