Unmanned aerial vehicle autonomous formation evaluation index and MPC formation control method

Abstract

The invention discloses an unmanned aerial vehicle autonomous formation evaluation index and model prediction control (MPC) formation control method and belongs to the technical field of flight control. According to the method, a definition relevant to unmanned aerial vehicle autonomous formation, a computing method of the collision prevention probability of unmanned aerial vehicle autonomous formation and an unmanned aerial vehicle autonomous formation evaluation index are provided, and the MPC formation control method applicable to unmanned aerial vehicles is provided. The method solves the problem how to give out the collision prevention quantitative index which should be followed by design of an autonomous formation flight control system when it is known that the unmanned aerial vehicle autonomous formation scale is M, the average expectation distance between unmanned aerial vehicles in formation is dr, and the collision probability of the whole formation is required to be smaller than Pc. The method provides a quantitative index basis for engineering design of the unmanned aerial vehicle autonomous formation control system, and the collision problem the unmanned aerial vehicles in dense formation is solved.

Description

technical field [0001] The invention belongs to the technical field of flight control, and relates to the establishment of an evaluation index for an autonomous formation of an unmanned aerial vehicle and a design method for 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 fo...

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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