QUEST-Based Kalman Filter and LQR for Satellite Attitude Control
- Resource Type
- Conference
- Authors
- Mwema, Moise; Hashim, Hashim A.
- Source
- 2022 10th International Conference on Control, Mechatronics and Automation (ICCMA) Control, Mechatronics and Automation (ICCMA), 2022 10th International Conference on. :135-141 Nov, 2022
- Subject
- Robotics and Control Systems
Satellites
Attitude control
Quaternions
Estimation
Position measurement
Mathematical models
Sensors
Kalman filter
linear-quadratic regulator
quaternion estimator
stability
low earth orbit satellite
- Language
This paper presents the design and implementation of accurate attitude estimation and control using low-cost Inertial Measurement Unit (IMU) sensors based on a satellite quaternion model. Mathematical models of the proposed algorithms are outlined and discussed extensively. A two-step optimal estimator from vector observations is proposed. QUEST algorithm is used to produce simultaneous non-collinear vector measurements of the sensors which are then fed into the Kalman filter to obtain better attitude estimates. Linear-Quadratic Regulator control is implemented using a reduced quaternion satellite model. Simulation results show that the two-step filter approach performs satisfactorily in eliminating the bias and error that is present in IMU sensor measurements. The optimal attitude is used to simulate quaternion-based attitude and angular velocity responses to LQR. The results show that the control strategy performs satisfactorily in making sure that there is a minor difference between the reference input attitude and estimated attitude (from the Kalman filter).