4.4 Article

New Approach to H∞ State Estimation for Continuous-Time Nonhomogeneous Markov Jump Systems with Time-Varying Delay

Journal

CIRCUITS SYSTEMS AND SIGNAL PROCESSING
Volume 41, Issue 8, Pages 4390-4412

Publisher

SPRINGER BIRKHAUSER
DOI: 10.1007/s00034-022-01995-8

Keywords

Switched vertices approach; State estimation; Markov jump systems; Nonhomogeneous transition rates

Funding

  1. National Natural Science Foundation of China [61973070]
  2. Liaoning Revitalization Talents Program [XLYC1802010]
  3. SAPI Fundamental Research Funds [2018ZCX22]
  4. Fundamental Research Funds for the Central Universities [N2104003]

Ask authors/readers for more resources

This paper investigates the H-infinity state estimation problem of continuous-time delayed nonhomogeneous Markov jump systems and proposes a switched vertices approach to relax the bound assumptions, resulting in more practical results.
This paper investigates the H-infinity state estimation problem of continuous-time delayed nonhomogeneous Markov jump systems (NMJSs). To fully consider the nonhomogeneous transition rates (TRs) and state-related vectors, a parameter-dependent Lyapunov-Krasovskii functional (PDLKF) with triple integrals is constructed, in which the integrands in the PDLKF are all time-varying. In order to deal with the derivative of the time-varying integrands, a switched vertices approach is proposed to relax the bound assumptions in the existing works, which leads to more practical results. Based on these ingredients, a corresponding switched estimator approach is proposed to match an H-infinity estimator for NMJSs. The designed H-infinity estimator is related to the switched rule, which is more general than nonswitched estimators in the previous works. Some examples are illustrated to show the effectiveness of the obtained results.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.4
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available