TY - GEN
T1 - Robust state estimation for jump Markov linear systems with autonomous mode transitions
AU - Li, Wenling
AU - Jia, Yingmin
AU - Meng, Deyuan
PY - 2010
Y1 - 2010
N2 - This paper addresses the robust state estimation problem for a class of jump Markov linear systems (JMLSs) with autonomous mode transitions. By describing the behavior of the autonomous mode transitions as Gaussian forms, we propose a novel robust state estimation algorithm by applying the basic interacting multiple model (IMM) approach and the H∞ estimation technique. Moreover, as the performance of the H∞ estimation depends on a group of weighting parameters, we present a way to tune them recursively. Simulation results show that the proposed algorithm tends to be more effective than the Kalman filtering counterpart when the noise statistics are not known exactly.
AB - This paper addresses the robust state estimation problem for a class of jump Markov linear systems (JMLSs) with autonomous mode transitions. By describing the behavior of the autonomous mode transitions as Gaussian forms, we propose a novel robust state estimation algorithm by applying the basic interacting multiple model (IMM) approach and the H∞ estimation technique. Moreover, as the performance of the H∞ estimation depends on a group of weighting parameters, we present a way to tune them recursively. Simulation results show that the proposed algorithm tends to be more effective than the Kalman filtering counterpart when the noise statistics are not known exactly.
KW - Autonomous mode transition
KW - H filtering
KW - Interacting multiple model
KW - Jump Markov linear system
UR - https://www.scopus.com/pages/publications/78650252714
M3 - 会议稿件
AN - SCOPUS:78650252714
SN - 9787894631046
T3 - Proceedings of the 29th Chinese Control Conference, CCC'10
SP - 1464
EP - 1469
BT - Proceedings of the 29th Chinese Control Conference, CCC'10
T2 - 29th Chinese Control Conference, CCC'10
Y2 - 29 July 2010 through 31 July 2010
ER -