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A novel approach to flight control laws robustness analysis is presented, aimed at improving the efficiency of the clearance process with respect to conventional techniques, especially when applied to vehicles following time–varying reference trajectories. The approach exploits the convexity of LTV systems, coupled to an approximate description of the original nonlinear system by a certain number of its time-varying linearizations. The method effectiveness and potentials are ascertained by application to the longitudinal flight control laws clearance of the Italian Aerospace Research Center (CIRA) experimental vehicle USV.

Ionospheric delays compensation is a mandatory step for precise absolute and relative positioning of Low Earth Orbit Satellites (LEO) by GPS measurements. The most frequently used ionosphere model for real-time GPS-based navigation in LEO is an isotropic model proposed by Lear, which uses the Vertical Total Electron Content (VTEC) above the receiver and a mapping function for TEC evaluation along a given ray path. Based on significant assessed results available for ground-based GPS receivers, we propose the use of a different model relying on the thin shell assumption and a bilinear horizontal variation of the VTEC as a function of latitude and longitude in the shell. It is expected that this model is capable of better describing horizontal gradients in the ionosphere, thus improving ionospheric delay estimation, especially in intense ionospheric conditions. This model is referred to as Linear Thin Shell (LTS). LTS performance in estimating undifferenced and double-differenced ionospheric delays is checked by comparing measured and predicted delays computed using flight data from the GRACE mission. Results show that the LTS always outperforms the isotropic model, especially in case of high solar activity. Moreover, the LTS model provides a higher performance uniformity over a wide range of ionospheric delays, thus ensuring good performance in different conditions. The results obtained demonstrate that the LTS model improves the ionosphere delays estimation accuracy by 20 and 40% for undifferenced and double-differenced delays, respectively. This suggests the LTS model can effectively contribute to improving precision in LEO positioning applications. © 2018, Springer-Verlag GmbH Germany, part of Springer Nature

A key aspect in the success of a space project is the capability to detect as soon as possible the problems that can arise during the project development. This approach allows to optimise mission reliability, project costs and temporal delays. In this paper a design tool, named PARAN, is proposed for parametric analysis of uncertain systems. This tool can be used in the very early design phase of the system, allowing to define the maximum extent of relevant parameter uncertainty ranges in which required system properties are guaranteed. A system requirement can be often represented by a Boolean property, as a function of a set of relevant design parameters. Given a method for checking that property, PARAN efficiently allows to estimate a multi-dimensional uncertainty region in the parameters space, in which the system satisfies the property. Main feature of the proposed tool lies in the efficient underlying algorithm for finding the uncertainty region, which minimizes the total number of property evaluations. In the paper a case study is presented, applying PARAN to estimate the maximum allowable aerodynamic uncertainty region where the CIRA USV is trimmable and manoeuvrable. Evaluation of PARAN efficiency with respect to usual industrial gridding techniques is reported.

A key aspect in the success of a space project is the capability to detect as soon as possible the problems that can arise during the project development. This approach allows to optimize mission reliability, project costs and temporal delays. As an example, given the extended range of flight regimes experienced by new generation Reusable Launch Vehicles ( RLV ) demonstrators (as NASA’s X-40A, X-43 ) throughout the various mission phases, assessing the impact of the aerodynamic uncertainties on the overall system performance is of great importance. System design should be performed so that uncertainties, with particular concern to the aerodynamics ones, do not significantly affect some basic vehicle properties, such as trajectory trimmability and dynamic stability. Therefore, identifying such admissible ranges of uncertainties might be a powerful system analysis methodology which could effectively help aerodynamics database refinement and system configuration development. A methodology aimed at quantifying the admissible ranges of uncertainties in which relevant vehicle properties can be guaranteed is presented. Specifically, the properties to which we refer are Trimmability and D-Stability of the longitudinal dynamics of an RLV-shaped, un-piloted, un-powered aircraft. The latter is a property wider than simple stability, in order to take into account that vehicle instability is acceptable if the Stability Augmentation System can still enforce the desired dynamics. The approach basically reduces the problem of determining the dynamic characteristics of the complete nonlinear system to an analysis of the robust stability of linear systems subject to uncertain parameters, by means of system’s linearization around a predetermined set of flight conditions. An analytic modeling of the system dynamics is carried out applying the well known Short Period Approximation, and successively deriving the necessary conditions that enforce stability and D-stability conditions as explicit functions of parameters of interest. An application case on a winged, autonomous RLV demonstrator vehicle is analyzed, modeling uncertainties on the vehicle longitudinal aerodynamic stability derivatives. Results have shown the method’s ability to identify the maximum admissible uncertainties, and to address the areas of major concern. Specifically, maximum acceptable uncertainties in terms of CLα and CMα have been identified, and can help to identify the needed level of accuracy in the aerodynamics model. Furthermore, when open-loop stability results are compared to closed-loop ones, indications can be derived on necessary flight control system features, in terms of both robustness and capability to cope with unstable plants.