Multi-UAV cooperative target tracking via consensus-based guidance vector fields and fuzzy MRAC

Purpose This paper aims to propose a multi-agent approach adaptive control of fixed-wing unmanned aerial vehicles (UAVs) tracking moving ground target. The implies that the UAVs in single group must maintain preset phase shift angles while rotating around target so as evaluate target’s movement more accurately. Thus, controls should ensure UAV swarm follows circular path whose center is also attaining and maintaining formation specific geometric shape; system capable self-tuning because dynamics uncertain. Design/methodology/approach considers two interaction architectures: an open-chain where each only interacts with its neighbors; cooperative leader, leading involved formation. controllers are self-tuned by fuzzy model reference (MRAC). Findings Using decentralized architecture allows have unlimited number aircraft formation, which line behavior concept. was tested for efficiency performance various scenarios using complete nonlinear flying-wing models equipped configured standard autopilot models. Research limitations/implications Assume rectilinear trajectory at constant speed. speed supposed be known advance. Another assumption weather windless. Originality/value In contrast studies, this one uses Lyapunov guidance vector fields direction- magnitude-nonuniform. overall controller structure based on centralized consensus.