Extremum-Seeking Control With Adaptive Excitation: Application to a Photovoltaic System

The objective of this study is to improve the performance of the extremum-seeking control (ESC) technique in terms of time and accuracy of convergence toward the optimum operating point of a dynamic system subject to the effect of external disturbances. More precisely, the idea is to reduce the undesirable effect of time scale separation in ESC on the performance of the closed loop system. The method consists in adaptively controlling the excitation signal amplitude using a neural network (NN) model, which gives a real-time estimate of the optimal operating point based on the measurement of the external disturbances. Stability of the proposed ESC with adaptive excitation, referred to in the following as ESC
_a,
is demonstrated. The superiority of ESC
_a
compared to ESC in terms of accuracy and time of convergence to the optimum is demonstrated both theoretically and experimentally, in the case of the optimization of a photovoltaic panel system.