Lyapunov-based switched extremum seeking for photovoltaic power maximization

This paper presents a practical variation of extremum seeking (ES) that guarantees asymptotic convergence through a Lyapunov-based switching scheme (Lyap-ES). Traditional ES methods enter a limit cycle around the optimum. Lyap-ES converges to the optimum by exponentially decaying the perturbation signal once the system enters a neighborhood around the extremum. As a case study, we consider maximum power point tracking (MPPT) for photovoltaics. Simulation results demonstrate how Lyap-ES is self-optimizing in the presence of varying environmental conditions and produces greater energy conversion efficiencies than traditional MPPT methods. Experimentally measured environmental data is applied to investigate performance under realistic operating scenarios.