Multi-UAV Cooperative Target Tracking via Consensus-based Guidance
Vector Fields and Fuzzy MRAC
Abstract
Link to peer-reviewed version: https://doi.org/10.1108/AEAT-02-2021-0058
This paper proposes a multi-agent approach to adaptive control of
fixed-wing unmanned aerial vehicles (UAVs) tracking a moving ground
target. The approach implies that the UAVs in a single group must
maintain preset phase shift angles while rotating around the target so
as to evaluate the target’s movement more ac-curately. Thus, the
controls should ensure that: (1) the UAV swarm follows a moving circular
path whose center is the target while also attaining and maintain-ing a
circular formation of a specific geometric shape; (2) the formation
control systems is capable of self-tuning since the UAV dynamics is
uncertain. In con-trast to known studies, this one uses Lyapunov vector
guidance fields that are di-rection- and magnitude-nonuniform. The
overall cooperative controller structure is based on a decentralized and
centralized consensus. This paper considers two interaction
architectures: an open chain where each UAV only interacts with its
neighbors; and cooperative leader, where the leading UAV is involved in
attain-ing the formation. Using open chain decentralized architecture
allows to have an unlimited number of aircraft in a group, which is in
line with the swarm behavior concept. The cooperative controllers are
self-tuned by fuzzy model reference adaptive control (MRAC). The
approach was tested for efficiency and performance in various scenarios
using complete nonlinear flying-wing UAV models equipped with configured
standard autopilot models.