Lan, J. (2023) Safety Monitoring and Alert for Neural Network-Enabled Control Systems. In: 22nd IFAC World Congress (IFAC 2023), Yokohama, Japan, 09-14 Jul 2023, pp. 9436-9441. (doi: 10.1016/j.ifacol.2023.10.237)
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Abstract
This paper considers the safety monitoring and enhancement for neural network-enabled control systems with disturbance and measurement noise. A robustly stable interval observer is designed to generate sound lower and upper bounds of the system state. The obtained interval is used to monitor the runtime system state and predict the one-step ahead future system trajectory, providing system safety monitoring and alert. The simulation results of a numerical example and an adaptive cruise control system demonstrate efficacy of the observer in runtime system monitoring and its potentials in detecting sensor faults and enhancing system safety.
| Item Type: | Conference Proceedings |
|---|---|
| Additional Information: | This work was supported by a Leverhulme Trust Early Career Fellowship under Award ECF-2021-517. |
| Keywords: | Safety, neural network, observer, fault detection, intelligent autonomous vehicles. |
| Status: | Published |
| Refereed: | Yes |
| Glasgow Author(s) Enlighten ID: | Lan, Dr Jianglin |
| Authors: | Lan, J. |
| College/School: | College of Science and Engineering > School of Engineering > Autonomous Systems and Connectivity |
| ISSN: | 2405-8963 |
| Published Online: | 22 November 2023 |
| Copyright Holders: | Copyright © 2023 The Authors |
| First Published: | First published in IFAC-PapersOnLine 56(2):9436-9441 |
| Publisher Policy: | Reproduced under a Creative Commons license |
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