Mamdani Fuzzy Logic Research Articles

Lux and current analysis on lab-scale smart grid system using Mamdani fuzzy logic controller

The increasing need for electrical energy requires suppliers to innovate in developing electric distribution systems that are better in terms of quality and affordability. In its development, it is necessary to have a control that can combine the electricity network from renewable energy and the main network through voltage back-up or synchronization automatically. The purpose of this research is to create an innovative lux and current analysis on a lab-scale smart grid system using a fuzzy logic controller to control the main network, solar panel network and generator network to supply each other with lab-scale electrical energy. In the control, Mamdani fuzzy logic controller method is used as the basis for determining the smart grid system control problem solving by adjusting the current conditions on the main network and the light intensity conditions on the LDR sensor. Current conditions are classified in three conditions namely safe, warning, and trip. Meanwhile, the light intensity conditions are classified into three conditions namely dark, cloudy and bright. From the test results, the utility grid (PLN) is at active conditions when the load current is 0.4 A (safe) and light intensity is 1,167 Lux (dark). Then the PLN + PV condition is active when the load current is 1.37 (warning) and the light intensity is 8,680 lux (bright). Finally, the generator condition is active when the load current is 1.6 (trip) and the light intensity is 8,680 (bright). Based on the test results, it is known that the system can work to determine which source is more efficient based on the parameters obtained.

Impact of COVID-19 Induced Lockdown on Environmental Quality in Four Indian Megacities Using Landsat 8 OLI and TIRS-Derived Data and Mamdani Fuzzy Logic Modelling Approach

The deadly COVID-19 virus has caused a global pandemic health emergency. This COVID-19 has spread its arms to 200 countries globally and the megacities of the world were particularly affected with a large number of infections and deaths, which is still increasing day by day. On the other hand, the outbreak of COVID-19 has greatly impacted the global environment to regain its health. This study takes four megacities (Mumbai, Delhi, Kolkata, and Chennai) of India for a comprehensive assessment of the dynamicity of environmental quality resulting from the COVID-19 induced lockdown situation. An environmental quality index was formulated using remotely sensed biophysical parameters like Particulate Matters PM10 concentration, Land Surface Temperature (LST), Normalized Different Moisture Index (NDMI), Normalized Difference Vegetation Index (NDVI), and Normalized Difference Water Index (NDWI). Fuzzy-AHP, which is a Multi-Criteria Decision-Making process, has been utilized to derive the weight of the indicators and aggregation. The results showing that COVID-19 induced lockdown in the form of restrictions on human and vehicular movements and decreasing economic activities has improved the overall quality of the environment in the selected Indian cities for a short time span. Overall, the results indicate that lockdown is not only capable of controlling COVID-19 spread, but also helpful in minimizing environmental degradation. The findings of this study can be utilized for assessing and analyzing the impacts of COVID-19 induced lockdown situation on the overall environmental quality of other megacities of the world.

Determining of Water Saturation Using Fuzzy Logic Method in Mirah-1 Well, Central Sumatra Basin of Indonesia

Water saturation is one important factor in determining the hydrocarbon content in a rock where the less water content in the rock affects the greater the number of hydrocarbons. The purpose of this study is to determine water saturation at various depths in drilling using fuzzy logic. Input variables used are depth, effective porosity, effective porosity of density-neutron log, total porosity, total porosity of density-neutron log. Furthermore, the fuzzy C-Mean Clustering (FCM) method is used to determine the optimal number of rules. The results showed that the prediction of water saturation with zero-order Sugeno fuzzy logic gives better accuracy compared to Mamdani fuzzy logic, BPNN, and LSTM-RNN.

Design, Control, and Simulation of a Neonatal Incubator.

In this project, a fully functional incubator with precise control with respect to temperature, humidity, and airflow was developed and assessed. In parallel with the development of the incubator, a heuristic simulation was created to test and tune the Mamdani fuzzy logic controller. The controller was then applied to the incubator prototype.

