Development of autonomous uninhibited aircraft, so called flying robots in the form of Micro Aerial Vehicles (MAVs) outfitted with autonomous autopilot controller has progressed quickly in recent years, and interest in this field continue to spread. Autopilot basically has two functionality 1) It will stabilize the plant in case it is perturbed due to some disturbances or uncertainties. 2) It will guide the MAV through a predefined path for a particular mission requirement. In this paper we propose a methodology for robust stabilization of MAVs using riccati type formulation. A nonlinear MAV model has been linearized at various operating conditions. A nominal model has been chosen among those linear models and variations from the nominal model are modeled in the from of unmatched parametric uncertainty and a robust sliding surface is designed. Design of robust sliding hyperplanes in the presence of parametric uncertainty is based on quadratic stability. The search of Lyapunov matrix along with constraints for unmatched uncertainties is formulated in terms of linear matrix inequality (LMI) which enables robust linear sliding surface design. A robust sliding controller using the linear sliding hyperplane is designed for the complete nonlinear plant model. Simulation results are done using nonlinear equations of motions to demonstrate the proposed methodology for MAVs. © 2012 IEEE.