Design and Implementation of Neuro-Fuzzy Controller Using FPGA for Sun Tracking System

2016 ◽  
Vol 12 (2) ◽  
pp. 123-136 ◽  
Author(s):  
Ammar Aldair ◽  
Adel Obed ◽  
Ali Halihal
Keyword(s):  
Optical Sensors ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
Tracking System ◽  
Maximum Power ◽  
Experimental Results ◽  
The Sun ◽  
Fixed Angle ◽  
Pv Panel ◽  
Neuro Fuzzy

Nowadays, renewable energy is being used increasingly because of the global warming and destruction of the environment. Therefore, the studies are concentrating on gain of maximum power from this energy such as the solar energy. A sun tracker is device which rotates a photovoltaic (PV) panel to the sun to get the maximum power. Disturbances which are originated by passing the clouds are one of great challenges in design of the controller in addition to the losses power due to energy consumption in the motors and lifetime limitation of the sun tracker. In this paper, the neuro-fuzzy controller has been designed and implemented using Field Programmable Gate Array (FPGA) board for dual axis sun tracker based on optical sensors to orient the PV panel by two linear actuators. The experimental results reveal that proposed controller is more robust than fuzzy logic controller and proportional-integral (PI) controller since it has been trained offline using Matlab tool box to overcome those disturbances. The proposed controller can track the sun trajectory effectively, where the experimental results reveal that dual axis sun tracker power can collect 50.6% more daily power than fixed angle panel. Whilst one axis sun tracker power can collect 39.4 % more daily power than fixed angle panel. Hence, dual axis sun tracker can collect 8 % more daily power than one axis sun tracker.

MEDIUM SIZE DUAL-AXIS SOLAR TRACKING SYSTEM WITH SUNLIGHT INTENSITY COMPARISON METHOD AND FUZZY LOGIC IMPLEMENTATION

2015 ◽  
Vol 77 (17) ◽  
Author(s):  
Azwaan Zakariah ◽  
Mahdi Faramarzi ◽  
Jasrul Jamani Jamian ◽  
Mohd Amri Md Yunus
Keyword(s):  
Fuzzy Logic ◽  
Solar Irradiance ◽  
Fuzzy Logic Controller ◽  
Solar Power ◽  
Tracking System ◽  
Medium Size ◽  
The Sun ◽  
Solar Pv ◽  
Pv Panel ◽  
Solar Tracking

Nowadays, renewable energy such as solar power has become important for electricity generation, and solar power systems have been installed in homes. Furthermore, solar tracking systems are being continuously improved by researchers around the world, who focus on achieving the best design and thus maximizing the efficiency of the solar power system. In this project, a fuzzy logic controller has been integrated and implemented in a medium-scale solar tracking system to achieve the best real-time orientation of a solar PV panel toward the sun. This project utilized dual-axis solar tracking with a fuzzy logic intelligent method. The hardware system consists of an Arduino UNO microcontroller as the main controller and Light Dependent Resistor (LDR) sensors for sensing the maximum incident intensity of solar irradiance. Initially, two power window motors (one for the horizontal axis and the other for the vertical axis) coordinate and alternately rotate to scan the position of the sun. Since the sun changes its position all the time, the LDR sensors detect its position at five-minute intervals through the level of incident solar irradiance intensity measured by them. The fuzzy logic controller helps the microcontroller to give the best inference concerning the direction to which the solar PV panel should rotate and the position in which it should stay. In conclusion, the solar tracking system delivers high efficiency of output power with a low power intake while it operates.

