The present paper treats with the implementation of the modified P&O (perturb and observe) maximum power point tracking (MPPT) algorithm to improve its performance. Firstly, the simulation study and comparison between the modified and the conventional P &O methods are presented to offer the efficacy of the developed method. Secondly, to verify the effectiveness of the developed method, practical validation is carried out using an Arduino Mega. The experimental and simulation tests present that the tracking speed is increased and fluctuations around the MPP (maximum power point) are reduced which demonstrates that the proposed algorithm overcomes the drawbacks of conventional one, and it does not require any extra hardware components.

Design and Implementation of Takagi-Sugeno Fuzzy Tracking Control for a DC-DC Buck Converter

This paper deals with the synthesis of fuzzy state feedback controller of permanent magnet synchronous machine (PMSM). First, the T-S fuzzy output tracking control will be presented, the concept of virtual desired variables and, in turn the so-called generalized kinematics are introduced to simplify the design procedure. The gains of fuzzy control are obtained by solving a set of Linear Matrix Inequality (LMI). Next, the Takagi-Sugeno (T-S) fuzzy model is employed to approximate a non linear system in d - q frame. Finally, simulation results are given to demonstrate the controller's effectiveness.This paper deals with the synthesis of fuzzy state feedback controller of permanent magnet synchronous machine (PMSM). First, the T-S fuzzy output tracking control will be presented, the concept of virtual desired variables and, in turn the so-called generalized kinematics are introduced to simplify the design procedure. The gains of fuzzy control are obtained by solving a set of Linear Matrix Inequality (LMI). Next, the Takagi-Sugeno (T-S) fuzzy model is employed to approximate a non linear system in d - q frame. Finally, simulation results are given to demonstrate the controller's effectiveness.

Introduction. A new global maximum power point tracking (GMPPT) control strategy for a solar photovoltaic (PV) system, based on the combination of Takagi-Sugeno (T-S) fuzzy models and an ANFIS, is presented. The novelty of this paper lies in the integration of T-S fuzzy models and the ANFIS approach to develop an efficient GMPPT controller for a PV system operating under partial shading conditions. Purpose. The new GMPPT control strategy aims to extract maximum power from the PV system under varying weather conditions or partial shading. Methods. An ANFIS algorithm is used to determine the maximum voltage, which corresponds to the actual maximum power point, based on PV voltage and current. Next, the nonlinear model of the PV system is employed to design the T-S fuzzy controller. A reference model is then derived based on the maximum voltage. Finally, a tracking controller is developed using the reference model and the T-S fuzzy controller. The stability of the overall system is evaluated using Lyapunov’s method and is represented through linear matrix inequalities expressions. The results clearly demonstrate the advantages of the proposed GMPPT-based fuzzy control strategy, showcasing its high performance in effectively reducing oscillations in various steady states of the PV system, ensuring minimal overshoot and a faster response time. In addition, a comparative analysis of the proposed GMPPT controller against conventional algorithms, such as Incremental Conductance, Perturb & Observe and Particle Swarm Optimization, shows that it offers a fast dynamic response in finding the maximum power with significantly less oscillation around the maximum power point. References 20, tables 3, figures 14.

The aim of this paper is to present a new fuzzy tracking control for a wind energy conversion system (WECS), which consists of a permanent magnet synchronous generator based variable speed wind turbine (WT). First, a fuzzy Takagi-Sugeno (T-S) model is used to represent the PMSG-WT nonlinear system. Next, a fuzzy tracking control based on the concept of virtual desired variables (VDVs) is formulated to simplify the design of the virtual reference model and the control law. Using this concept, a two-stage design procedure is developed: i) determine the VDVs from the output equation of the nonlinear system and the generalized kinematics constraints ii) find the feedback controller gains by solving a set of linear matrix inequalities (LMIs). Finally, simulation results are provided to demonstrate the validity and the effectiveness of the proposed method.