Abstract
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.
Highlights
The dream of controlled flight was first realized by the invention of the airship, where it is claimed that Jean-Baptiste Meusnier designed the first airship in 1748 [1]; it lacked a lightweight, powerful engine
The work presented here focuses on the design of a sub-optimal gain-scheduled feedback control law based on linear quadratic (LQ) methods
The simulation is initialized with the airship at the origin of the inertial frame; the airship will travel to four pre-programmed waypoints until it has visited each one
Summary
The dream of controlled flight was first realized by the invention of the airship, where it is claimed that Jean-Baptiste Meusnier designed the first airship in 1748 [1]; it lacked a lightweight, powerful engine. The work presented here focuses on the design of a sub-optimal gain-scheduled feedback control law based on linear quadratic (LQ) methods. This controller is expected to fly the airship through a series of planar waypoints based on commands generated by a track-specific navigation algorithm. This is not always true in reality, where some states may not be available by measurement This issue is addressed in the work presented in this paper by designing and implementing a novel scheduled extended Kalman filter (SEKF) to estimate the required states for control and navigation with a minimal sensor suite on-board the airship. The results obtained from this research are introduced and discussed to formulate a conclusive argument
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