scholarly journals Study of the Intelligent Behavior of a Maximum Photovoltaic Energy Tracking Fuzzy Controller

Energies ◽  
2018 ◽  
Vol 11 (12) ◽  
pp. 3263 ◽  
Author(s):  
Gul Tchoketch Kebir ◽  
Cherif Larbes ◽  
Adrian Ilinca ◽  
Thameur Obeidi ◽  
Selma Tchoketch Kebir
Keyword(s):  
Fuzzy Logic ◽  
Control Method ◽  
Fuzzy Controller ◽  
Power Converter ◽  
Climatic Conditions ◽  
Maximum Power ◽  
Maximum Speed ◽  
Special Choice ◽  
Photovoltaic Generators ◽  
Inputs And Outputs

The Maximum Power Point Tracking (MPPT) strategy is commonly used to maximize the produced power from photovoltaic generators. In this paper, we proposed a control method with a fuzzy logic approach that offers significantly high performance to get a maximum power output tracking, which entails a maximum speed of power achievement, a good stability, and a high robustness. We use a fuzzy controller, which is based on a special choice of a combination of inputs and outputs. The choice of inputs and outputs, as well as fuzzy rules, was based on the principles of mathematical analysis of the derived functions (slope) for the purpose of finding the optimum. Also, we have proved that we can achieve the best results and answers from the system photovoltaic (PV) with the simplest fuzzy model possible by using only 3 sets of linguistic variables to decompose the membership functions of the inputs and outputs of the fuzzy controller. We compare this powerful controller with conventional perturb and observe (P&O) controllers. Then, we make use of a Matlab-Simulink® model to simulate the behavior of the PV generator and power converter, voltage, and current, using both the P&O and our fuzzy logic-based controller. Relative performances are analyzed and compared under different scenarios for fixed or varied climatic conditions.

Hybrid Anti-Windup Fuzzy PI Controller Based Direct Torque Control of Three Phase Induction Motor

2014 ◽  
Vol 573 ◽  
pp. 155-160
Author(s):  
A. Pandian ◽  
R. Dhanasekaran
Keyword(s):  
Fuzzy Logic ◽  
Induction Motor ◽  
Fuzzy Logic Controller ◽  
Control Method ◽  
Fuzzy Controller ◽  
Direct Torque Control ◽  
Operating Conditions ◽  
Torque Control ◽  
Constant Speed ◽  
Three Phase

This paper presents improved Fuzzy Logic Controller (FLC) of the Direct Torque Control (DTC) of Three-Phase Induction Motor (IM) for high performance and torque control industrial drive applications. The performance of the IM using PI Controllers and general fuzzy controllers are meager level under load disturbances and transient conditions. The FLC is extended to have a less computational burden which makes it suitable for real time implementation particularly at constant speed and torque disturbance operating conditions. Hybrid control has advantage of integrating a superiority of two or more control techniques for better control performances. A fuzzy controller offers better speed responses for startup and large speed errors. If the nature of the load torque is varied, the steady state speed error of DTC based IM drive with fuzzy logic controller becomes significant. To improve the performance of the system, a new control method, Hybrid fuzzy PI control is proposed. The effectiveness of proposed method is verified by simulation based on MATLAB. The proposed Hybrid fuzzy controller has adaptive control over load toque variation and can maintain constant speed.

scholarly journals Integrated Design of Adaptive & Fuzzy Logic Control for Trajectory Tracking of 2 DOF Quadrotor

2021 ◽  
Author(s):  
Mustefa Jibril
Keyword(s):  
Fuzzy Logic ◽  
Trajectory Tracking ◽  
Degrees Of Freedom ◽  
Fuzzy Logic Controller ◽  
Control Method ◽  
Fuzzy Controller ◽  
Vertical Plane ◽  
Integrated Design ◽  
Adaptive Fuzzy ◽  
Quadrotor Uav

