Real-time reachable set estimation for linear time-delay systems based on zonotopes-Reference-Cited by-同舟云学术

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Real-time reachable set estimation for linear time-delay systems based on zonotopes

Published:2023-04-19 Issue:8 Volume:54 Page:1639-1647
ISSN:0020-7721
Container-title:International Journal of Systems Science
language:en
Short-container-title:International Journal of Systems Science

Author:

Li Tuochen¹,Zheng Cunxi¹,Feng Zhiguang²,Dinh Thach N.³^ORCID,Raïssi Tarek³

Affiliation:

1. School of Economics and Management, Harbin Engineering University, Harbin, People's Republic of China

2. College of Automation, Harbin Engineering University, Harbin, People's Republic of China

3. Conservatoire National des Arts et Métiers (CNAM), Cedric-Lab, Paris, France

Publisher

Informa UK Limited

Subject

Computer Science Applications,Theoretical Computer Science,Control and Systems Engineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/00207721.2023.2189534

Reference38 articles.

1. Guaranteed state estimation by zonotopes

2. Set Propagation Techniques for Reachability Analysis

3. Computing reachable sets of hybrid systems using a combination of zonotopes and polytopes

4. Robust MPC of constrained discrete-time nonlinear systems based on approximated reachable sets

5. Estimation and synthesis of reachable set for switched linear systems

Cited by 4 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Set‐membership state estimation for delayed switched systems with interval uncertainty: A zonotopic approach;International Journal of Adaptive Control and Signal Processing;2024-08-15

2. Tight interval state estimate for discrete‐time descriptor linear systems;International Journal of Robust and Nonlinear Control;2024-02-16

3. Reachable Set Estimation and Controller Design for Linear Time-Delayed Control System with Disturbances;Mathematics;2024-01-05

4. Zonotope-Based Distributed Set-Membership Fusion Estimation for Artificial Neural Networks Under the Dynamic Event-Triggered Mechanism;IEEE Transactions on Neural Networks and Learning Systems;2023

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