A method of aircraft formation control

Abstract

The present invention provides a kind of aircraft formation control method, establishes the leader-follower relative movement model, adopts the three-axis acceleration of the follower under the leader coordinate system as the control amount to control the flight of each follower, so that the current position of each follower is the same as that of each follower. The distance between the corresponding desired positions is less than the set value, so that the formation is realized by flying according to the preset formation; it can be seen that the present invention can effectively realize the formation flight of the aircraft, and can satisfy the effect of the distance constraint between the aircraft.

Description

technical field [0001] The invention belongs to the technical field of aircraft flight strategies, and in particular relates to an aircraft formation control method. Background technique [0002] At present, for the formation control of UAVs, there are mainly formation methods based on the leader-slave mode and formation methods based on the distributed communication mode. For example, based on the ant colony algorithm, the relative path is planned for the aircraft and then tracked by designing the track tracking control rate, but this algorithm divides the formation formation and reconfiguration into two parts: path planning and track tracking, and the solution efficiency is low; or, The control action and time are parameterized and discretized respectively, and the improved genetic algorithm and pigeon group algorithm are used for optimization respectively. However, such methods have a large amount of calculation and are only applicable to two-dimensional planes. Effectiv...

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Problems solved by technology

For example, based on the ant colony algorithm, the relative path is planned for the aircraft and then tracked by designing the track tracking control rate, but this algorithm divides the formation formation and reconfiguration into two parts: path planning and track tracking, and the solution efficiency is low; or, The control action and time are parameterized and discretized respectively, and the improved genetic algorithm and pigeon group algorithm are used for optimization respectively. However, such methods have a large amount of calculation and are only applicable to two-dimensional planes. Effective verification; Finally, the particle swarm optimization algorithm can also be used to solve the PI controller parameters. Although effective formation control is achieved, this method does not consider the energy consumption problem in the formation reconstruction process

In addition, compared with the multi-objective optimization algorithm, the solution result of the single-objective optimization algorithm is greatly affected by the weight of the cost function. When the formation formation time or energy consumption index changes, the optimal solution needs to be recalculated, which is inefficient.

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