Fast and Precise Formation of UAV Swarm System via Adaptive Robust Diffeomorphism-Based Constraint-Following Control

This article proposes an adaptive robust diffeomorphism-based constraint-following control (ARDCFC) method for an unmanned aerial vehicle (UAV) swarm system to achieve fast and precise formation (FPF). FPF means that the UAV swarm system has the ability to converge to the desired formation within a short time while maintaining high accuracy. This control problem imposes requirements on both transient and steady-state performance, as well as collision avoidance under time-varying (possibly fast and irregular) uncertainties with unknown bounds. The FPF requirements and collision avoidance are formulated as inequality constraints, whereas the ideal swarm performance is formulated as a series of equality constraints. A diffeomorphism approach is adopted to transform all the above inequalities and equality constraints into unified equality constraints. The uncertainties are accounted for by adaptively estimating and utilizing a conservative bound. ARDCFC regards the equality constraints as control targets, thereby formulating FPF control with simultaneous collision avoidance as a constraint-following problem. The robustness and effectiveness of the proposed formation control method are demonstrated through rigorous proofs and simulations. To the best of our knowledge, this is probably the first study to simultaneously guarantee FPF and collision avoidance for an uncertain UAV swarm system.