Model reduction on Markovian jump systems with partially unknown transition probabilities: balanced truncation approach-Reference-Cited by-同舟云学术

Model reduction on Markovian jump systems with partially unknown transition probabilities: balanced truncation approach

Published:2015-06 Issue:9 Volume:9 Page:1411-1421
ISSN:1751-8652
Container-title:IET Control Theory & Applications
language:en
Short-container-title:IET Control Theory & Applications

Author:

Zhang Huiyan¹,Wu Ligang¹,Shi Peng²³,Zhao Yuxin⁴

Affiliation:

1. Space Control and Inertial Technology Research Center, Harbin Institute of TechnologyHarbin150001People's Republic of China

2. School of Electrical and Electronic Engineering, University of AdelaideSA5005Australia

3. College of Engineering and Science, Victoria UniversityMelbourneVIC8001Australia

4. College of Automation, Harbin Engineering UniversityHarbin150001People's Republic of China

Funder

National Natural Science Foundation of China

Fok Ying Tung Education Foundation

Australian Research Council

Publisher

Institution of Engineering and Technology (IET)

Subject

Electrical and Electronic Engineering,Control and Optimization,Computer Science Applications,Human-Computer Interaction,Control and Systems Engineering

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/iet-cta.2014.0792

Reference30 articles.

1. Stochastic state estimation for neural networks with distributed delays and Markovian jump

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3. Delayed-state-feedback exponential stabilization for uncertain Markovian jump systems with mode-dependent time-varying state delays

4. Stability of discrete‐time delay Markovian jump systems with stochastic non‐linearity and impulses

5. Delay-range-dependent ℋ∞ filtering for two-dimensional Markovian jump systems with interval delays

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