A unifying approach to extremum seeking: Adaptive schemes based on estimation of derivatives

Experimental closed-loop control of separated-flow over a plain flap using extremum seeking

“…The estimation of the static map local curvature is realized by adding a second demodulation step in series with the first one (e.g., Nesić et al 2010Nesić et al , 2012. Following the development made in Chabert et al (2014), but considering this time the second-order Taylor expansion of g in a neighborhood of θ 0 , the signal HP[y] is so Ξ, the signal obtained from the first demodulation, reads…”

“…The modulation-demodulation method for successive derivative estimation is presented in the general case by Nesić et al (2010Nesić et al ( , 2012. In the following, this estimation will be presented in a purely applicative way.…”

Nonlinear extremum seeking inspired on second order sliding modes

“…This is in contrast to usual ES frameworks, see Ariyur and Krstic (2003), Nesic et al (2010) or Tan et al (2010). Specifically, we consideṙ…”

“…One of the results of recent analysis is a clear understanding of the essential components of ES algorithms: an optimization method, and an estimation of the gradient of the input-output map . Yet, despite the freedom to choose these to components, most ES algorithms estimate the gradient using a time-scale separation, a dither signal (to explore the input-output map) and averaging of the resulting oscillations (Ariyur & Krstic, 2003;Nesic et al, 2010). Even less conventional ES algorithms using Second Order Sliding Modes (SOSM) are based on this method (Yu & Ozguner, 2002.…”

Optimal cold start calibration of spark ignition engines

“…In this instance, there may be benefits in incorporating both a model based approach to optimal calibration that uses less accurate engine models that are faster to define, and coupling this with model free optimisation approaches (such as Popovic et al (2006); Nesic et al (2010a) or Nesic et al (2010b)) that can fine tune the solution to find a local optima.…”