A review of safe online learning for nonlinear control systems
dc.contributor.author | Osborne, Matthew | |
dc.contributor.author | Shin, Hyosang | |
dc.contributor.author | Tsourdos, Antonios | |
dc.date.accessioned | 2021-07-28T10:46:19Z | |
dc.date.available | 2021-07-28T10:46:19Z | |
dc.date.issued | 2021-07-19 | |
dc.description.abstract | Learning for autonomous dynamic control systems that can adapt to unforeseen environmental changes are of great interest but the realisation of a practical and safe online learning algorithm is incredibly challenging. This paper highlights some of the main approaches for safe online learning of stabilisable nonlinear control systems with a focus on safety certification for stability. We categorise a non-exhaustive list of salient techniques, with a focus on traditional control theory as opposed to reinforcement learning and approximate dynamic programming. This paper also aims to provide a simplified overview of techniques as an introduction to the field. It is the first paper to our knowledge that compares key attributes and advantages of each technique in one paper. | en_UK |
dc.identifier.citation | Osborne M, Shin H-S, Tsourdos A. (2021) A review of safe online learning for nonlinear control systems. In: 2021 International Conference on Unmanned Aircraft Systems (ICUAS), 15-18 June 2021, Athens | en_UK |
dc.identifier.issn | 2575-7296 | |
dc.identifier.uri | https://doi.org/10.1109/ICUAS51884.2021.9476765 | |
dc.identifier.uri | https://dspace.lib.cranfield.ac.uk/handle/1826/16941 | |
dc.language.iso | en | en_UK |
dc.publisher | IEEE | en_UK |
dc.rights | Attribution-NonCommercial 4.0 International | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc/4.0/ | * |
dc.subject | Nonlinear dynamical systems | en_UK |
dc.subject | Real-time systems | en_UK |
dc.subject | Nonlinear control systems | en_UK |
dc.subject | Reinforcement learning | en_UK |
dc.subject | Heuristic algorithms | en_UK |
dc.title | A review of safe online learning for nonlinear control systems | en_UK |
dc.type | Conference paper | en_UK |
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