This study presents a new adaptive predictive error filter-based maximum power point tracker (MPPT) for a photovoltaic (PV) system. This MPPT is developed using the concept of an adaptive predictive filter (APEF) that consists of a one-tap finite impulse response. The filter step-size of the APEF is adapted using a recursive least-square (RLS) algorithm with an adaptive forgetting factor. The specialty of this MPPT is that it performs MPP tracking operation in a single step. It performs two functions: namely, MPP estimation adjusting operating point of a boost converter at MPP and then filtering of the PV voltage fluctuation after MPPT action. Thus, the proposed MPPT is compact and efficient with less computational complexities than existing MPPTs such as perturb and observe (P&O) and incremental conductance. The filter part of the proposed RLS-APEF-MPPT is a discrete PID-controller, where PD-part is tuned using pole-placement strategy and integral-term is fixed. The performances of the proposed RLS-APEF-MPPT were verified using experimentation on a prototype PV system. Its performances were compared with that of P&O, adaptive-P&O-MPPTs. From the observed results, it is confirmed that the proposed MPPT exhibits superior performance.

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Adaptive predictive error filter-based maximum power point tracking algorithm for a photovoltaic system

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