  This paper presents a solution for the state estimation and control problems
for a class of unconventional vertical takeoff and landing (VTOL) UAVs
operating in forward-flight conditions. A tightly-coupled state estimation
approach is used to estimate the aircraft navigation states, sensor biases, and
the wind velocity. State estimation is done within a matrix Lie group framework
using the Invariant Extended Kalman Filter (IEKF), which offers several
advantages compared to standard multiplicative EKFs traditionally used in
aerospace and robotics problems. An SO(3)- based attitude controller is
employed, leading to a single attitude control law without a separate sideslip
control loop. A control allocator is used to determine how to use multiple,
possibly redundant, actuators to produce the desired control moments. The wind
velocity estimates are used in the attitude controller and the control
allocator to improve performance. A numerical example is considered using a
sample VTOL tailsitter-type UAV with four control surfaces. Monte-Carlo
simulations demonstrate robustness of the proposed control and estimation
scheme to various initial conditions, noise levels, and flight trajectories.
