Multi-UAV Cooperative Target Tracking via Consensus-based Guidance Vector Fields and Fuzzy MRAC
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.