A UAV autonomous formation evaluation index and MPC formation control method

Abstract

The invention discloses an autonomous formation evaluation index and a model predictive control (MPC) formation control method for unmanned aerial vehicles, belonging to the technical field of flight control. The invention provides relevant definitions about the autonomous formation of UAVs, a calculation method of the collision avoidance probability of the autonomous formation of the UAVs and an evaluation index of the autonomous formation of the UAVs, and proposes an MPC formation control method suitable for the UAVs. The present invention solves the problem of how to provide autonomous formation flight control when the size of the autonomous formation of the known UAVs is M, the average expected distance between the UAVs in the formation is dr, and the collision probability of the entire formation is required to be less than Pc The system design should follow the problem of the quantitative index of collision avoidance. The method of the invention provides a quantified index basis for the engineering design of the autonomous formation control system of the unmanned aerial vehicles, and solves the collision avoidance problem of the intensive formation of the unmanned aerial vehicles.

Description

technical field [0001] The invention belongs to the technical field of flight control, and relates to the establishment of an autonomous formation evaluation index of an unmanned aerial vehicle and a design method of an MPC (Model Predictive Control, model predictive control) formation controller. Background technique [0002] In the case of dense autonomous formation flight of multiple UAVs, the distance between UAVs is close to the minimum safe distance, and for a specific UAV in the formation, because of its surrounding distribution There are other UAVs and lack of free movement space, which makes the UAV's collision avoidance maneuver (such as avoiding the undesired movement of neighboring UAVs due to various random disturbances or some unexpected situations or failures) is more effective than loose formation The situation is more difficult and complex. How to judge the density of the autonomous formation, and how to design and evaluate the performance of the formation ...

AI Technical Summary

Problems solved by technology

[0002] In the case of dense autonomous formation flight of multiple UAVs, the distance between UAVs is close to the minimum safe distance, and for a specific UAV in the formation, because of its surrounding distribution There are other UAVs and lack of free movement space, which makes the UAV's collision avoidance maneuver (such as avoiding the undesired movement of neighboring UAVs due to various random disturbances or some unexpected situations or failures) is more effective than loose formation more difficult and complex

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