The Analysis of Fuzzy Logic Method and Multiple Linear Regression in Determining National Rice Production to Improve Food Self-Sufficiency in Indonesia

Indonesia in 2023 targets rice self-sufficiency. To be included in the category of rice self-sufficiency, Indonesia’s total rice production should be 82 million tons in accordance with Government Regulation No.2 of 2015. The amount of rice production is uncertain. One way to calculate uncertainty in forecasting is by using the Fuzzy Logic of the Mamdani method and the Linear Regression of the Least Squares method. In the Fuzzy Logic Mamdani method there are 4 steps namely; 1) Fuzzy set formation; 2) Application of Implication functions; 3) Composition of Rules; and 4) Defuzzification. Rice Harvested Area, Rice Production and National Rice Consumption are the input variables and National Rice Production is the output variable. The data used are secondary data from the Central Statistics Agency (BPS) and the Ministry of Agriculture Annual Report 2006 - 2017. The data analysis process also uses matlab and minitab software. From the research results obtained that the Fuzzy Logic of the Mamdani method and the Linear Regression of the Smallest Square method can be used to predict the amount of national rice production. For the results of predictions of Fuzzy Logic the Mamdani method has a relatively large error compared to the Linear Regression of the Smallest Squares method. Furthermore it is also known that there is a significant relationship between harvested area and consumption. These two variables will be the determining factors for realizing rice self-sufficiency in Indonesia.

SISTEM PENDUKUNG KEPUTUSAN PENENTUAN POTENSI ANGIN UNTUK PEMBANGKIT LISTRIK TENAGA BAYU (PLTB) MENGGUNAKAN METODE FUZZY MAMDANI

In order to assist the government in realizing the use of 23% of EBT in 2025, to support the direction of government policies and strategies to improve accessibility by providing electricity to remote islands and villages. so in this study, the researcher makes a decision support system for determining the potential of renewable energy, especially energy produced by wind for wind power plants, The method used in this research is the Mamdani Fuzzy Logic, a system consisting of 3 Input criteria, including wind speed, temperature and air pressure, and output is potential for wind energy, output is presented in the form of a percentage unit with a range of 0-100%. The research was conducted in Sumenep Regency, after processing with the Fuzzy Mamdani method, the value of wind potential was generated with the average of the total output data = 43.51%, the value of min = 31.27%, the max value = 49.87%.

Comparative Assessment of Control Strategies Used in a Hybrid AC-DC Micro-Grid Consisting of Composite Energy Sources

In the present paper, comparative assessment of two important available intelligent control strategies namely the Mamdani fuzzy logic controller and the T–S fuzzy controller used for DC-link voltage control in DC micro-grid is carried out, first. Then, a new inverter control technique is proposed to maintain the inverter voltage as well as the DC-link voltage in a hybrid AC-DC micro-grid. The DC micro-grid under study comprises of photovoltaic system, permanent magnet synchronous generator-based wind energy system, battery energy storage system, fuel cell, electrolyzer and DC loads. The complete DC Micro-grid along with its correlated control algorithms are examined and accessed through MATLAB/Simulink environment.

Optimizing parameters in surface reconstruction of transtibial prosthetic socket using central composite design coupled with fuzzy logic-based model

In this paper, a fuzzy logic-based artificial intelligence technique is delineated to optimize surface reconstruction parameters, initiating from raw point cloud data using contactless scanning of transtibial prosthetic socket. The prosthetic socket having a free-form surface is considered for reconstruction of an accurate and complete digital model, which is further crucial for subsequent design, analysis and production. The input factors considered for the socket surface reconstruction includes number of points, filtering, triangle counts and smoothing level. The experimental trials are performed using face-centered central composite design, and further experimental data are used to establish Mamdani fuzzy logic model to predict the surface standard deviation and required space in computer memory as the response parameters. The confirmation experiment results reveal that the fuzzy model shows good agreement of 96.53% with the experimental measured value. Based on the results, it is proved that established fuzzy model can be used for predicting the surface reconstruction parameters to improve the final accuracy of the transtibial prosthetic socket model. The results concluded that the fuzzy logic provides commendable results; in addition, it successfully predicts the effect of different parameters considered for surface reconstruction on surface accuracy and computer file size.

