Session
Session VI: Advanced Technology 3-Enterprise
Location
Salt Palace Convention Center, Salt Lake City, UT
Abstract
Small satellite missions in low Earth orbit (LEO) can utilize propellant-free aerodynamic drag for maneuvering, but achieving precise orbit control is challenged by non-linearities and uncertainties. This paper proposes a nonlinear model predictive control (NMPC) framework designed for precise trajectory tracking under these conditions. By focusing on following a given reference path, our NMPC controller overcomes time-varying perturbations (e.g., J2, J3, J4 effects). We validated this tracking-focused approach with simulations incorporating stochastic atmospheric models. Monte Carlo analysis, using controlled de-orbiting profiles as reference trajectories, demonstrates that our NMPC system provides a powerful tool for enabling precise, propellant-free maneuvers. This work presents an effective solution for small satellite missions where following a pre-defined path with high fidelity is critical.
Document Type
Event
Development of Model Predictive Control Approach for Precise De-Orbit of Nanosatellite Using Aerodynamic Drag
Salt Palace Convention Center, Salt Lake City, UT
Small satellite missions in low Earth orbit (LEO) can utilize propellant-free aerodynamic drag for maneuvering, but achieving precise orbit control is challenged by non-linearities and uncertainties. This paper proposes a nonlinear model predictive control (NMPC) framework designed for precise trajectory tracking under these conditions. By focusing on following a given reference path, our NMPC controller overcomes time-varying perturbations (e.g., J2, J3, J4 effects). We validated this tracking-focused approach with simulations incorporating stochastic atmospheric models. Monte Carlo analysis, using controlled de-orbiting profiles as reference trajectories, demonstrates that our NMPC system provides a powerful tool for enabling precise, propellant-free maneuvers. This work presents an effective solution for small satellite missions where following a pre-defined path with high fidelity is critical.
