Tracking Control of UAV in Formation Based on FHM

Abstract

In order to achieve the goal offormation maintenance, each Unmanned Aerial Vehicle (UAV) tracks the leader aircraft more accurately in formation. A UAV trajectory tracking control method based on Fuzzy Hyperbolic Model (FHM) is proposed to realize the purpose of UAV tracking the leader aircraft quickly and accurately in formation, combining with FHM and back propagation (BP) neural network algorithm. First of all, the dynamics model of single UAV is established, according to the principle of flight mechanics. Secondly, the FHM of UAV tracking leader aircraft was established, combining with the law of flight movement of leader aircraft and the fuzzy control principle. Then the neural network topology of FHM is constructed and the network parameter is identified by gradient descent method. Meanwhile, a UAV trajectory tracking controller based on FHM is designed, which is verified by simulation method. Finally, the simulation results can be seen: When UAV tracks the leader aircraft in a short distance, the convergence speed of control system is high, steady-state error is zero and control energy input is minimal. Therefore, each UAV in formation can track the leader aircraft quickly and accurately through this method, maintaining the same state of movement with the leader aircraft.