Novel extreme seeking control framework with ordered excitation and nonlinear function based PSO: Method and application

Abstract

The performance of a photovoltaic power system is heavily influenced by mismatches, for example, partial shading effects. In literature, it lacks of a scrupulous study on intelligent control designs whose transient responses and steady state responses are not directly given when achieving the goal of global maximum power point tracking (GMPPT). A novel and systematic control design approach is proposed mathematically to derive explicit discrete controllers for the overall GMPPT performance. Specifically, the new algorithms of nonlinear function (NF) based particle swarm optimization (PSO) and ordered excitation (OE) are incorporated into the extreme seeking controller for the enhancement of both transient and steady state responses when fulfilling the extreme seeking task. The explicit control functions are easy to implement in the applications. Both the simulation based analysis and experimental study are carried out in a statistical manner in order to evaluate the proposed controller through a number of control performance indicators. A comparison analysis of the statistical data reveals that both simulation and experimental results agree with the theory where both algorithms of NF-PSO and OE play a role to improve transient responses and steady state responses for the global extreme seeking. Meanwhile, the proposed intelligent controller outperforms the classical benchmark in tracking the GMPP. The insightful and instructive control design tool is promising in both academia and engineering.