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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

AVERAGE REACHABILITY OF CONTINUOUS-TIME MARKOV JUMP LINEAR SYSTEMS AND THE LINEAR MINIMUM MEAN SQUARE ESTIMATOR

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Author(s):
Narvaez, Alfredo R. R. ; Costa, Eduardo F.
Total Authors: 2
Document type: Journal article
Source: SIAM JOURNAL ON CONTROL AND OPTIMIZATION; v. 54, n. 4, p. 2063-2089, 2016.
Web of Science Citations: 1
Abstract

In this paper we study the average reachability gramian for continuous-time linear systems with additive noise and jump parameters driven by a general Markov chain. We define a rather natural reachability concept by requiring that the average reachability gramian be positive definite. Aiming at a testable condition, we introduce a set of reachability matrices for this class of systems and employ invariance properties of the null space of the noise coefficient matrices to show that the system is reachable if and only if these matrices are of full rank. We also show for reachable systems that the state second moment is positive definite. One consequence of this result in the context of linear minimum mean square state estimation for reachable systems is that the expectation of the error covariance matrix is positive definite. Moreover, the average boundedness of the error covariance matrix is invariant to a type of perturbation in the noise model, meaning that the estimates are not overly sensitive, which consists in a property that is desirable in applications and sometimes referred to as stability of the estimator. (AU)

FAPESP's process: 13/19380-8 - Control and filtering of stochastic systems
Grantee:Eduardo Fontoura Costa
Support Opportunities: Regular Research Grants
FAPESP's process: 10/12360-3 - Stability of Kalman filter for stochastic systems
Grantee:Eduardo Fontoura Costa
Support Opportunities: Regular Research Grants