Adaptive Numerical Differentiation for Extremum Seeking with Sensor Noise

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2501.04275v1.pdf (1.76 MB)

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http://arxiv.org/abs/2501.04275

Permanent Link

https://doi.org/10.48550/arXiv.2501.04275
 http://hdl.handle.net/11603/37693

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UMBC Faculty Collection
UMBC Mechanical Engineering Department
UMBC Student Collection

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Author/Creator ORCID

https://orcid.org/0000-0003-2778-686X
 https://orcid.org/0000-0002-4146-6275

Date

2025-01-08

Type of Work

journal articles
preprints
Text

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Citation of Original Publication

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This item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.

Subjects

UMBC Estimation, Control, and Learning Laboratory (ECLL).
Electrical Engineering and Systems Science - Systems and Control
Computer Science - Systems and Control

Abstract

Extremum-seeking control (ESC) is widely used to optimize performance when the system dynamics are uncertain. However, sensitivity to sensor noise is an important issue in ESC implementation due to the use of high-pass filters or gradient estimators. To reduce the sensitivity of ESC to noise, this paper investigates the use of adaptive input and state estimation (AISE) for numerical differentiation. In particular, this paper develops extremum-seeking control with adaptive input and state estimation (ESC/AISE), where the high-pass filter of ESC is replaced by AISE to improve performance under sensor noise. The effectiveness of ESC/AISE is illustrated via numerical examples.