Cooperative tracking for a swarm of Unmanned Aerial Vehicles: A distributed Tagaki-Sugeno fuzzy framework design

This paper focuses on a systematic analysis for the tracking problem in swarm-based missions for Unmanned Aerial Vehicles (UAVs) with linear and angular velocity constraints. In this paper the nonlinear model of the dynamics are represented by Takagi-Sugeno (TS) fuzzy models. A distributed control law is introduced which is composed of both node and network level information. Firstly feedback gains are synthesised for the isolated UAVs ignoring interconnections. The resulting common Lyapunov matrix is utilised at network level, to incorporate into the control law the relative differences in the states of the agents, to induce cooperative behaviour. Eventually stability is guaranteed for the entire swarm. The control synthesis is all performed subject to design criteria, posed as Linear Matrix Inequalities (LMIs). An illustrative example based on a UAV tracking scenario is included to outline the potential of the analysis.