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Date
2024-01-19Type
- Conference Paper
ETH Bibliography
yes
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Abstract
This paper proposes a novel online data-driven adaptive control for discrete-time unknown linear time-varying systems. Initialized with an empirical feedback gain, the algorithm periodically updates this gain based on the data collected over a short time window before each update. Meanwhile, the stability of the closed-loop system is analyzed in detail, which shows that under some mild assumptions, the proposed online data-driven adaptive control scheme can guarantee practical global exponential stability. Finally, the proposed algorithm is demonstrated by numerical simulations and its performance is compared with other control algorithms for unknown linear time-varying systems. Show more
Publication status
publishedExternal links
Book title
2023 62nd IEEE Conference on Decision and Control (CDC)Pages / Article No.
Publisher
IEEEEvent
Organisational unit
02140 - Dep. Inf.technologie und Elektrotechnik / Dep. of Inform.Technol. Electrical Eng.
Funding
203979 - From model-based to data-driven design: Signal processing and control of noisy nonlinear systems (SNF)
Notes
Conference lecture held on December 15, 2023.More
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ETH Bibliography
yes
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