TY - GEN
T1 - An adaptive predictor-corrector entry guidance law based on online parameter estimation
AU - Li, Wei Jie
AU - Sun, Si Hao
AU - Shen, Zuo Jun
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2017/1/20
Y1 - 2017/1/20
N2 - Due to the rapid improvement of the onboard computation capabilities, lots of novel entry guidance methods have appeared, of which numerical predictor-corrector algorithms have got a lot of attention and research. However, the properties of the predictor-corrector algorithms are vulnerable to the perturbation of the atmospheric density and aerodynamic parameters such as the lift and drag coefficient, which means that the algorithms highly depend on the model correctness. In this paper, an online identification method based on extended Kalman filter is used to estimate the uncertain parameters in reentry flight of X-33, which is of great value to reconfigure an auto-adaptive predictor-corrector guidance law. The Monte Carlo simulations show that the uncertainties in atmospheric density and aerodynamic parameters are estimated and an auto-adaptive guidance law is reconfigured successfully, which make great contributions to the satisfaction of the constraints in the presence of significant dispersions.
AB - Due to the rapid improvement of the onboard computation capabilities, lots of novel entry guidance methods have appeared, of which numerical predictor-corrector algorithms have got a lot of attention and research. However, the properties of the predictor-corrector algorithms are vulnerable to the perturbation of the atmospheric density and aerodynamic parameters such as the lift and drag coefficient, which means that the algorithms highly depend on the model correctness. In this paper, an online identification method based on extended Kalman filter is used to estimate the uncertain parameters in reentry flight of X-33, which is of great value to reconfigure an auto-adaptive predictor-corrector guidance law. The Monte Carlo simulations show that the uncertainties in atmospheric density and aerodynamic parameters are estimated and an auto-adaptive guidance law is reconfigured successfully, which make great contributions to the satisfaction of the constraints in the presence of significant dispersions.
UR - https://www.scopus.com/pages/publications/85015253586
U2 - 10.1109/CGNCC.2016.7829045
DO - 10.1109/CGNCC.2016.7829045
M3 - 会议稿件
AN - SCOPUS:85015253586
T3 - CGNCC 2016 - 2016 IEEE Chinese Guidance, Navigation and Control Conference
SP - 1692
EP - 1697
BT - CGNCC 2016 - 2016 IEEE Chinese Guidance, Navigation and Control Conference
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 7th IEEE Chinese Guidance, Navigation and Control Conference, CGNCC 2016
Y2 - 12 August 2016 through 14 August 2016
ER -