Decentralized Modular Hybrid Supervisory Control for the Formation of Unmanned Helicopters

This paper presents a collision-free decentralized hybrid supervisory control approach for the Unmanned Aerial Vehicles (UAVs) that are involved in a leader-follower formation mission. Towards this end, a symbolic motion planning scheme is developed to polarly partition the motion space, which results in a finite state discrete model for the motion dynamics of each UAV. Then, a modular discrete supervisor is designed for different components of the formation mission including reaching the formation, keeping the formation, and collision avoidance. While for reaching and keeping the formation, each UAV can satisfy the desired performance independently, for the collision avoidance, a tight cooperation of the UAVs is required. For this purpose, a top-down technique is developed to design the local supervisors decentralizedly, so that the locally supervised distributed agents, as a whole, can cooperatively satisfy the desired specification. The proposed decentralized supervisory algorithm is verified through a hardwarein-the-loop simulator for the formation control of unmanned helicopters.