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Deadline-Miss-Adaptive Controller Implementation for Real-Time Control Systems

Vreman, Nils LU ; Mandrioli, Claudio LU orcid and Cervin, Anton LU orcid (2022)
Abstract
The policy used to implement a control algorithm in a real-time system can significantly affect the quality of control. In this paper, we present a method to adapt the controller implementation, with the objective to improve the system’s performance under real-time faults. Our method compensates for missing state updates by adapting the controller parameters according to the number of consecutively missed deadlines. It extends the state-of-the-art by considering dynamic controllers, which have had limited coverage in previous literature. The adaptation mechanism can be precomputed offline, solely based on knowledge about the controller and not on the controlled plant. The approach is indifferent to the control design, as well as to the... (More)
The policy used to implement a control algorithm in a real-time system can significantly affect the quality of control. In this paper, we present a method to adapt the controller implementation, with the objective to improve the system’s performance under real-time faults. Our method compensates for missing state updates by adapting the controller parameters according to the number of consecutively missed deadlines. It extends the state-of-the-art by considering dynamic controllers, which have had limited coverage in previous literature. The adaptation mechanism can be precomputed offline, solely based on knowledge about the controller and not on the controlled plant. The approach is indifferent to the control design, as well as to the scheduling policy, and can be automatically realised by the operating system, thus improving the robustness of the control system to intermittent and unexpected real-time faults. We develop a stochastic performance analysis method and apply it to both a real plant and numerous simulated plants to evaluate our adaptive controller. Complementary to the stochastic analysis, we also do worst-case stability analysis of the resulting system. The results confirm the conjuncture that the adaptive controller improves both the performance and robustness in the presence of deadline misses. (Less)
Please use this url to cite or link to this publication:
author
; and
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
Adaptive Control, Real-Time Control, Deadline Misses
host publication
2022 IEEE 28th Real-Time and Embedded Technology and Applications Symposium (RTAS)
publisher
IEEE - Institute of Electrical and Electronics Engineers Inc.
external identifiers
  • scopus:85133696049
DOI
10.1109/RTAS54340.2022.00010
project
Towards Adaptively Morphing Embedded Systems
language
English
LU publication?
yes
id
921fe515-9800-40da-b7d7-99a7906bdc41
date added to LUP
2022-07-21 10:53:03
date last changed
2023-11-21 07:23:36
@inproceedings{921fe515-9800-40da-b7d7-99a7906bdc41,
  abstract     = {{The policy used to implement a control algorithm in a real-time system can significantly affect the quality of control. In this paper, we present a method to adapt the controller implementation, with the objective to improve the system’s performance under real-time faults. Our method compensates for missing state updates by adapting the controller parameters according to the number of consecutively missed deadlines. It extends the state-of-the-art by considering dynamic controllers, which have had limited coverage in previous literature. The adaptation mechanism can be precomputed offline, solely based on knowledge about the controller and not on the controlled plant. The approach is indifferent to the control design, as well as to the scheduling policy, and can be automatically realised by the operating system, thus improving the robustness of the control system to intermittent and unexpected real-time faults. We develop a stochastic performance analysis method and apply it to both a real plant and numerous simulated plants to evaluate our adaptive controller. Complementary to the stochastic analysis, we also do worst-case stability analysis of the resulting system. The results confirm the conjuncture that the adaptive controller improves both the performance and robustness in the presence of deadline misses.}},
  author       = {{Vreman, Nils and Mandrioli, Claudio and Cervin, Anton}},
  booktitle    = {{2022 IEEE 28th Real-Time and Embedded Technology and Applications Symposium (RTAS)}},
  keywords     = {{Adaptive Control; Real-Time Control; Deadline Misses}},
  language     = {{eng}},
  month        = {{05}},
  publisher    = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
  title        = {{Deadline-Miss-Adaptive Controller Implementation for Real-Time Control Systems}},
  url          = {{http://dx.doi.org/10.1109/RTAS54340.2022.00010}},
  doi          = {{10.1109/RTAS54340.2022.00010}},
  year         = {{2022}},
}