Application of fuzzy logic method in wind turbine yaw control system to obtain maximum energy: a methodological and prototype approach

2021 ◽  
Author(s):  
Ramaswamy Bharani ◽  
Arumugam Sivaprakasam
Keyword(s):  
Fuzzy Logic ◽  
Control System ◽  
Wind Turbine ◽  
Maximum Energy ◽  
Yaw Control ◽  
Fuzzy Logic Method ◽  
Logic Method

scholarly journals Fuzzy Regulator Design for Wind Turbine Yaw Control

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Stefanos Theodoropoulos ◽  
Dionisis Kandris ◽  
Maria Samarakou ◽  
Grigorios Koulouras
Keyword(s):  
Fuzzy Logic ◽  
Control System ◽  
Automatic Control ◽  
Wind Turbine ◽  
Power Output ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
Yaw Control ◽  
Fuzzy Regulator ◽  
System Effectiveness

This paper proposes the development of an advanced fuzzy logic controller which aims to perform intelligent automatic control of the yaw movement of wind turbines. The specific fuzzy controller takes into account both the wind velocity and the acceptable yaw error correlation in order to achieve maximum performance efficacy. In this way, the proposed yaw control system is remarkably adaptive to the existing conditions. In this way, the wind turbine is enabled to retain its power output close to its nominal value and at the same time preserve its yaw system from pointless movement. Thorough simulation tests evaluate the proposed system effectiveness.

scholarly journals Penerapan Metode Fuzzy Sugeno Sebagai Sistem Navigasi Robot Menggunakan Mikrokontroler Arduino dan Sensor Ultrasonik

2018 ◽  
Vol 9 (1) ◽  
Author(s):  
Husnawati Husnawati
Keyword(s):  
Fuzzy Logic ◽  
Control System ◽  
Good Control ◽  
Ultrasonic Sensor ◽  
Human Needs ◽  
Fuzzy Logic Method ◽  
Arduino Uno ◽  
Work Done ◽  
Robot Path ◽  
Logic Method

<p align="center"><strong><em>Abstract <br /></em></strong></p><p><em>In the era of industrial technology and automation, robots are widely used as a tool that can ease human work, so the robot which has a good control system is needed so that the work done by the robot can be optimized. The development of control systems in robots is currently quite rapid along with increasingly diverse human needs. Several methods are applied to the robot control system automatically. Fuzzy logic is a method that is most used in navigating robot motion. In this study will be applied Sugeno type fuzzy logic method as a robot navigation system which embedded in Arduino Uno microcontroller and ultrasonic sensor is used as distance input value, in each robot path is given 30 cm obstacle so that the PWM value generated by the robot can be measured. The results obtained in this study is the Sugeno fuzzy logic method which embedded in the Arduino Uno microcontroller can control the motion of the robot and avoid the obstacles in the environment well.</em></p><p><strong><em>Keywords</em></strong><em>:</em><em> Control System, Navigation, Fuzzy Logic, Arduino, Ultrasonic Sensor</em></p><p align="center"><em> </em></p><p align="center"><strong><em>Abstrak <br /></em></strong></p><p><em>Pada era teknologi dan otomasi industri saat ini banyak digunakan robot sebagai alat bantu yang dapat meringankan pekerjaan manusia, sehingga dibutuhkan robot yang memiliki sistem pengendalian yang baik agar pekerjaan yang dilakukan oleh robot tersebut dapat lebih optimal. Perkembangan sistem pengendalian pada robot saat ini cukup pesat seiring dengan kebutuhan manusia yang semakin beragam. Beberapa metode banyak diterapkan pada sistem pengendalian robot secara otomatis. Logika fuzzy merupakan metode yang banyak digunakan dalam navigasi gerak robot. Sehingga pada penelitian ini akan diterapkan metode logika fuzzy dengan tipe Sugeno sebagai sistem navigasi robot yang ditanamkan pada mikrokontroler Arduino uno dan digunakan sensor ultrasonik sebagai nilai inputan jarak, pada masing – masing lintasan robot diberikan halangan sejauh 30 cm sehingga nilai pwm yang dihasilkan oleh robot dapat terukur. Hasil yang diperoleh pada penelitian ini adalah metode logika fuzzy Sugeno yang ditanamkan pada mikrokontroler Arduino uno dapat mengendalikan gerak robot dan menghindari halangan yang berada di sekitar lingkungan dengan baik.</em></p><strong><em>Kata kunci </em></strong><em>: Sistem Kendali, Navigasi, Logika Fuzzy, Arduino, Sensor Ultrasonik.</em>

