Adaptive decentralized flocking control of multi-UAV circular formations based on vector fields and backstepping. (December 2020)

• Record Type: Journal Article
• Authors: Muslimov, Tagir Z.; Munasypov, Rustem A.
• Is Part Of: ISA transactions. Volume 107(2021)
• Page Start: 143
• Page End: 159
• Publication Date: 2020-12
• Subjects: Standoff tracking -- Collective circumnavigation -- UAV consensus-based control -- Cooperative guidance -- Distributed control -- UAV swarming; Engineering instruments -- Periodicals; Engineering instruments; Periodicals; Electronic journals; 629.805
• DOI: 10.1016/j.isatra.2020.08.011
• Languages: English
• ISSNs: 0019-0578

Abstract

Abstract: This is a paper on controlling fixed-wing unmanned aerial vehicle (UAV) swarm formations while coordinating their flocking to a specified circular path. The proposed non-uniform in both magnitude and direction path-following vector fields enable the aircraft of the entire group to converge to a circular motion around a target while also attaining and maintaining relative phase-shift angles between the UAVs. It is thereby assumed that UAVs use decentralized consensus for their neighbor–neighbor​ coordination, which implies unconstrained scalability of the formation. The highlight of this research is that it gets rid of the conventional assumption that all the UAVs must initially be on a circular path and follow it strictly, which makes the proposed approach more practical. The obtained backstepping-based control commands explicitly factor in the input constraints and make the UAV course angles and speeds converge to the vector field-specified values. The inevitable parameter uncertainties of UAV kinematic models can destabilize the formation, which is why adaptive self-tuning is applied. The new decentralized UAV flocking controller has been tested by detailed numerical MATLAB/Simulink experiments, including comparative experimentation, using realistic six degree-of-freedom (DoF) 12-state nonlinear UAV models; numerical modeling demonstrates the proposed approach stable for a variety of initial conditions. Highlights: Fixed-wing UAVs are coordinated by decentralized scalable consensus; however, the approach is explicitly tailored to the nonlinear dynamics of autopilot-UAV systems. The proposed method has proven global asymptotic stability and therefore gets rid of the conventional assumption that all UAVs must be strictly on a circular path. Parameter uncertainties of the assumingly accurate guidance-level models may destabilize the UAV formation; however, adaptive self-tuning neutralizes their effects.