Distributed game strategy for unmanned aerial vehicle formation with external disturbances and obstacles

We investigate a distributed game strategy for unmanned aerial vehicle (UAV) formations with external disturbances and obstacles. The strategy is based on a distributed model predictive control (MPC) framework and Levy flight based pigeon inspired optimization (LFPIO). First, we propose a non-singular fast terminal sliding mode observer (NFTSMO) to estimate the influence of a disturbance, and prove that the observer converges in fixed time using a Lyapunov function. Second, we design an obstacle avoidance strategy based on topology reconstruction, by which the UAV can save energy and safely pass obstacles. Third, we establish a distributed MPC framework where each UAV exchanges messages only with its neighbors. Further, the cost function of each UAV is designed, by which the UAV formation problem is transformed into a game problem. Finally, we develop LFPIO and use it to solve the Nash equilibrium. Numerical simulations are conducted, and the efficiency of LFPIO based distributed MPC is verified through comparative simulations.