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Energy optimal 3D target tracking using fixed-wing UAV

Fixed-wing unmanned aerial vehicles (UAVs) can be used for target tracking applications in urban regions. Developing a target tracking controller for fixed-wing vehicle in urban regions is challenging due to limited energy, obstacle avoidance, visibility restrictions due to obstacles, finite camera field-of-view, and unknown target motion. This paper presents an economic model predictive controller (EMPC) that tracks the target efficiently while addressing all the mentioned challenges. The EMPC enables energy minimization while maximizing the tracking performance. The EMPC performance is validated through simulations by comparing with a MPC controller and a greedy approach. The results show that the controller tracks the target efficiently with no loss of target sight and consumed three times less energy than MPC. The greedy tracking strategy is unable to track the target persistently.