Ricerc@Sapienza

Aerospace vehicles often encounter challenging mission scenarios. These represent critical phases that determine the satisfactory achievement of the mission objectives, and, sometimes, the outcome of the entire mission. This research project is intended to develop and apply an effective methodology for real-time guidance and control of aerospace vehicles, based on nonlinear control theory and techniques. Potential challenging scenarios include (a) precise orbit control for low-altitude space vehicles dedicated to monitoring or surface mapping, (b) docking maneuvers between two cooperating or non-cooperating spacecraft, and (c) safe planetary landing of unmanned vehicles. High-fidelity dynamical modeling represents a crucial issue for investigating the critical phases of aerospace missions. In this research project, the environment and vehicle parameters are being identified, together with the related uncertainties. Constraints and quantization of control actuators introduce further complexity and are being included in the dynamical modeling through original geometric and analytic approaches. Moreover, this research aims at selecting the representations and governing equations (for trajectory and attitude) that are most advantageous in relation to the specific application. In fact, a suitable choice of variables offers a deep insight on the natural dynamical evolution of the aerospace system of interest and can facilitate considerably the design of the nonlinear control algorithm. With this regard, sliding mode control appears as a very promising option among the nonlinear techniques proposed in recent years. The performance of the nonlinear guidance and control algorithms being developed in this research will be tested using high-fidelity modeling of both the environment and the aerospace vehicle, with the final objective of demonstrating their accuracy and robustness, even in the presence of large deviations from nominal flight conditions.