Performance enhancement of fuzzy-PID controller for MPPT of PV system to extract maximum power under different conditions

In this article, a maximum Power Point Tracking (MPPT) controller is designed for photovoltaic (PV) applications. This controller has been implemented with Fuzzy Gain Scheduling of Proportional-Integral-Derivative (PID) type controller (FGS-PID). To implement this controller, scaling factors (SF) for the input signals of FGS are applied. The recommended adaptive two-level controller has all the welfare of fuzzy logic system (FLC) and PID control. Zieglere-Nichols technique is used to fine-tune the initial PID's gains. The PID's gains are updated with FGS-PID in transient and steady-state conditions to cope with fluctuations, minimize settling time and ensure stability. FLC is used for gain factors to deal with tuning of conditioned input signals of the FGS-PID. Moreover, FLC and an improved shuffled frog leaping algorithm (ISFLA) are applied to tune the member functions (MFs) of FGS. The use of this algorithm can lead to automatic regulation of the triangular MFs. Simulations are done to confirm the edge of this approach over conventional methods. It is very fast and accurate in tracking the maximum power. It provides minimum oscillations and improved dynamic response than other approaches. The speed of the tracking is also improved with acceptable accuracy.

Automated summary

This article presents the design of a maximum Power Point Tracking (MPPT) controller for photovoltaic (PV) applications. The controller utilizes a Fuzzy Gain Scheduling of Proportional-Integral-Derivative (PID) type controller (FGS-PID) and scaling factors (SF) to enhance control performance and stability in the presence of fluctuations and varying conditions. The use of an adaptive two-level controller and the combination of fuzzy logic system (FLC) and PID control contribute to improved tracking accuracy, reduced settling time, and enhanced dynamic response compared to conventional methods.