Kalman filter-based model predictive control for drag-free satellite under actuator failures and input saturations

Area of Science:

• Aerospace Engineering
• Control Systems Theory
• Satellite Dynamics

Background:

• Drag-free satellites require precise control to counteract external forces.
• Actuator failures and input saturations pose significant challenges to satellite control systems.
• Existing control methods may not adequately address the combined effects of faults and disturbances.

Purpose of the Study:

• To develop a fault-tolerant control strategy for drag-free satellites.
• To address actuator failures and input saturation issues.
• To enhance system robustness against measurement noise and external disturbances.

Main Methods:

• A Kalman filter-based model predictive control (MPC) approach is proposed.
• A dynamic model of the drag-free satellite is developed.
• A fault-tolerant design scheme is integrated with the Kalman filter and MPC.

Main Results:

• The proposed controller effectively handles actuator failures and input saturation.
• The system demonstrates enhanced robustness against measurement noise and external disturbances.
• Numerical simulations validate the correctness and effectiveness of the fault-tolerant control method.

Conclusions:

• The Kalman filter-based MPC offers a viable solution for fault-tolerant control of drag-free satellites.
• The developed method guarantees system robustness and overcomes actuator limitations.
• This approach is crucial for maintaining the operational integrity of drag-free satellite missions.