Stochastic finite-time H∞ filtering for nonlinear Markovian jump systems with partly known transition probabilities-Reference-Cited by-同舟云学术

Stochastic finite-time H∞ filtering for nonlinear Markovian jump systems with partly known transition probabilities

Published:2018-05-07 Issue:1 Volume:233 Page:31-43
ISSN:0959-6518
Container-title:Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering
language:en
Short-container-title:Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering

Author:

Wang Bo¹²³^ORCID,Cheng Jun⁴,Zou Fucheng¹²

Affiliation:

1. School of Electrical and Information Engineering, Xihua University, Chengdu, P.R. China

2. Key Laboratory of Fluid and Power Machinery, Ministry of Education, Xihua University, Chengdu, P.R. China

3. School of Applied Mathematics, University of Electronic Science and Technology of China, Chengdu, P.R. China

4. School of Science, Hubei University for Nationalities, Enshi, P.R. China

Abstract

This article investigates the problem of the stochastic finite-time [Formula: see text] filtering for continuous nonlinear Markovian jump systems with partly known transition probabilities. Based on linear matrix inequality techniques, a novel Lyapunov function is constructed to design a filter with a prescribed finite-time [Formula: see text] performance index. Reciprocally, convex approach is introduced to decrease the conservatism of achieved criteria. Finally, some numerical simulations are carried out to demonstrate the effectiveness of developed method.

Publisher

SAGE Publications

Subject

Mechanical Engineering,Control and Systems Engineering

Link

http://journals.sagepub.com/doi/pdf/10.1177/0959651818770337

Reference55 articles.

1. Multi-sensor Ensemble Kalman filtering algorithm based on observation fuzzy support degree fusion

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