Asymptotic convergence through Lyapunov-based switching in extremum seeking with application to photovoltaic systems

This paper presents a practical extension to extremum seeking control systems which guarantees asymptotic convergence through a Lyapunov-based switching scheme. In contrast, traditional extremum seeking methods enter a limit cycle around the optimal set-point, once identified. The proposed approach converges to the optimal set-point by exponentially decaying the sinusoidal perturbation signal once the system enters a neighborhood around the extremum. To analyze the performance characteristics of this method, we apply this algorithm to the maximum power point tracking (MPPT) problem in photovoltaic systems. Simulation results indicate that our approach is self-optimizing in the presence of varying environmental conditions and produces higher energy conversion efficiencies than traditional MPPT methods under typical operating scenarios.