This paper presents a model reference adaptive controller applied to the problem of station-keeping (maintaining relative position) and landing of a fixed-wing UAV onto a maneuvering platform. By retrofitting the aircraft with a side force control surface and utilizing the direct lift control flaps, translational maneuvers without change in pitch and roll attitude can be achieved. The additional controls allow model inversion to be done on all six degrees of freedom. A reference model is proposed such that position and heading can be matched synchronously at touchdown. Our approach differs from the previous works as many researchers did not explicitly address the attitude match problem. The controller is a model reference adaptive controller with a neural network as the adaptive element. Simulation results are presented for two successful cases and three failed cases (which are overly ambitious in practice). The two successful cases are: zero attitude station-keeping with a turning platform, and full 6DOF match landing on a turning platform. The failed cases are: positive pitch descent, large relative heading hold, and station-keeping with a platform with high turn rate.