Details
| Original language | English |
|---|---|
| Pages (from-to) | 7014-7021 |
| Number of pages | 8 |
| Journal | IEEE Transactions on Automatic Control |
| Volume | 68 |
| Issue number | 11 |
| Early online date | 27 Feb 2023 |
| Publication status | Published - Nov 2023 |
Abstract
Keywords
- Approximation error, Data models, Mathematical models, Noise measurement, Nonlinear systems, Standards, Trajectory, nonlinear systems, feedback linearization, Data-driven control
ASJC Scopus subject areas
- Engineering(all)
- Electrical and Electronic Engineering
- Engineering(all)
- Control and Systems Engineering
- Computer Science(all)
- Computer Science Applications
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In: IEEE Transactions on Automatic Control, Vol. 68, No. 11, 11.2023, p. 7014-7021.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - Data-Based Control of Feedback Linearizable Systems
AU - Alsalti, Mohammad Salahaldeen Ahmad
AU - Lopez Mejia, Victor Gabriel
AU - Berberich, Julian
AU - Allgöwer, Frank
AU - Müller, Matthias A.
PY - 2023/11
Y1 - 2023/11
N2 - We present an extension of Willems' Fundamental Lemma to the class of multi-input multi-output discrete-time feedback linearizable nonlinear systems, thus providing a data-based representation of their input-output trajectories. Two sources of uncertainty are considered. First, the unknown linearizing input is inexactly approximated by a set of basis functions. Second, the measured output data is contaminated by additive noise. Further, we propose an approach to approximate the solution of the data-based simulation and output matching problems, and show that the difference from the true solution is bounded. Finally, the results are illustrated on an example of a fully-actuated double inverted pendulum.
AB - We present an extension of Willems' Fundamental Lemma to the class of multi-input multi-output discrete-time feedback linearizable nonlinear systems, thus providing a data-based representation of their input-output trajectories. Two sources of uncertainty are considered. First, the unknown linearizing input is inexactly approximated by a set of basis functions. Second, the measured output data is contaminated by additive noise. Further, we propose an approach to approximate the solution of the data-based simulation and output matching problems, and show that the difference from the true solution is bounded. Finally, the results are illustrated on an example of a fully-actuated double inverted pendulum.
KW - Approximation error
KW - Data models
KW - Mathematical models
KW - Noise measurement
KW - Nonlinear systems
KW - Standards
KW - Trajectory
KW - nonlinear systems
KW - feedback linearization
KW - Data-driven control
UR - http://www.scopus.com/inward/record.url?scp=85149390738&partnerID=8YFLogxK
U2 - 10.1109/TAC.2023.3249289
DO - 10.1109/TAC.2023.3249289
M3 - Article
VL - 68
SP - 7014
EP - 7021
JO - IEEE Transactions on Automatic Control
JF - IEEE Transactions on Automatic Control
SN - 0018-9286
IS - 11
ER -