Neuro Fuzzy Controller for DTC of Induction Motor Using Multilevel Inverter with SVM

2021 ◽  
pp. 2150250
Author(s):  
B. Kiran Kumar ◽  
Y. V. Siva Reddy ◽  
M. Vijaya Kumar
Keyword(s):  
Induction Motor ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
Reference Voltage ◽  
Training Dataset ◽  
Testing Time ◽  
Hybrid Technique ◽  
Nonlinear Loads ◽  
Neuro Fuzzy ◽  
Voltage Signal

In this paper, an effective neuro-fuzzy controller (NFC) technique has been proposed to control the induction motor torque and flux. The NFC hybrid technique is the grouping of the neural network (NN) and fuzzy logic controller (FLC), which generated the target voltages with the corresponding input flux and torque. The novelty of the proposed hybrid technique is highly flexible in nonlinear loads, convenient user interface and logical intellectual and permitting for integrated controlling schemes. Here, the FLC generates the training dataset of the NN technique based on the logical rules. The generated dataset contains the information about the flux and torque deviation parameters and the corresponding reference voltage parameters. The NN has been trained based on training dataset and the testing time which produces the optimal reference voltage parameters depends on the variation of the torque and flux parameters. By using the output of the NFC technique, the space vector modulation (SVM) develops the appropriate control pulses to the five-level inverter and the inverter generates the output voltage signal to the induction motor. The proposed method is designed in the MATLAB/Simulink platform and the outputs are verified through the comparison analysis with the existing techniques.

A Fuzzy Logic Controlled Single Axis Solar Tracking System

2015 ◽  
Vol 787 ◽  
pp. 893-898
Author(s):  
Suneetha Racharla ◽  
K. Rajan ◽  
K.R. Senthil Kumar
Keyword(s):  
Fuzzy Controller ◽  
Tracking System ◽  
Renewable Energy Sources ◽  
Energy Resource ◽  
Clean Energy ◽  
Energy Sources ◽  
Pv Panel ◽  
Solar Tracking ◽  
Simulation Results ◽  
Improved Performance

Recently renewable energy sources have gained much attention as a clean energy. But the main problem occurs with the varying nature with the day and season. Aim of this paper is to conserve the energy, of the natural resources. For solar energy resource, the output induced in the photovoltaic (PV) modules depends on solar radiation and temperature of the solar cells. To maximize the efficiency of the system it is necessary to track the path of sun in order to keep the panel perpendicular to the sun. This paper proposes the design and construction of a microcontroller-based solar panel tracking system. The fuzzy controller aims at maximizing the efficiency of PV panel by focusing the sunlight to incident perpendicularly to the panel. The system consists of a PV panel which can be operated with the help of DC motor, four LED sensors placed in different positions and a fuzzy controller which takes the input from sensors and gives output speed to motor. A prototype is fabricated to test the results and compared with the simulation results. The results show the improved performance by using a tracking system

BACKPROPAGATION THROUGH TIME TRAINING OF A NEURO-FUZZY CONTROLLER

2010 ◽  
Vol 20 (05) ◽  
pp. 421-428 ◽  
Author(s):  
PETIA KOPRINKOVA-HRISTOVA
Keyword(s):  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
Fuzzy Rule ◽  
Linguistic Meaning ◽  
Rule Base ◽  
Linguistic Variables ◽  
Backpropagation Through Time ◽  
Linear Plant ◽  
Neuro Fuzzy ◽  
Neural Network Structure

The paper considers gradient training of fuzzy logic controller (FLC) presented in the form of neural network structure. The proposed neuro-fuzzy structure allows keeping linguistic meaning of fuzzy rule base. Its main adjustable parameters are shape determining parameters of the linguistic variables fuzzy values as well as that of the used as intersection operator parameterized T-norm. The backpropagation through time method was applied to train neuro-FLC for a highly non-linear plant (a biotechnological process). The obtained results are discussed with respect to adjustable parameters rationality. Conclusions are made with respect to the appropriate intersection operations too.

scholarly journals Wheelchair Neuro Fuzzy Control and Tracking System Based on Voice Recognition

Sensors ◽  
2020 ◽  
Vol 20 (10) ◽  
pp. 2872 ◽  
Author(s):  
Mokhles M. Abdulghani ◽  
Kasim M. Al-Aubidy ◽  
Mohammed M. Ali ◽  
Qadri J. Hamarsheh
Keyword(s):  
Fuzzy Controller ◽  
Tracking System ◽  
Voice Recognition ◽  
Real Data ◽  
Communication Technologies ◽  
Real Time Control ◽  
Time Control ◽  
Smart Wheelchairs ◽  
Neuro Fuzzy ◽  
The Disabled