Accurate and precise trajectory tracking is crucial for a quadrotor to operate in disturbed environments. This paper presents a novel tracking hybrid controller for a quadrotor UAV that combines the Adaptive and Fuzzy logic controller. The Adaptive fuzzy controller is implemented to govern the behavior of two degrees of freedom quadrotor UAV. The proposed controller allows controlling the movement of UAVs to track a given trajectory in a 2D vertical plane. The Fuzzy Logic system provides an automatic adjustment of the Adaptive parameters to reduce tracking errors and improve the quality of the controller. The results showed perfect behavior for the control law to control a quadrotor trajectory tracking task. To show the effectiveness of the intelligent controller, simulation results are given to confirm the advantages of the proposed control method, compared with Fuzzy and Proportional integral derivative (PID) control methods.

scholarly journals Efficiency Maximization of Grid-Connected Tidal Stream Turbine System: A Supervisory Energy-Based Speed Control Approach with Processor in the Loop Experiment

2021 ◽  
Vol 13 (18) ◽  
pp. 10216
Author(s):  
Youcef Belkhier ◽  
Nasim Ullah ◽  
Ahmad Aziz Al Alahmadi
Keyword(s):  
Fuzzy Logic ◽  
Closed Loop ◽  
Fuzzy Logic Controller ◽  
High Efficiency ◽  
Reactive Power ◽  
Control Method ◽  
Speed Control ◽  
Power Converter ◽  
Convergence Criterion ◽  
Dc Voltage

Permanent magnet synchronous generator (PMSG) with a back-to-back power converter is one of the commonly used technologies in tidal power generation schemes. However, the nonlinear dynamics and time-varying parameters of this kind of conversion system make the controller computation a challenging task. In the present paper, a novel intelligent control method based on the passivity concept with a simple structure is proposed. This proposed strategy consists of passivity-based speed control (PBSC) combined with a fuzzy logic method to address the robustness problems faced by conventional control techniques such as proportional-integral (PI) control. The proposed method extracts the maximum power from the tidal energy, compensates for the uncertainty in a damped way where the entire dynamics of the PMSG are considered when designing the control law. The fuzzy logic controller is selected, which makes the proposed strategy intelligent to compute the damping gains to make the closed-loop passive and approximate the unstructured dynamics of the PMSG. Thus, the robustness property of the closed-loop system is considerably increased. The regulation of DC voltage and reactive power to their desired values are the principal objectives of the present work. The proposed method is used to control the machine-side converter (MSC), while a conventional PI method is adopted to control the grid-side converter (GSC). Dynamic simulations show that the DC voltage and reactive power errors are extremely reduced with the proposed strategy; ±0.002 for the DC-link voltage and ±0.000015 in the case of the reactive power. Moreover, the lowest steady-state error and better convergence criterion are shown by the proposed control (0.3 × 10−3 s). Generally, the proposed candidate offers high robustness, fast speed convergence, and high efficiency over the other benchmark nonlinear strategies. Moreover, the proposed controller was also validated in a processor in the loop (PIL) experiment using Texas Instruments (TI) Launchpad.

scholarly journals A comparative study on conventional and modern maximum power point tracking algorithms applied to photovoltaic systems

2019 ◽  
Vol 9 (2) ◽  
pp. 29-35
Author(s):  
Rachid Belaidi ◽  
Boualem Bendib ◽  
Djamila Ghribi ◽  
Belkacem Bouzidi ◽  
Mohamed Mghezzi Larafi
Keyword(s):  
Fuzzy Logic ◽  
Comparative Study ◽  
Fuzzy Controller ◽  
Maximum Power ◽  
Photovoltaic System ◽  
Pv System ◽  
Software Environment ◽  
Maximum Power Point ◽  
Pv Systems ◽  
Power Point

The main goal of maximum power point (MPP) tracking control is to extract the maximum photovoltaic (PV) power by finding the optimal operating point under varying atmospheric conditions to improve the efficiency of PV systems. In recent years, the field of tracking the MPP of PV systems has attracted the interest of many researchers from the industry and academia. This research paper presents a comparative study between the modern fuzzy logic based controller and the conventional perturb & observe (P&O) technique. The comparative study was carried out under different weather conditions in order to analyse and evaluate the performance of the PV system. The overall system simulation has been performed using Matlab/Simulink software environment. The simulation results show that the dynamic behaviour exhibited by the modern fuzzy controller outperforms that of the conventional controller (P&O) in terms of response time and damping characteristics.   Keywords: MPPT, photovoltaic system, fuzzy logic control, P&O algorithm.

