Adaptive output-feedback control design for maximum power point tracking of uncertain photovoltaic systems

The problem of maximum power point tracking (MPPT) control of uncertain photovoltaic (PV) systems is addressed in this paper, on the basis of an adaptive Kalman-like observer. The system is composed of a photovoltaic generator (PVG) supplying power to a DC centrifugal pump driven by a DC–DC boost converter. The PVG is connected to the converter by a long PV cable. Indeed, many PV power plant situations require that the PV panels be installed at a great distance from the converter for several reasons including the security and the property of the site and its exposure to good daily solar irradiance. This obviously leads to the difficulty of PVG output current and voltage measurement using ordinary sensors. Such quantities measurement being in fact necessary for MPPT algorithms and controllers design. Furthermore, the specific parameters of the long PV cable used, namely its resistance and inductance, could have a significant effect on the MPPT control efficiency if instead of PVG delivered voltage and current measurements, only those accessible at the converter side of the cable are used in MPPT controllers design. Therefore, this work aims at overcoming the two aforementioned issues by proposing an adaptive output-feedback control-based MPPT for PV systems. An adaptive Kalman-like observer providing online estimates of inaccessible state variables as well as of PV cable unknown parameters is firstly designed. Then, a backstepping control law is synthesized to meet the MPPT objective. The convergence of both adaptive observer and closed-loop system control has been established using Lyapunov approach and the effectiveness of the developed adaptive MPPT controller in achieving an accurate and robust MPPT control towards uncertainties of the PV cable parameters, has been validated through numerical simulations.