Skip to Main content Skip to Navigation
Conference papers

Hybrid Descriptor System State Estimation through an IMM Approach

Liangquan Zhang 1 Qinghua Zhang 1, 2
1 I4S - Statistical Inference for Structural Health Monitoring
Inria Rennes – Bretagne Atlantique , IFSTTAR/COSYS - Département Composants et Systèmes
Abstract : Stochastic hybrid systems have been largely studied in the literature in the framework of Markov mode transitions and linear Gaussian state space mode models. In order to generalize such results to hybrid systems involving phenomena characterized by differential-algebraic equations, this paper studies the problem of state estimation for stochastic hybrid systems with modes described by descriptor equations. The proposed state estimation algorithm follows the interacting multiple model (IMM for short) approach, but the classical state space system Kalman filters are replaced by descriptor system Kalman filters. Because of the difficulty for computing the innovation of each descriptor system Kalman filter, a new method for likelihood evaluation is proposed, as one important step of the new IMM algorithm. Numerical examples are presented to illustrate the performance of the proposed algorithm.
Document type :
Conference papers
Complete list of metadata

Cited literature [12 references]  Display  Hide  Download

https://hal.inria.fr/hal-01232174
Contributor : Qinghua Zhang <>
Submitted on : Monday, November 23, 2015 - 10:45:56 AM
Last modification on : Tuesday, December 8, 2020 - 10:20:37 AM
Long-term archiving on: : Wednesday, February 24, 2016 - 11:21:15 AM

File

SYSID2015_hybrid.pdf
Files produced by the author(s)

Identifiers

  • HAL Id : hal-01232174, version 1

Collections

Citation

Liangquan Zhang, Qinghua Zhang. Hybrid Descriptor System State Estimation through an IMM Approach. 17th IFAC Symposium on System Identification (SYSID), Oct 2015, Beijing, China. ⟨hal-01232174⟩

Share

Metrics

Record views

333

Files downloads

191