PID plus fuzzy logic method for torque control in traction control system

2012 ◽  
Vol 13 (3) ◽  
pp. 441-450 ◽  
Author(s):  
H. -Z. Li ◽  
L. Li ◽  
L. He ◽  
M. -X. Kang ◽  
J. Song ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Control System ◽  
Torque Control ◽  
Traction Control ◽  
Traction Control System ◽  
Fuzzy Logic Method ◽  
Logic Method

Prediction of State of Charge (SOC) of Battery Electric Vehicle

2021 ◽  
Vol 104 ◽  
pp. 65-71
Author(s):  
Illa Rizianiza ◽  
Dian Mart Shoodiqin
Keyword(s):  
Fuzzy Logic ◽  
Maximum Energy ◽  
State Of Charge ◽  
Battery Management ◽  
Charge Condition ◽  
Available Energy ◽  
Energy Needs ◽  
Fuzzy Logic Method ◽  
Input Variables ◽  
Charging And Discharging Processes

Batteries have an important thing in development of energy needs. A good performance battery, will support the device it supports. The energy that can save a battery is limited, so the battery will increase its charge and discharge cycles. Incorrect charging and discharging processes can cause battery performance to decrease. Therefore battery management is needed so that the battery can reach the maximum. One aspect of battery management is setting the state which is the ratio of available energy capacitance to maximum energy capacity. One method for estimating load states is the fuzzy logic method, namely by assessing the input and output systems of prediction. Predictor of State of Charge use Mamdani Fuzzy Logic that have temperature and voltage as input variables and State of Charge as output variable. A result of prediction State of Charge battery is represented by the number of Root Mean Square Error. Battery in charge condition has 2.7 for RMSE and level of accuracy 81.5%. Whereas Battery in discharge condition has RMSE 1.5 and level of accuracy 84.7%.

scholarly journals Using WSR-88D Polarimetric Data to Identify Bird-Contaminated Doppler Velocities

2013 ◽  
Vol 2013 ◽  
pp. 1-13 ◽  
Author(s):  
Yuan Jiang ◽  
Qin Xu ◽  
Pengfei Zhang ◽  
Kang Nai ◽  
Liping Liu
Keyword(s):  
Fuzzy Logic ◽  
Real Data ◽  
Radar Data ◽  
Second Step ◽  
Doppler Velocity ◽  
Data Quality Control ◽  
Fuzzy Logic Method ◽  
Automated Technique ◽  
Migrating Birds ◽  
Logic Method

As an important part of Doppler velocity data quality control for radar data assimilation and other quantitative applications, an automated technique is developed to identify and remove contaminated velocities by birds, especially migrating birds. This technique builds upon the existing hydrometeor classification algorithm (HCA) for dual-polarimetric WSR-88D radars developed at the National Severe Storms Laboratory, and it performs two steps. In the first step, the fuzzy-logic method in the HCA is simplified and used to identify biological echoes (mainly from birds and insects). In the second step, another simple fuzzy logic method is developed to detect bird echoes among the biological echoes identified in the first step and thus remove bird-contaminated velocities. The membership functions used by the fuzzy logic method in the second step are extracted from normalized histograms of differential reflectivity and differential phase for birds and insects, respectively, while the normalized histograms are constructed by polarimetric data collected during the 2012 fall migrating season and sorted for bird and insects, respectively. The performance and effectiveness of the technique are demonstrated by real-data examples.

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