.png){kind=icon}
.png){kind=icon}
Return
An extremum seeking algorithm for 1D static maps with delay-based derivative estimation
.png){kind=icon}
PRE
AI
DOI：10.1016/j.ejcon.2025.101339.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
For an even power convex or concave function of a scalar variable having a global and unique extremum, an algorithm of the extremum seeking is proposed, which does not use any dither excitation signal, hence, being asymptotically exact, and it is based on online time derivative estimation of the measured output. Two approaches are discussed, first, with utilization of the super-twisting differentiator, and second, where the derivative is estimated via the time-delay method. For analysis of the latter, an extension of the invariance principle is formulated for functional differential inclusions. The efficiency of the suggested extremum seeking algorithms is illustrated through numeric experiments.
Keywords:
extremum seeking
derivative estimation
super-twisting differentiator
time-delay method
functional differential inclusions
Journal
IF:
2.6
Papers:
323
Citations:
2.5K