Adaptive Piyavskii–Shubert Algorithm and Its Application to Maximum Power Point Tracking Control

This paper proposes an efficient maximum power point tracking control algorithm based on the Piyavskii–Shubert algorithm under partial shading conditions. The Piyavskii–Shubert algorithm, a deterministic global optimization algorithm, maximizes a function satisfying the Lipschitz continuity over a closed set. However, the algorithm often converges slowly because it uses an inefficient parameter even in neighborhoods of a global maximum. The proposed method accelerates convergence to the global maximum by adaptively changing the parameter based on prior information. Simulations are conducted to illustrate the effectiveness of the proposed method by comparing it with traditional methods.