Optimization of Items Production using Fuzzy Logic Mamdani Methods

The availability of a production item is still difficult to monitor by the company, because the system used still relies on manual calculations from employees of the company. Assisting the company in predicting the availability of production goods effectively then used the fuzzy logic calculations. During this time the availability of production goods in Salman Collection is seen from customer's request. This makes the company not get the maximum profit because there is no planning the amount of production of goods, if the number of products manufactured by the company is less than the number of requests then the company will lose the opportunity to Gain maximum profit. Conversely, if the number of products produced is much more than the number of requests then the company will suffer losses. Application of goods production optimization using Fuzzy logic Mamdani method is an application intended to solve the problem of goods production in Salman Collection is uncertain. Implementing Fuzzy logic on solving the problem of production goods can help the company to optimize the production of goods. The construction of this application the company can determine the amount of production that corresponds to consumer demand and by applying Fuzzy logic Mamdani methods Most of the demand in Salman Collection is fulfilled and more optimal than With the old system or the amount in production by the company.

Effectiveness of fuzzy sliding mode control boundary layer based on uncertainty and disturbance compensator on suspension active magnetic bearing system

This paper presents the disturbance and uncertainty suppression by using the nonlinear disturbance observer and an extended state observer for a nonlinear active magnetic bearing system. Otherwise, the chattering free is assured by a fuzzy controller, where the fixed sliding mode surface boundary is regulated by fuzzy boundary layer. The stability of the system is guaranteed by Lyapunov condition. First, the nonlinear disturbance observer is presented to estimate the disturbance from outside of the system. Second, the system parameter variations are estimated by an extended state observer with the construction via the estimated disturbance value. Third, the proportional–integral–derivative sliding mode surface has been constructed due to the chattering values that appear from the high-frequency switching control values. Fourth, these chattering values are reduced by using a Mamdani fuzzy logic control. The proposed control methodology was given by the MATLAB simulation. The overshoot value that is equal to zero, narrow settling time, and the average distance tracking error value which is quite small are archived.

Server Room Temperature and Monitoring System Using Fuzzy Based on RobotDyn Microcontroller

Server role becomes very important to provide service to clients. Therefore the performance of the server needs to be maintained. The performance of the server is not only influenced by the technology of the hardware but also influenced by server room ideal temperature and humidity condition. Monitoring and adjusting temperature condition is not possible to be done continuously manually because of limited human resources. One of the solutions is using a system based on the Internet of Things (IoT). This research proposed a prototype of server room temperature and humidity real-time monitoring system using RobotDyn ATmega+ESP8266 microcontroller and the Blynk IoT platform. The prototype also can maintain the temperature of server room on ideal condition by controlling Air Conditioner using Fuzzy logic Mamdani Method and infrared communication. The result of this research a prototype that can read temperature and humidity of server room accurately realtive error for temperature is 0,81% and relative error for humidity is 4,52%. Quality of Service for data transmission from prototype to Blynk Platform is very good, with average delay 127.54ms, average packet loss ratio 0.54%, average packet delivery ratio 99.46%, and average throughput 10.5 kbps. Control System that built using fuzzy logic Mamdani Method can automatically control the value of Air Conditioner temperature output that adjust the condition of server room with maximum range for control Air Conditioner is 4 meters and 45° from Air Conditioner’s transmitter

