TY - GEN
T1 - Uncertain parameters identification based on hierarchical adaptive filters during Mars entry
AU - Wang, Liansheng
AU - Xia, Yuanqing
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/7/7
Y1 - 2016/7/7
N2 - The uncertain parameters exist in Mars entry have a significant effect on Mars entry navigation. In this paper, the hierarchical adaptive filter regulated by a gating network is presented to identify the uncertain parameters during Mars entry, which are atmosphere density, lift over drag ratio and ballistic coefficient. The hierarchical structure is composed of several bank of filters, and each bank of filters is composed of several experts running in parallel. Each expert is a realization of some parameter values. The gating network can adaptively assign appropriate weights to the filter banks and the experts. The weight which is close to unity corresponding to certain expert means that the given parameter value is close to the real value or is right the real value. By this way, the uncertain parameters can be identified. Also the effect of learning rate factor on the convergence rate of gating weights and the identification capability is demonstrated. The effectiveness of this method can be illustrated by the case of Mars entry navigation.
AB - The uncertain parameters exist in Mars entry have a significant effect on Mars entry navigation. In this paper, the hierarchical adaptive filter regulated by a gating network is presented to identify the uncertain parameters during Mars entry, which are atmosphere density, lift over drag ratio and ballistic coefficient. The hierarchical structure is composed of several bank of filters, and each bank of filters is composed of several experts running in parallel. Each expert is a realization of some parameter values. The gating network can adaptively assign appropriate weights to the filter banks and the experts. The weight which is close to unity corresponding to certain expert means that the given parameter value is close to the real value or is right the real value. By this way, the uncertain parameters can be identified. Also the effect of learning rate factor on the convergence rate of gating weights and the identification capability is demonstrated. The effectiveness of this method can be illustrated by the case of Mars entry navigation.
UR - https://www.scopus.com/pages/publications/84980385837
U2 - 10.1109/VSS.2016.7506947
DO - 10.1109/VSS.2016.7506947
M3 - Conference contribution
AN - SCOPUS:84980385837
T3 - Proceedings of IEEE International Workshop on Variable Structure Systems
SP - 373
EP - 378
BT - 2016 14th International Workshop on Variable Structure Systems, VSS 2016
PB - IEEE Computer Society
T2 - 14th International Workshop on Variable Structure Systems, VSS 2016
Y2 - 1 June 2016 through 4 June 2016
ER -