Autonomous wheelchairs are important tools to enhance the mobility of people with disabilities. Advances in computer and wireless communication technologies have contributed to the provision of smart wheelchairs to suit the needs of the disabled person. This research paper presents the design and implementation of a voice controlled electric wheelchair. This design is based on voice recognition algorithms to classify the required commands to drive the wheelchair. An adaptive neuro-fuzzy controller has been used to generate the required real-time control signals for actuating motors of the wheelchair. This controller depends on real data received from obstacle avoidance sensors and a voice recognition classifier. The wheelchair is considered as a node in a wireless sensor network in order to track the position of the wheelchair and for supervisory control. The simulated and running experiments demonstrate that, by combining the concepts of soft-computing and mechatronics, the implemented wheelchair has become more sophisticated and gives people more mobility.

scholarly journals An Intelligent Maximum Power Point Tracking Algorithm for Photovoltaic System

2018 ◽  
Vol 7 (4.35) ◽  
pp. 457
Author(s):  
M. I. Iman ◽  
M. F. Roslan ◽  
Pin Jern Ker ◽  
M. A. Hannan
Keyword(s):  
Fuzzy Logic Controller ◽  
Boost Converter ◽  
Maximum Power ◽  
Photovoltaic System ◽  
Resistive Load ◽  
Pv System ◽  
Maximum Power Point ◽  
Point Tracking ◽  
Pv Panel ◽  
Power Point

This work comprehensively demonstrates the performance analysis of Fuzzy Logic Controller (FLC) with Particle Swarm Optimization (PSO) Maximum Power Point Tracker (MPPT) algorithm on a stand-alone Photovoltaic (PV) applications systems. A PV panel, DC-DC Boost converter and resistive load was utilized as PV system. Three different MPPT algorithms were implemented in the converter. The result obtained from the converter was analyzed and compared to find the best algorithm to be used to identify the point in which maximum power can be achieve in a PV system. The objective is to reduce the time taken for the tracking of maximum power point of PV application system and minimize output power oscillation. The simulation was done by using MATLAB/Simulink with DC-DC Boost converter. The result shows that FLC method with PSO has achieved the fastest response time to track MPP and provide minimum oscillation compared to conventional P&O and FLC techniques.

Fuzzy and neuro-fuzzy approaches to control a flexible single-link manipulator

2003 ◽  
Vol 217 (5) ◽  
pp. 387-399 ◽  
Author(s):  
B Subudhi ◽  
A S Morris
Keyword(s):  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
Fuzzy Model ◽  
Scale Parameters ◽  
Neuro Fuzzy ◽  
On Line ◽  
Position Regulation ◽  
Tip Position ◽  
Typical Model ◽  
Better Than

In this paper, new fuzzy and neuro-fuzzy approaches to tip position regulation of a flexible-link manipulator are presented. Firstly, a non-collocated, proportional-dervative (PD) type, fuzzy logic controller (FLC) is developed. This is shown to perform better than typical model-based controllers (LQR and PD). Following this, an adaptive neuro-fuzzy controller (NFC) is described that has been developed for situations where there is payload variability. The proposed NFC tunes the input and output scale parameters of the fuzzy controller on-line. The efficacy of the NFC has been evaluated by comparing it with a fuzzy model reference adptive controller (FMRC).

scholarly journals IMPROVING THE EFFICIENCY OF A PHOTOVOLTAIC SYSTEM BY INCORPORATING TRACKING SYSTEM AND MPPT: A REVIEW

2018 ◽  
Vol 17 (1) ◽  
pp. 57
Author(s):  
S Udhayakumar ◽  
R A Sindhu ◽  
R Srivasthan ◽  
Y Yogaraj
Keyword(s):  
Tracking System ◽  
Power Conversion ◽  
Maximum Power ◽  
Photovoltaic System ◽  
The Sun ◽  
Solar Panels ◽  
Maximum Power Point ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Power Point