Optimasi Produksi Barang Menggunakan Logika Fuzzy Metode Mamdani

Maximum profit gained from maximum sales. Maximum sales means that they can meet the demands. If the products produced by the company is less than requests then the company will lose the opportunity to get maximum profit. Therefore, planning the Amount products in a company is very important in order to meet the market demand precisely and with the appropriate amount. Factors that need to be considered in determining the amount products, such as the demand and supply of old periods. The availability of production goods is still difficult to monitor by the company, because the system is still relying on manual calculations of the company employees, to assist the company in predicting the availability of production goods Effective then used the fuzzy logic calculations. During this time the availability of production goods in Salman Collection is seen from customer request. This makes the company not get the maximum profit because there is no planning the amount of production of goods. This study uses methods with a descriptive approach using the fuzzy logic Mamdani technique. The results of this research is an application of calculation of goods production based on the fuzzy manual calculations of the "logic Mamdani," Built applications can help the company determine the amount of production in accordance with consumer demand so that The demand at Salman Collection is fulfilled and the more optimal the amount that the company will produce.

Sustainability Ranking of Desalination Plants Using Mamdani Fuzzy Logic Inference Systems

As water desalination continues to expand globally, desalination plants are continually under pressure to meet the requirements of sustainable development. However, the majority of desalination sustainability research has focused on new desalination projects, with limited research on sustainability performance of existing desalination plants. This is particularly important while considering countries with limited resources for freshwater such as the United Arab Emirates (UAE) as it is heavily reliant on existing desalination infrastructure. In this regard, the current research deals with the sustainability analysis of desalination processes using a generic sustainability ranking framework based on Mamdani Fuzzy Logic Inference Systems. The fuzzy-based models were validated using data from two typical desalination plants in the UAE. The promising results obtained from the fuzzy ranking framework suggest this more in-depth sustainability analysis should be beneficial due to its flexibility and adaptability in meeting the requirements of desalination sustainability.

Smart grid photovoltaic system pilot scale using sunlight intensity and state of charge (SoC) battery based on Mamdani fuzzy logic control

The Utilization of renewable energy such as a photovoltaic system is the foremost alternative in transfers generated by conventional power plants, but the lack of photovoltaics is support for light intensity. The purpose of this research is to develop a pilot-scale smart grid photovoltaic system that can regulate the supply of electrical energy from either the battery or the power supply. The control system in this study uses the Mamdani fuzzy logic method in determining automatic system performance. This system monitors the intensity of light and battery which are then used as automatic safety parameters on the power supply, battery, and photovoltaic. The results of this study display the indicator results from the microcontroller in supplying electrical energy for the use of electrical loads, Power Supply has been served the load when the battery is in a low state which have a voltage `11 Volts, the battery has been served the load when the condition of the battery is in a medium and high condition which has a voltage of 11.5 `; ....; `13 Volts. PV has been served batteries or loads when the light intensity is cloudy and bright which have a light intensity of 3585 `; ...; `10752 Lux. This system can reduce dependence on conventional energy without reducing the quality of the energy supply at load and Photovoltaic system dependence on light intensity does not affect the supply of energy consumption to electrical loads.

Using Fuzzy Logic to Stabilize the Position of a Multi Rotor

Abstract The article is a continuation of research into a stabilization system for the Unmanned Aerial Vehicle of vertical takeoff and landing. The stabilization system was designed on the basis of a fuzzy logic Mamdani type controller. In the framework of the research, the authors built a test stand with a Multi Rotor model, which allows “Hardware In The Loop” testing in real time. The control system was written in the Matlab/Simulink software and implemented to the Arduino microcontroller.

Fuzzy Logic Controlled Paddle Wheel Aerator

Aeration, as an essential process in the aquaculture industry, has incorporated mechanical aerators especially paddle wheel which is dubbed as the most efficient type. However, an operation of such a device depends on traditional on/off mechanisms based on human intuitions when the need for aeration is necessary. In this paper, Mamdani Fuzzy Logic was integrated into automating the paddlewheel aerator to control and to ensure the correct level of dissolved oxygen in ponds. A microcontroller based on the received output from the dissolved oxygen sensor is capable of automatically controlling the impellers appropriate to the current environment condition. Series of testing was conducted to look at the accuracy of the sensing mechanism and a mean relative error of 1.32% was detected. The researchers compared theoretical and actual supply voltage for all possible dissolved oxygen readings and interpreted a 0.73% mean relative error. With the incorporation of Fuzzy Logic Controller, the system was able to maintain 6 parts per million in the test environment. The system can also reduce power consumption to 65.13% compared to traditional switching. The aerator developed in this study can be used in maintaining the dissolved oxygen in aquaculture farms without human intervention.

