Fuzzy Logic Based Control System Research Articles

Chicken Egg Hatching Optimization with Automatic Control Using Fuzzy Logic<b></b>

Egg hatching is an important process in the livestock industry to produce quality poultry seedlings. In the hatching process environmental conditions such as temperature and humidity must be carefully regulated to ensure optimal hatching. In an effort to improve the efficiency and accuracy of hatching, this research introduces an egg hatching machine tool that adopts a fuzzy logic approach. The developed machine tool is equipped with temperature and humidity sensors that measure the environmental conditions inside the egg incubator in real-time. The data obtained from the sensors are used as inputs for a fuzzy logic-based control system that regulates the temperature and humidity of the incubator. The hatching machine is built keeping in mind the ideal conditions between 35° - 40° with 70% - 80% humidity. Fuzzy logic allows the system to handle uncertainty and ambiguity in temperature and humidity settings. Based on the fuzzy rules set, the system can adaptively adjust the environmental conditions to achieve optimal conditions for hatching eggs.

Использование нечеткой логики в системе управления технологическим комплексом напыления покрытий летательных аппаратов

The reliability of aircraft is ensured by various functional coatings applied to them. The quality indicators of coatings are determined by the capabilities of the control system for the technological complex of their spraying. The control system is effective if, with a large number of input parameters, it adopts the optimal technological solution to achieve the set values of coating quality indicators. The use of fuzzy logic in the control system of the technological complex of coating spraying is proposed. Using the Fuzzy Logic Toolbox package of the MATLAB program, an analysis of the fuzzy logic-based control system for the technological operation of applying a sprayed composition to a coated surface was carried out. It is shown that the use of fuzzy logic as an element of artificial intelligence is effective in the control system of the technological spraying process.

Application of Fuzzy logic and IoT in a small-scale Smart Greenhouse System

This research aims to address the critical challenges caused by global population increase, climate change, and urbanization on food production by means of a Fuzzy Logic controller in a small-scale greenhouse and improving agricultural efficiency and sustainability.The growing global population has stressed the significance of implementing efficient food production techniques. Furthermore, the impact of climate change and extreme weather events complicates the production process. The goal of this study is to combine an innovative small greenhouse design with a fuzzy logic-based control system in order to develop an IoT-enabled self-regulating environment for autonomous plant growing.Continuous advances in technology have been focusing on automating greenhouses to provide self-regulating microclimates and optimal developmental conditions. Current trends focus on automating greenhouses to provide self-regulating microclimates. Looking ahead, the strategy entails combining automated approaches with precisely planned structures via IoT.This study's key findings include the successful integration of a fuzzy logic control system with greenhouse infrastructure, allowing for real-time monitoring and adjustment of environmental parameters, as well as the development of a pilot IoT ecosystem demonstrating the feasibility of self-regulating microclimates for improved plant growth.

Fuzzy Logic-Based Energy Storage Control in Smart Grids for Grid Stability

This study studies the usefulness of fuzzy logic-based control systems for improving energy storage control inside smart grids to promote grid stability. The study combines empirical data analysis, including energy storage system (ESS) specifications, smart grid operational data, fuzzy logic-based control rules, and ESS state variables, to demonstrate the suitability and efficiency of using fuzzy logic-based control mechanisms in dynamic grid environments. The examination of ESS specs revealed a wide range of maximum capacities, spanning from 100 kWh to 200 kWh. Additionally, the charge and discharge efficiencies exhibited variations, ranging from 85% to 96%. An analysis of operational data from the smart grid revealed significant variations in grid frequency, ranging from 50.0 Hz to 50.3 Hz. Voltage levels also exhibited fluctuations, ranging from 229 kV to 232 kV. Additionally, renewable energy generation from solar and wind sources showed fluctuations between 1400 kW to 1650 kW and 800 kW to 850 kW, respectively. The incorporation of linguistic factors and fuzzy rules based on grid parameters facilitated the adaptive control of ESS units in the construction of fuzzy logic-based control rules. The analysis of ESS state variables revealed dynamic changes in the state of charge, which ranged from 60% to 90%. Additionally, oscillations in available energy were observed across different timestamps and ESS units. An investigation of in state variables, revealed adaptive changes percentage change demonstrating varying degrees of variations in state of charge, available energy, and operational states at various timestamps. The results emphasize the flexibility and efficiency of control systems based on fuzzy logic in improving energy storage operations in smart grids, highlighting their capacity to improve grid stability and efficiently handle changing grid characteristics.

2 in 1 Humidifier + Air Purifier Fuzzy Control System

In this modern era, smart home appliance control has quickly penetrated the market. This study explains the design and simulation results of a 2-in-1 humidifier + air purifier control system based on fuzzy rules. The rule block obtains three hard shell input values from air quality, humidity, and water level sensor, divides the sermon space into sections of each individual section with two (2) fuzzy variables, activates rules, and extends the singleton output value to match the output variables individually. Two defuzzifiers are arranged to adjust two actuators: the speed of the humidifier and the speed of the air purifier. The results obtained by MATLAB simulation are consistent with the proposed model, and accurate values are obtained. This study will expand the capabilities of fuzzy logic-based control systems in the process of systematization and potential returns. Using MATLAB Simulink R2016b, the design goals are achieved.

