Bounded Extremum Seeking for Single-Variable Static Map using State Transformation
Document Type
Conference Proceeding
Publication Date
1-1-2024
Abstract
We solve a gradient based bounded extremum seeking problem for single-variable static maps in the presence of time-varying piecewise continuous measurement uncertainty. Instead of using previously reported averaging-based methods, we introduce a new state transformation, allowing us to use new comparison function and generalized Lyapunov function approaches to obtain our ultimate bounds on the parameter estimation error. We illustrate significant advantages of our new method, including less restrictive conditions on the extremum seeking parameters, as compared with previous methods.
Publication Source (Journal or Book title)
Proceedings of the IEEE Conference on Decision and Control
First Page
6257
Last Page
6262
Recommended Citation
Mazenc, F., Malisoff, M., & Fridman, E. (2024). Bounded Extremum Seeking for Single-Variable Static Map using State Transformation. Proceedings of the IEEE Conference on Decision and Control, 6257-6262. https://doi.org/10.1109/CDC56724.2024.10886636