The harvesting of solar energy is gaining increasing attention as it is pollution free and is available in abundance. Various researches and experiments are being carried out to improve the efficiency of power conversion by altering the material of the photovoltaic panels, by incorporating tracking systems and by making use of Maximum Power Point Tracking (MPPT) algorithms. The conventional rigidly fixed solar panels limit their area of exposure to the sun during the entire day. The use of tracker increases the area of panel exposed to direct beam of the sun, thus increasing the power generated. MPPT algorithm tracks the maximum power point attained at all loads and extracts the power from the panel at that voltage. Despite the variations in the external environment, the power obtained from the panel is always maximum. This paper reviews various tracking methods and MPPT techniques to increase the energy harvesting capacity of the panel and in turn improve its efficiency.

scholarly journals Real-Time Experimental Assessment of a New MPPT Algorithm Based on the Direct Detection of the Short-Circuit Current for a PV System

2021 ◽  
Vol 19 ◽  
pp. 598-603 ◽  
Author(s):  
C.B. Nzoundja Fapi ◽  
◽  
P. Wira ◽  
M. Kamta ◽  
Keyword(s):  
Fuzzy Logic Controller ◽  
Direct Detection ◽  
Short Circuit ◽  
Short Circuit Current ◽  
Maximum Power ◽  
Solar Irradiation ◽  
Pv System ◽  
Maximum Power Point ◽  
Pv Panel ◽  
Power Point

To substantially increase the efficiency of photovoltaic (PV) systems, it is important that the Maximum Power Point Tracking (MPPT) system has an output close to 100%.This process is handled by MPPT algorithms such as Fractional Open-Circuit Voltage (FOCV), Perturb and Observe (P&O), Fractional Short-Circuit Current (FSCC), Incremental Conductance (INC), Fuzzy Logic Controller (FLC) and Neural Network (NN) controllers. The FSCC algorithm is simple to be implemented and uses only one current sensor. This method is based on the unique existence of the linear approximation between the Maximum Power Point (MPP) current and the short-circuit current in standard conditions. The speed of this MPPT optimization technic is fast, however this algorithm needs to short-circuit the PV panel each time in order to obtain the short circuit current. This process leads to energy losses and high oscillations. In order to improve the FSCC algorithm, we propose a method based on the direct detection of the shortcircuit current by simply reading the output current of the PV panel. This value allows directly calculating the short circuit current by incrementing or decrementing the solar irradiation. Experimental results show time response attenuation, little oscillations, power losses reduction and better MPPT accuracy of the enhanced algorithm compared to the conventional FSCC method.

Output Power Enhancement of Solar PV Panel Using Solar Tracking System

2019 ◽  
Vol 12 (1) ◽  
pp. 45-49
Author(s):  
Abhishek Kumar Tripathi ◽  
Mangalpady Aruna ◽  
Ch. S.N. Murthy
Keyword(s):  
Solar Radiation ◽  
Output Power ◽  
Tracking System ◽  
The Sun ◽  
Solar Pv ◽  
Design Development ◽  
Pv Panel ◽  
Solar Tracking ◽  
Power Enhancement ◽  
Panel Surface

Solar Photovoltaic (PV) energy conversion has gained much attention nowadays. The output power of PV panel depends on the condition under which the panel is working, such as solar radiation, ambient temperature, dust, wind speed and humidity. The amount of falling sunlight on the panel surface (i.e., solar radiation) directly affects its output power. In order to maximize the amount of falling sunlight on the panel surface, a solar tracking PV panel system is introduced. This paper describes the design, development and fabrication of the solar PV panel tracking system. The designed solar tracking system is able to track the position of the sun throughout the day, which allows more sunlight falling on the panel surface. The experimental results show that there was an enhancement of up to a 64.72% in the output power of the PV panel with reference to the fixed orientation PV panel. Further, this study also demonstrates that the full load torque of the tracking system would be much higher than the obtained torque, which is required to track the position of the sun. This propounds, that the proposed tracking system can also be used for a higher capacity PV power generation system.

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