Scientists have developed a method for controlling groups of unmanned aerial vehicles (UAVs) that can make formation flight smoother and also reduce energy consumption and mechanical wear. The study was published in the International Journal of Systems, Control and Communications.
The new approach combines fuzzy logic - a way of processing data in which decisions are made not on a strict "yes/no" principle but taking into account the degree of confidence - and a self-tuning PID controller. The abbreviation PID stands for proportional-integral-derivative: such a controller adjusts the control action based on the current error, the error accumulated over past time and the rate of its change.
The task of coordinating drones and maintaining a stable formation is complicated by disturbances and by the interaction of the vehicles with each other. To describe this, the researchers built a model in which each drone in the formation is linked to the others by virtual springs and dampers. These are mathematical elements that represent the forces returning each vehicle to the required point. The model makes it possible to display the formation and observe how it deforms under various disturbances and then restores itself.
In the controller, fuzzy logic is combined with PID regulation, in which the response changes depending on the current error, the accumulated past error and the rate of its change. The fuzzy logic component uses rules to adjust the control parameters: when deviations are large, the corrections become stronger, and as the formation stabilizes, they become softer.
Tests showed that the method made the drones' flight corrections smoother, with fewer abrupt changes in commands. Smoother commands can limit wear on actuators and reduce energy consumption in tasks such as reconnaissance and surveillance.
The authors emphasize that these are results of modeling and testing, not a finished commercial product. The work does not state when the method could be introduced in practice.