Synergetic Control Framework for Autonomous UAV Swarm Coordination

This study presents a synergetic control approach for coordinating the motion of a UAV swarm based on self-organization principles and energy-potential interactions. The proposed method effectively addresses the known limitations of traditional potential field techniques. A procedure for synthesizing synergetic control of swarm motion is developed using a virtual force field with symmetric attraction and repulsion functions, enabling natural collision avoidance and stable formation maintenance. Damping terms are incorporated into the equations of motion to eliminate self-oscillations and ensure asymptotic stability. A synergetic controller based on virtual-pendulum meters is introduced to prevent stagnation. The curse of dimensionality is mitigated by a specialized mathematical framework, as confirmed by simulations. The swarm-formation time increases sublinearly with the number of UAVs, highlighting the scalability of the approach. A modeling study of swarm self-organization reveals three characteristic phases: chaotic motions, transitional reconfiguration, and ordered swarm behavior. The formation process corresponds to a gradual minimization of inter-UAV interaction energy, while stable collective motion is achieved by maintaining a constant polarization of vehicle heading angles. Simulations also identify parameter ranges that provide optimal synergetic properties during swarm formation and coordinated movement. The findings are further validated through real-world experimental tests of swarm control.