Improved Output Characteristic of Distributed Hybrid Solar–Wind Generating Materials by Using Fuzzy and Immune MPPT Control Method

2011 ◽  
Vol 321 ◽  
pp. 76-79
Author(s):  
Li Qun Liu ◽  
Chun Xia Liu
Keyword(s):  
Solar Wind ◽  
Electric Power ◽  
Control Method ◽  
Response Speed ◽  
Climatic Conditions ◽  
Output Characteristic ◽  
Maximum Power ◽  
Maximum Power Point ◽  
Power Point ◽  
Response Feedback

The price of photovoltaic (PV) materials and wind generating system (WGS) materials is costly, and the stand-alone PV or WGS can not steadily supplied electric power for end user, fortunately, solar power and wind power can compensate well for one another under various locations and climatic conditions, an efficient maximum power point tracking (MPPT) method for hybrid solar-wind electricity materials is important to extract maximum power from wind and solar energy because of the costly price of PV and WGS. The fuzzy MPPT method is used to track the maximum power point (MPP) of distributed small WGS and PV and hybrid solar-wind system. In order to decrease the output oscillation, the immune response feedback principle (IRFP) is used to improve the track speed and response speed and robust of output characteristic of electricity materials, the results displayed that the immune theory can effectively improve the performance and the stability of electric power of stand-alone or hybrid generating materials.

scholarly journals Fuzzy Logic Controlled PV Based Quasi Impedance Source Inverter for Charge Balancing

2019 ◽  
Vol 9 (1) ◽  
pp. 2633-2638
Keyword(s):  
Control Method ◽  
Fuzzy Controller ◽  
Maximum Power ◽  
Storage Unit ◽  
Maximum Power Point ◽  
Charge Condition ◽  
Energy Storage Unit ◽  
Point Tracking ◽  
Power Point ◽  
Battery Energy

A photovoltaic power generation system based on battery-energy quasi impedance source cascaded multi-level inverter incorporates the advantages of a quasi-impedance source inverter, a CMI, and a battery-energy storage unit. Unbalanced battery charging between cascaded H-bridge inverter modules will degrade the efficiency of an entire system and reduce the lifetime of the battery. This paper proposed a control method for tracking the maximum power point and balancing the SOC of the battery under the large variation of solar input. A fuzzy based optimized linearizer for the battery charge and maximum power point tracking are proposed. The fuzzy controller is proposed to enhance the battery state of charge regulation takes as a individual modules as a loop to reduce over charge condition. The Proposed method validation is done by comparing it with base work control by PI and P&O with the performance parameters. The base work and proposed work are designed and simulated in the Matlab Simulink software.

scholarly journals Design and Simulation of SEPIC Converter with Fuzzy-logic MPPT for Standalone System

2020 ◽  
pp. 112-119
Author(s):  
Sudharsan V N, Dr.K. Ranjith Kumar Rahulkumar J
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Control ◽  
Control Method ◽  
Maximum Power ◽  
Maximum Power Point ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Logic Control ◽  
Control Scheme ◽  
Power Point

This Paper establishes the system of Solar fed independent systems with a SEPIC converter with Dual Input and Dual output. The Maximum power point tracking of solar has been achieved by Fuzzy-logic Control method. The Control scheme implemented in this helps to extract maximum power effectively. The various suitable operations of converter have been achieved through Real time simulator (RTDS) and the outcomes are highlighted.

scholarly journals Optimizing the operation of a photovoltaic generator by a genetically tuned fuzzy controller

