Paper Title
STATE AND PARAMETER ESTIMATION ARCHITECTURE FOR QUAD-ROTOR TAIL-SITTER VTOL UAV

Abstract
In this paper, we present a novel architecture for state and parameter estimation of a quad-rotor tail-sitter VTOL UAV. The proposed approach utilizes multiplier matrices, data-driven concurrent learning, and an adaptive observer to improve the control and navigation of tail-sitter VTOL UAVs. Under certain excitation conditions, the parameter estimation error is guaranteed to converge to a given neighborhood of the origin. Keywords - State estimation, parameter estimation, quad-rotor tail-sitter VTOL UAV, Extended Luenberger Nonlinear Observers