TY - GEN
T1 - Fault diagnosis of spacecraft attitude control system based on dual-strong tracking square-root cubature Kalman filter
AU - Yang, Ze
AU - Ma, Jie
AU - Yang, Baoqing
N1 - Publisher Copyright:
© 2021 Technical Committee on Control Theory, Chinese Association of Automation.
PY - 2021/7/26
Y1 - 2021/7/26
N2 - In order to improve the reliability of the spacecraft system, a fault estimation method based on the dual multiple fading factors strong tracking square-root cubature Kalman filter (Daul-ST-SRCKF) is proposed for the problem of actuator fault diagnosis under the influence of external interference in the spacecraft attitude control system. To ensure the safety and reliability of the spacecraft. First, establish a spacecraft attitude dynamics model considering actuator fault and external disturbance; then, design a ST-SRCKF to observe the states of the system, total disturbance signals to realize the disturbance compensation for another filter system model. And another ST-SRCKF estimate fault information, two filters can exchange parameters to form a Daul-ST-SRCKF; Finally, Simulation results show that this method can quickly and accurately identify fault information and complete health assessment under the presence of internal and external disturbances.
AB - In order to improve the reliability of the spacecraft system, a fault estimation method based on the dual multiple fading factors strong tracking square-root cubature Kalman filter (Daul-ST-SRCKF) is proposed for the problem of actuator fault diagnosis under the influence of external interference in the spacecraft attitude control system. To ensure the safety and reliability of the spacecraft. First, establish a spacecraft attitude dynamics model considering actuator fault and external disturbance; then, design a ST-SRCKF to observe the states of the system, total disturbance signals to realize the disturbance compensation for another filter system model. And another ST-SRCKF estimate fault information, two filters can exchange parameters to form a Daul-ST-SRCKF; Finally, Simulation results show that this method can quickly and accurately identify fault information and complete health assessment under the presence of internal and external disturbances.
KW - cubature Kalman filter
KW - disturbance estimation
KW - fault detection and diagnosis
KW - health management
KW - multiple fading factors
KW - spacecraft attitude control system
UR - https://www.scopus.com/pages/publications/85117318319
U2 - 10.23919/CCC52363.2021.9550015
DO - 10.23919/CCC52363.2021.9550015
M3 - 会议稿件
AN - SCOPUS:85117318319
T3 - Chinese Control Conference, CCC
SP - 4630
EP - 4635
BT - Proceedings of the 40th Chinese Control Conference, CCC 2021
A2 - Peng, Chen
A2 - Sun, Jian
PB - IEEE Computer Society
T2 - 40th Chinese Control Conference, CCC 2021
Y2 - 26 July 2021 through 28 July 2021
ER -