2013 ◽  
Vol 23 (2) ◽  
pp. 145-167 ◽  
Author(s):  
Nadia Drir ◽  
Linda Barazane ◽  
Malik Loudini
Keyword(s):  
Genetic Algorithm ◽  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
Fast Response ◽  
Maximum Power ◽  
Photovoltaic System ◽  
Maximum Power Point ◽  
Precise Control ◽  
Power Point

This paper presents design and application of advanced control scheme which integrates fuzzy logic concepts and genetic algorithms to track the maximum power point in photovoltaic system. The parameters of adopted fuzzy logic controller are optimized using genetic algorithm with innovative tuning procedures. The synthesized genetic algorithm which optimizes fuzzy logic controller is implemented and tested to achieve a precise control of the maximum power point response of the photovoltaic generator. The performance of the adopted control strategy is examined through a series of simulation experiments which prove good tracking properties and fast response to changes of different meteorological conditions such as isolation or temperature.

An automatic gear-shifting strategy for manual transmissions

2007 ◽  
Vol 221 (5) ◽  
pp. 757-768 ◽  
Author(s):  
B Mashadi ◽  
A Kazemkhani ◽  
R Baghaei Lakeh
Keyword(s):  
Fuzzy Inference ◽  
Control Method ◽  
Fuzzy Controller ◽  
Step Function ◽  
Maximum Speed ◽  
Vehicle Speed ◽  
Deceleration Phase ◽  
Shifting Strategy ◽  
Automated Manual Transmission ◽  
Driver’S Intention

Based on two different criteria, namely the engine working conditions and the driver's intention, the governing parameters in decision making for gear shifting of an automated manual transmission are discussed. The gear-shifting strategy was designed by taking into consideration the effects of these parameters, with the application of a fuzzy control method. The controller structure is formed in two layers. In the first layer, two fuzzy inference modules are used to determine the necessary outputs. In the second layer a fuzzy inference module makes the decision of shifting by upshift, downshift, or maintain commands. The behaviour of the fuzzy controller is examined by making use of ADVISOR software. It is shown that at different driving conditions the controllers make correct decisions for gear shifting accounting for the dynamic requirements of the vehicle. It is also shown that the controller based on both the engine state and the driver's intention eliminates unnecessary shiftings that are present when the intention is overlooked. A microtrip is designed in which a required speed in the form of a step function is demanded for the vehicle on level or sloping roads. Both strategies for the vehicle to reach the maximum speed starting from rest allow the gear shift to be made consecutively. Considerable differences are observed between the two strategies in the deceleration phase. The engine-state strategy is less sensitive to downshift, taking even unnecessary upshift decisions. The state intention strategy, however, interprets the driver's intention correctly for decreasing speed and utilizes engine brake torque to reduce the vehicle speed in a shorter time.

scholarly journals Artificial Neural Network Controller Strategy for Improving DC Link Voltage of Grid Connected Hybrid PV-Wind Generation Systems

2021 ◽  
Vol 2070 (1) ◽  
pp. 012133
Author(s):  
B. Maheswara Rao ◽  
G.V. Nagesh Kumar ◽  
Vempalle Rafi
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Power System ◽  
Wind Farm ◽  
Control Method ◽  
Climatic Conditions ◽  
Maximum Power ◽  
Step Response ◽  
Neural Network Controller ◽  
Artificial Neural

Abstract This paper presents a power system, consisting of photovoltaic (PV) station and wind farm integrated by ac bus, connected to the grid. The load gets power from both the sources and maximum power is tracked by maximum power point techniques (MPPT) during any changes in the environment. The paper explores how MPPT techniques help power system in tracking power from PV and wind in the conditions of different solar irradiances and different wind speeds. This paper’s objective is to show the improvement in step response of dc link voltage by artificial neural network (ANN) controller. The control method significantly maintains constant grid voltage ensuring unity power factor even during climatic conditions variation. The whole system is simulated using matlab/simulink software and the results compare the proposed system with existing controller i.e., Proportional Integral (PI). The results show the efficient performance of ANN controller than PI controller.

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