Automatica, Vol.47, No.7, 1520-1524, 2011
Robust state estimation for uncertain discrete-time stochastic systems with missing measurements
In this paper, results of robust estimation of Zhou (2010a) are extended to state estimation with missing measurements. A new procedure is derived which inherits the main properties of that of Zhou (2010a). In this extension, a covariance matrix used in the recursions is replaced by its estimate which makes its asymptotic property investigation mathematically difficult. Though introducing a monotonic function and using the so-called squeeze rule, this new robust estimator is proved to converge to a stable system. Numerical simulation results indicate that the proposed estimator may have an estimation accuracy better than the estimator of Wang, Yang, Daniel, and Liu (2005). (C) 2011 Elsevier Ltd. All rights reserved.
Keywords:Recursive state estimation;Sensitivity penalization;Data missing;Riccati equation;Convergence property