Finite Memory Output Feedback Control for Unmanned Aerial Vehicle

In this paper, we propose a novel control strategy, a finite memory output feedback control (FMOFC), for an unmanned aerial vehicle (UAV). The proposed control strategy is designed with the estimated states obtained by stacking a finite N number of measurements, and the finite N number is defined as the horizon size, which represents the finite memory structure of the system. Through extending the concept of the horizon size by introducing a vector form to the augmented horizon size, the UAV is considered as a parallel system in terms of four independent states. Furthermore, the controller gain of the FMOFC is derived from the reconstructed parallel system under not only the finite memory structure, but also unbiasedness. Because of those constraints, the FMOFC exhibits a robust performance even in the presence of disturbance or unexpected noises from uncertainties, computational errors, and sudden changes in environments. The fast convergence and robust performance under disturbance or unexpected noises of the proposed control strategy are demonstrated through experimental results.