Abstract
The current development process especially of small unmanned aircraft systems from automatic to semi-autonomous or even fully autonomous behaviour demands reliable and precise navigation solutions as well as robust control strategies. For a truly autonomous system adequate as well as secure reactions towards nonlinearities arising for example from unknown environmental conditions or system damages are a prerequisite. An adaptive flight control system, which has to cancel the undesirable effects of such disturbances, depends on constantly available accurate navigation data. To satisfy these boundary conditions, it is sensible to stronger intertwine the development process of miniaturised navigation systems and adaptive flight controllers. As the controller design and its validation is based on nonlinear simulations, it is advisable to model the integrated navigation system and its low-cost components in a detailed way, so that its distinct dynamic properties can already be taken into account during the development process of the controller. In this context, a tightly coupled integrated navigation scheme is presented, where the characteristics of the sensor components are identified and modelled using the Allan variance analysis. This information can be used during the validation process of the proposed adaptive flight control system, which is based on the concept of nonlinear dynamic inversion combined with artificial neural networks. This paper gives an overview on how miniaturised navigation systems can be modelled and utilised for adaptive flight control schemes of small unmanned aircraft.
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Vörsmann, P., Kaschwich, C., Krüger, T. et al. MEMS based integrated navigation systems for adaptive flight control of unmanned aircraft — State of the art and future developments. Gyroscopy Navig. 3, 235–244 (2012). https://doi.org/10.1134/S2075108712040116
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DOI: https://doi.org/10.1134/S2075108712040116