Demystifying ESC Parameters' Impact on Dynamic Response

Extremum seeking control (ESC) is a model-free optimization technique that autonomously drives a system toward its optimal operating point despite unknown system dynamics. It has been widely applied in various fields, including renewable energy systems, automotive control, and industrial process optimization. However, the selection of ESC parameters remains a significant challenge, as improper tuning can lead to slow convergence, instability, or suboptimal performance. While several adaptive tuning methods have been developed to adjust the perturbation signal amplitude, other critical ESC parameters have received limited attention. Therefore, this paper provides a comprehensive review of existing adaptive tuning methods for optimizing perturbation signal amplitude and investigates the impact of other ESC parameters on convergence. Two analytical verification examples are presented to illustrate the influence of these parameters, followed by extensive simulation results and experimental results that validate the theoretical analysis. The effect of cascaded systems on ESC convergence is also simulated and experimentally demonstrated.