Unmanned aerial vehicle cooperative track control method based on hybrid swarm intelligence algorithm

Abstract

The invention discloses an unmanned aerial vehicle cooperative track control method based on a hybrid swarm intelligence algorithm, and belongs to the technical field of positioning navigation and control. The method comprises the following steps: firstly, designing an unmanned aerial vehicle cooperative track evaluation function according to a required constraint term; secondly, relevant parameters of a hybrid swarm intelligence algorithm are set, a particle swarm and a tabu table are initialized, and the maximum number of iterations of the algorithm is set; then, according to a track evaluation function, judging the spatial position of a particle solution, comparing to generate an individual optimal solution, judging whether to update a global optimal solution or not, repeating iteration until the maximum number of iterations is reached, obtaining a particle individual extreme value and a global extreme value, and updating a particle position and speed formula; finally, each unmanned aerial vehicle updates the state according to a particle position and speed formula and moves to a next track point to generate a new particle population; and each unmanned aerial vehicle arrives at the final target point. The method can be effectively applied to navigation problems of flight path planning and the like of platforms such as unmanned aerial vehicles, and is of great significance to development and construction of related industries.

Description

technical field [0001] The invention belongs to the technical field of positioning, navigation and control, and in particular refers to a method for controlling a cooperative track of an unmanned aerial vehicle based on a mixed group intelligent algorithm. Background technique [0002] With the more and more widespread applications of UAVs in recent years, the realization of UAVs' coordinated formation flight missions has become a current research hotspot. Among the many technologies involved in UAV collaboration, collaborative trajectory planning and control is one of the most critical technologies, which has the characteristics of wide interdisciplinary coverage and high difficulty in algorithm innovation. [0003] Cooperative trajectory planning control is essentially a kind of optimization problem. Relevant scholars at home and abroad have conducted a series of research on it. The research shows that the heuristic swarm intelligence algorithm is an effective way to solve...

AI Technical Summary

Problems solved by technology

[0004] The use of particle swarm optimization algorithm for various optimization problems has good advantages, but its inherent local search ability is poor when the global optimal value is the search target, and it is easy to prematurely fall into local optimal problems. Therefore, some improvements to the algorithm are needed.

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