Performance of photovoltaic (PV) generator systems relies on its operating conditions. Maximum power extracted from PV generators depends strongly on solar irradiation, load impedance, and ambient temperature. A most maximum power point tracking (MPPT) algorithm is based on a perturb and observe method and an incremental conductance method. It is well known the latter is better in terms of dynamics and tracking characteristics under condition of rapidly changing solar irradiation. However, in case of digital implementation, the latter has some error for determining a maximum power point. This paper presents a PID based MPPT algorithm for such PV systems. We use neural network technique for determining PID parameters by online learning approach. And we construct a boost converter to regulate the output voltage from PV generator system. Computer simulation is carried out to evaluate the proposed MPPT method and we accomplish comparative study with a perturb and observe based MPPT method to prove its superiority.