Fuzzy Model Reference Adaptive Control of Consensus-based Helical UAV Formations

Helical formations of unmanned aerial vehicles (UAVs), which constitute the subject matter hereof, are a step up from 2D circular formations to 3D formations that control the UAV altitude difference. Helical formations need to be controlled when fixed-wing UAVs are climbing or descending, whereby the formation may neither change its structure nor stop tracking its ground target. Decentralized formations, e.g., consensus-based ones, complicate the problem. The author’s research has shown uncertain UAV dynamics threatens the stability of the system and may thus jeopardize the formation control algorithms. This paper presents a control concept for consensus-based helical UAV formations; the concept uses fuzzy model reference adaptive control (fuzzy MRAC). Unlike many other papers, the approach proposed hereon utilizes fuzzy Lyapunov functions to stabilize the adaptation loop. Simulations on full nonlinear UAV models (6 degrees of freedom and 12 states) show this approach to be effective. Formation controllers keep the system stable by means of self-tuning, which showcases the effectiveness of the approach. As a result, we were able to attain a helical 3D formation even in light of uncertain dynamics.