English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Tools annual

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

In this paper, we present a novel Newton-based extremum seeking controllerfor the solution of multivariable model-free optimization problems in staticmaps. Unlike existing asymptotic and fixed-time results in the literature, wepresent a scheme that achieves (practical) fixed time convergence to aneighborhood of the optimal point, with a convergence time that is independentof the initial conditions and the Hessian of the cost function, and thereforecan be arbitrarily assigned a priori by the designer via an appropriate choiceof parameters in the algorithm. The extremum seeking dynamics exploit a classof fixed time convergence properties recently established in the literature fora family of Newton flows, as well as averaging results for perturbed dynamicalsystems that are not necessarily Lipschitz continuous. The proposed extremumseeking algorithm is model-free and does not require any explicit knowledge ofthe gradient and Hessian of the cost function. Instead, real-time optimizationwith fixed-time convergence is achieved by using real time measurements of thecost, which is perturbed by a suitable class of periodic excitation signalsgenerated by a dynamic oscillator. Numerical examples illustrate theperformance of the algorithm.

Fixed-Time Newton-Like Extremum Seeking