Fast online optimization of uncertain Wiener systems using extremum seeking control (ESC) is investigated. Derivative estimation in extremum seeking is herefore described as an online parametric system identification problem. Multisine dithering is applied with frequencies around the first resonance frequency of the system to remove the time scale separation between dither and plant dynamics which is commonly required in ESC. Recursive use of the Fourier transform, over a moving window of historic data, provides a frequency response function estimate of the system's local best linear approximation. Continuous online complex curve fitting is then applied to extrapolate to an estimate of the steady-state response which coincides with the local gradient of the steady-state objective function. An analysis of the closed-loop dynamics is provided. Transient improvements and robustness of the approach against plant variation are demonstrated with a simulation example.
|Number of pages||6|
|Publication status||Published - 2020|
|Event||21st IFAC World Congress 2020 - Berlin, Germany|
Duration: 12 Jul 2020 → 17 Jul 2020
- Closed-loop identification
- Extremum seeking and model-free adaptive control
- Frequency domain identification