Avionic air data sensors fault detection and isolation by means of singular perturbation and geometric approach

Singular Perturbations represent an advantageous theory to deal with systems characterized by a two-time scale separation, such as the longitudinal dynamics of aircraft which are called phugoid and short period. In this work, the combination of the NonLinear Geometric Approach and the Singular Perturbations leads to an innovative Fault Detection and Isolation system dedicated to the isolation of faults affecting the air data system of a general aviation aircraft. The isolation capabilities, obtained by means of the approach proposed in this work, allow for the solution of a fault isolation problem otherwise not solvable by means of standard geometric techniques. Extensive Monte-Carlo simulations, exploiting a high fidelity aircraft simulator, show the effectiveness of the proposed Fault Detection and Isolation system.Singular Perturbations represent an advantageous theory to deal with systems characterized by a two-time scale separation, such as the longitudinal dynamics of aircraft which are called phugoid and short period. In this work, the combination of the NonLinear Geometric Approach and the Singular Perturbations leads to an innovative Fault Detection and Isolation system dedicated to the isolation of faults affecting the air data system of a general aviation aircraft. The isolation capabilities, obtained by means of the approach proposed in this work, allow for the solution of a fault isolation problem otherwise not solvable by means of standard geometric techniques. Extensive Monte-Carlo simulations, exploiting a high fidelity aircraft simulator, show the effectiveness of the proposed Fault Detection and Isolation system

Nonconvex Distributed Feedback Optimization for Aggregative Cooperative Robotics

Distributed aggregative optimization is a recently emerged framework in which the agents of a network want to minimize the sum of local objective functions, each one depending on the agent decision variable (e.g., the local position of a team of robots) and an aggregation of all the agents' variables (e.g., the team barycentre). In this paper, we address a distributed feedback optimization framework in which agents implement a local (distributed) policy to reach a steady-state minimizing an aggregative cost function. We propose Aggregative Tracking Feedback, i.e., a novel distributed feedback optimization law in which each agent combines a closed-loop gradient flow with a consensus-based dynamic compensator reconstructing the missing global information. By using tools from system theory, we prove that Aggregative Tracking Feedback steers the network to a stationary point of an aggregative optimization problem with (possibly) nonconvex objective function. The effectiveness of the proposed method is validated through numerical simulations on a multi-robot surveillance scenario

Uniform quasi-convex optimisation via Extremum Seeking

The paper deals with a well-known extremum seeking scheme by proving uniformity properties with respect to the amplitudes of the dither signal and of the cost function. Those properties are then used to show that the scheme guarantees the global minimiser to be semi-global practically stable despite the presence of local saddle points. To achieve these results, we analyse the average system associated with the extremum seeking scheme via arguments based on the Fourier series

NLGA based Active Control in Aerospace: fault tolerability, disturbance rejection, and parameter estimation

A new control scheme has been presented in this thesis. Based on the NonLinear Geometric Approach, the proposed Active Control System represents a new way to see the reconfigurable controllers for aerospace applications. The presence of the Diagnosis module (providing the estimation of generic signals which, based on the case, can be faults, disturbances or system parameters), mean feature of the depicted Active Control System, is a characteristic shared by three well known control systems: the Active Fault Tolerant Controls, the Indirect Adaptive Controls and the Active Disturbance Rejection Controls. The standard NonLinear Geometric Approach (NLGA) has been accurately investigated and than improved to extend its applicability to more complex models. The standard NLGA procedure has been modified to take account of feasible and estimable sets of unknown signals. Furthermore the application of the Singular Perturbations approximation has led to the solution of Detection and Isolation problems in scenarios too complex to be solved by the standard NLGA. Also the estimation process has been improved, where multiple redundant measuremtent are available, by the introduction of a new algorithm, here called "Least Squares - Sliding Mode". It guarantees optimality, in the sense of the least squares, and finite estimation time, in the sense of the sliding mode. The Active Control System concept has been formalized in two controller: a nonlinear backstepping controller and a nonlinear composite controller. Particularly interesting is the integration, in the controller design, of the estimations coming from the Diagnosis module. Stability proofs are provided for both the control schemes. Finally, different applications in aerospace have been provided to show the applicability and the effectiveness of the proposed NLGA-based Active Control System

Isolation and functional characterization of a high affinity urea transporter from roots of Zea mays

Background Despite its extensive use as a nitrogen fertilizer, the role of urea as a directly accessible nitrogen source for crop plants is still poorly understood. So far, the physiological and molecular aspects of urea acquisition have been investigated only in few plant species highlighting the importance of a high-affinity transport system. With respect to maize, a worldwide-cultivated crop requiring high amounts of nitrogen fertilizer, the mechanisms involved in the transport of urea have not yet been identified. The aim of the present work was to characterize the high-affinity urea transport system in maize roots and to identify the high affinity urea transporter. Results Kinetic characterization of urea uptake (<300 \u3bcM) demonstrated the presence in maize roots of a high-affinity and saturable transport system; this system is inducible by urea itself showing higher Vmax and Km upon induction. At molecular level, the ORF sequence coding for the urea transporter, ZmDUR3, was isolated and functionally characterized using different heterologous systems: a dur3 yeast mutant strain, tobacco protoplasts and a dur3 Arabidopsis mutant. The expression of the isolated sequence, ZmDUR3-ORF, in dur3 yeast mutant demonstrated the ability of the encoded protein to mediate urea uptake into cells. The subcellular targeting of DUR3/GFP fusion proteins in tobacco protoplasts gave results comparable to the localization of the orthologous transporters of Arabidopsis and rice, suggesting a partial localization at the plasma membrane. Moreover, the overexpression of ZmDUR3 in the atdur3-3 Arabidopsis mutant showed to complement the phenotype, since different ZmDUR3-overexpressing lines showed either comparable or enhanced 15[N]-urea influx than wild-type plants. These data provide a clear evidence in planta for a role of ZmDUR3 in urea acquisition from an extra-radical solution. Conclusions This work highlights the capability of maize plants to take up urea via an inducible and high-affinity transport system. ZmDUR3 is a high-affinity urea transporter mediating the uptake of this molecule into roots. Data may provide a key to better understand the mechanisms involved in urea acquisition and contribute to deepen the knowledge on the overall nitrogen-use efficiency in crop plants