System Modeling & Control

Guidance, Navigation and Control for AeroSpace

In the aerospace field, Guidance, Navigation and Control (GNC) is the engineering branch focused on the design of systems to control the movement of aeronautical and space vehicles: navigation for assessing position, velocity and attitude of a vehicle at a given time instant, guidance for determining vehicle reference trajectory, and control for the application of forces and torques needed to apply guidance commands and to maintain the vehicle stability. The SMC group has applied its competences on Robotics and Automatics  to the aerospace field developing nonlinear, adaptive, robust, stochastic and randomized algorithms to guarantee operative and safety constraints fulfillment despite the presence of internal/external disturbance sources, and environmental, geometrical and model uncertainties, and to ensure computational compatibility with the hardware capabilities onboard satellites or UAVs. In particular, the group focused on the definition of optimal trajectories for planetary landing or precision agricultural operational scenario for UAVs, trajectory tracking for drones during urban surveillance, monitoring over risky areas, and remote-sensing for agriculture applications, orbit and attitude maintenance during autonomous rendezvous and proximity operations between satellites, fault detection and monitoring of complex systems, co-design of aerospace systems and control laws to optimize aircraft performance or operations to be carried out. Furthermore, typical concepts of automatic controls have been translated into the field of point clouds to obtain simplified polytopic maps that are computationally light to be used in real time on board of UAVs.

References:

  • E. Capello, E. Punta, F. Dabbene, G. Guglieri, R. Tempo, “Sliding-mode control strategies for rendezvous and docking maneuvers”, in Journal of Guidance, Control, and Dynamics, 2017.
  • M. Mammarella, E. Capello, F. Dabbene, G. Guglieri, “Sample-Based SMPC for Tracking Control of Fixed-Wing UAV”, in IEEE Control Systems Letters, 2018.
  • M. Mammarella, M. Lorenzen, E. Capello, H. Park, F. Dabbene, G. Guglieri, M. Romano, F. Allgöwer, “An Offline-Sampling SMPC Framework with Application to Autonomous Space Maneuvers”, in IEEE Transactions of Control Systems Technology, 2019.
  • M. Mancini, N. Bloise, E. Capello, E. Punta, “Sliding mode control techniques and artificial potential field for dynamic collision avoidance in rendezvous maneuvers”, in IEEE Control Systems Letters, 2020.
  • L. Comba, S. Zaman, A. Biglia, D. Ricauda Aimonino, F. Dabbene, P. Gay, “Semantic interpretation and complexity reduction of 3D point clouds of vineyards”, in Biosystems Engineering, 2020.

Projects: LISA | AgriDrones