Prediksi Tingkat Kriminalitas Menggunakan Fuzzy Logic

Crime is an act of violation of the law that damages morals and social life in society. The purpose of this study is to predict the level of crime so that the results can be considered by related parties. The decisive factors in predicting crime rates in Batam City are unemployment, age and population. Sources of data were obtained from the statistical center agency and the Batam City Barelang Police. To do the crime rate process, use fuzzy logic with the Mamdani method. The input variable consists of unemployment, age and population, while the output is the crime rate. The stages in the processing are done by the Mamdani fuzzy logic that is determining the formation of the fuzzy set. This study produces prediction of crime in Batam City at position 49.5 which is in the medium range, with a population of 50 as inputted, 60 unemployment, and 50 years of age.

Fuzzy Based Fault Classifier and Time Domain Reflectometry Based Fault Locator for Underground Cables

Cables are insulating wires used for transferring power or transmitting signals. If any fault occurs in the cable then, it causes detrimental effects to power system equipments. The technical difficulty is to find, analyze, and classify faults. In case of underground cables it will be a time consuming and expensive process to repair the faults or replace the cables. This paper aims to analyse the faults by creating the various types of short and open circuit faults, classify them by taking in account of grounding, and to locate the distance at which the fault is occurred. The underground cable is simulated using MATLAB/ Simulink, the faults are created and the Fourier transform of voltage and current are observed at the source end. The generated fault phase current data from the simulation has been normalized using fault index is the input to the Mamdani fuzzy logic controller. The defuzzified output is verified for different phase current values which classify the nature of the fault. Two fuzzy classifiers like ground and phase faults are developed which holds good for different range of cables. A methodology to find the fault location in long transmission line is attempted using PSPICE, by creating short circuit fault. The distance is determined by using velocity of propagation of travelling waves, which is realized using impulse voltage wave generator which is based on impedance

Penerapan Metode Fuzzy Mamdani Untuk Menentukan Stok Produk Herbal Berdasarkan Permintaan dan Penjualan

Sales is one of the activities undertaken by many people as a promising business field. Prediction of the number of items to be sold must be in accordance with stock at the store so that demand and sales can be fulfilled. Therefore, we need a system to find out the amount of stock of herbal products so they do not experience problems in determining stock in each month. By using the Fuzzy Mamdani method as an algorithm for solving the problem, and the criteria are changed in the form of weighting so that the system can do calculations that provide the speed of information in the form of a computerized system. The results of this study aim to apply the Mamdani fuzzy logic method in predicting the amount of herbal product stock based on sales data and the number of requests. Provides results in the form of information printed in a report containing order data for the number of subsequent stock orders

SIMULASI PENENTUAN WAKTU MEMASAK BUAH KELAPA SAWIT MENGGUNAKAN LOGIKA FUZZY

Simulation is a technique to imitate the operations or processes - processes that occur in a system with the help of computer equipment and based on certain assumptions that the system can be studied scientifically useful to facilitate in solving a problem. In designing this system using fuzzy logic mamdani. This research focused to know the cooking time by two palm fruit input variables. The first input is a lot of oil in a fuzzy set is grouped into three namely, small, medium, and a lot. As the second input is a great pressure of water vapor which is divided into three fuzzy sets are small, normal, and large. As the output variable is the time to cook the fruit in the palm of krlompokan into three fuzzy sets namely, fast, medium and slow. In this simulation design used fuzzy logic matlab mamdani with the help of software. Keywords : fuzzy logic, quick learning fuzzy logic, fuzzy logic applications, Simulation