Session
Poster Session 1
Location
Salt Palace Convention Center, Salt Lake City, UT
Abstract
This work explores the use of online estimation techniques to enhance advanced thruster-only attitude control strategies. Classical fixed-gain feedback control and newer model predictive control (MPC) based approaches all suffer from reduced efficiency or performance when the system parameters deviate from their nominal values. By incorporating optimal estimation techniques, this can be avoided and deviations from nominal values can be leveraged for fault detection, isolation, and recovery (FDIR).
Specifically, this work investigates the use of extended Kalman filters (EKF) to estimate parameters such as thruster torque and disturbances in real time, using satellite attitude measurements and known control inputs. In addition to providing nominal parameter estimates, this approach also yields uncertainty estimates, which can be used to provide stochastic robustness guarantees.
High-fidelity simulations are performed with varying levels of noise introduced, and using a variety of different fine pointing and slewing attitude control schemes, to assess the effectiveness of the developed adaptive parameter estimation techniques. This is done by studying the effects on total propellant use, stability of control algorithms, and the convergence of the parameter estimates.
Document Type
Event
Efficient Adaptive Thruster Control Strategies for Nanosatellite Attitude Control
Salt Palace Convention Center, Salt Lake City, UT
This work explores the use of online estimation techniques to enhance advanced thruster-only attitude control strategies. Classical fixed-gain feedback control and newer model predictive control (MPC) based approaches all suffer from reduced efficiency or performance when the system parameters deviate from their nominal values. By incorporating optimal estimation techniques, this can be avoided and deviations from nominal values can be leveraged for fault detection, isolation, and recovery (FDIR).
Specifically, this work investigates the use of extended Kalman filters (EKF) to estimate parameters such as thruster torque and disturbances in real time, using satellite attitude measurements and known control inputs. In addition to providing nominal parameter estimates, this approach also yields uncertainty estimates, which can be used to provide stochastic robustness guarantees.
High-fidelity simulations are performed with varying levels of noise introduced, and using a variety of different fine pointing and slewing attitude control schemes, to assess the effectiveness of the developed adaptive parameter estimation techniques. This is done by studying the effects on total propellant use, stability of control algorithms, and the convergence of the parameter estimates.
