This paper presents a control method suitable for photovoltaic (PV) systems which ensure that power generated is maximized for various conditions. Due to partial shading conditions in PV, the power-voltage characteristics exhibit multiple local peaks; one such phenomenon is the global peak. These conditions make it very challenging for maximum power point tracking (MPPT) to locate the global maximum power point. Many tracking algorithms have been proposed for this purpose. In this paper, a modified particle swarm optimization (PSO)-based MPPT technique is proposed. Unlike the conventional PSO-based MPPT methods, the proposed method accelerate convergence of the PSO algorithm by consistently decreasing the weighting factor, the cognitive and social parameters thus reducing the steps of iterations and improved the tracking response time. The advantage of the proposed method is that it requires fewer search steps (converges to the desired solution in a reasonable time) compared to other methods. It requires only the idea of series cells; thus, it is system independent. The study is supported by numerical and experimental results.