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This paper deals with the control of lighter-than-air vehicles, more specifically the design of an integrated guidance, navigation and control (GNC) scheme that is capable of navigating an airship through a series of constant-altitude, planar waypoints. Two guidance schemes are introduced, a track-specific guidance law and a proportional navigation guidance law, that provide the required signals to the corresponding controllers based on the airship position relative to a target waypoint. A novel implementation of the extended Kalman filter, namely the scheduled extended Kalman filter, estimates the required states and wind speed to enhance the performance of the track-specific guidance law in the presence of time-varying wind. The performance of the GNC system is tested using a high fidelity nonlinear dynamic simulation for a variety of flying conditions. Representative results illustrate the performance of the integrated system for chosen flight conditions.

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An automatic landing system for an unmanned aerial vehicle (UAV) is presented in the following paper. The nonlinear aircraft model with thrust, elevator, rudder and aileron deflections as control inputs is established using the appropriate aerodynamic data. The flight trajectory the airplane is expected to travel during landing is then defined. A nonlinear control law, using feedback linearization method, is designed to develop the automatic landing controller for the UAV aircraft. A linear state-feedback control law is also designed for means of comparison with the nonlinear controller. The elevator is employed for longitudinal control whereas the rudder and aileron aid in lateral control. Thrust is the control input for velocity control, which is held constant during landing. A nonlinear simulation, incorporating wind shear and ground effects, is run using MATLAB/Simulink to assess the controllers’ integrity. The auto-landing system designed in this paper is meant to increase the autonomy of the UAV to eventually reach a fully autonomous system. Simulation results show the importance of designing the controller considering such effects. Landing trajectory tracking performance by the nonlinear controller is of great tone.

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