Design of Battery Energy Storage System (BESS) with Fuzzy Control for Pico Hydro

Pico hydro system, a combination of hydro turbine governor, electronic load controller, and generator are outlined as one of the recommended approaches for off-grid power supply option for rural areas communities. In a conventional installation of a hydro system, an electronic load controller with proportional–integral–derivative (PID) is the best alternative to provide power balancing between power generation and load-consuming demand. However, there is always a peak in power demand during the day, but the energy consumption is low at night. This situation caused much energy to be dumped and wasted and a lack of energy management regarding the plant's power stability. Therefore, this research aimed to design fuzzy logic control (FLC) for an energy system that could meet the critical load requirement before being simulated using MATLAB SIMULINK to evaluate the effective utilization of the excess energy. Using Mamdani's methods with 25 membership rules to implement a fuzzy logic-based control system could potentially perform efficient power flow control between scenarios such as discharging, battery backup, and load supply. The result showed that this approach is a better alternative and more efficient system stabilization and energy supply by implementing fuzzy control in surplus power generation from the pico hydro system from 2 sec to 3 sec.

Kontrol Fuzzy Logic Dalam Menentukan Produksi Air Demin Pada PLTU

Demineralized water production that is not in accordance with the supplies needed in a power plant results in less effective and efficient operation of the power plant. This requires careful control. The control system can use a fuzzy logic-based control system. In this article, we describe the trial of controlling the production of demin water with the aim of determining the production of electricity for consumer needs. The method used is fuzzy logic control. The result can adjust the supply of demin water according to the available stock and the number of requests. The electricity production resulting from fuzzy calculations in generating electricity production is the Tsukamoto method of 698.3 MW/day, the Mamdani method of 254.16 MW/day, and the Sugeno method of 537.3 MW/day.

Application of SMES Technology in Improving the Performance of a DFIG-WECS Connected to a Weak Grid

Wind Turbine Generator (WTG) has become one of the most popular renewable-based power generation that is broadly connected to electricity grids worldwide. Till the year 2019, the total WTGs installed worldwide reached about 650.8GW. The WTG is interfaced to the electricity grid through power electronic converters with a proper control algorithm to facilitate a smooth power delivery as well as maintaining the system voltage and frequency stability during wind intermittency. However, power grids are usually subjected to load expansion which affects the stiffness of the grid and hence its stability. A weak electricity grid exhibits voltage instability that may affect the performance of WTGs and in some cases may lead to serious damages to the wind turbines and the entire system. In this paper, superconducting magnetic energy storage (SMES) technology based on fuzzy logic controller is implemented to effectively resolve this issue and improve the overall performance of WTGs. Hysteresis current and fuzzy logic-based control system is proposed to control the energy exchange between the SMES coil and the investigated system. Results show the effectiveness of the SMES to improve the overall system performance and along with the fault ride-through capability of the doubly-fed induction generator (DFIG).

Fuzzy logic-based control system of a robocar based on software control of the electric motor power

Fuzzy logic-based control system of a robocar based on software control of the electric motor power

Fuzzy Logic based control system and Artificial Intelligence in Industrial Automation

Amidst the AI driven world, the Automation plays a major role in every sector. Usually the control systems in industries are manually controlled in unpredictable conditions. We are in need of a human to control a system. In this affair an AI trained machine acts as a human replica to drive it fully automated. The highly labor-intensive industries can be benefited by the use of Artificial Intelligence in the automation part, this reduces the human errors and safeguard them from risky areas. The fuzzy based PID controller is used here because it acts as Human-in-the-loop behind the whole process. This helps in tuning the PID controller to set a desired value which enhances the gains, adding to that it gives a high accuracy and brings up more flexibility in changing the rules. The result which is obtained is simulated in MATLAB with overshoot difference.

A Fuzzy Logic-based Control System for Microwave Ovens

Conventional microwave ovens rely on users for their cooking time. In other words, the user must set the oven’s cooking time manually. This paper aims to design a fuzzy logic-based controller to resolve the above-mentioned issue by determining the cooking time of the microwave oven automatically. The time determined depends on the quantity and type of food. During the fuzzy logic process, we used the Mamdani fuzzy model. This model involves determining the crisp input, fuzzification, rule evaluation, and defuzzification, to obtain the crisp output result. Input real variables used were the type of food and quantity of food, whereas the output variable used was cooking time. A fuzzy logic toolbox on MATLAB software was used to design and simulate the whole system. Considering the IF-THEN rules and functions, we used the value of food as 50, and the type of food as 50 and we obtained the cooking time as 25 minutes. The result showed that Fuzzy models are good at determining cooking time in Microwave ovens and that their cooking time depends on the inputs. Using fuzzy logic in microwave ovens helps to maintain food quality, saves users’ time, and controls the energy used by the oven.

Fuzzy Logic Controller for Classroom Air Conditioner

In the modernized era, the air conditioners are an integrated part of comfort living especially in hot climates. They are used to control the interior spatial temperature, relative humidity, degree of cleanliness, and speed of air streaming. The automatic controllers are the key elements of the modern air conditioning systems that ensure the reliable operation, improved quality, low operation cost, and better security. Thus, the realization, design, and application of the controller systems require the exact specifications of the involved processes. In this regard, controllers based on the fuzzy logic (FL) are prospective for air conditioners due to the easy accessibility of different output levels. Furthermore, using the FL it is possible to scale and control the users’ air processing demand depending on the temperature and relative humidity of the space. Based on these factors, this paper reports the design and performance evaluation of a FL based controller useful for air conditioners when implemented in the classroom setting. This FL based control system can reduce the complexity of programming thereby can be executed on general microcontrollers utilized in the control panels of classroom air conditioner. The results revealed the outperforming nature of the FL based controllers over other traditional controllers used to adjust the indoor temperature and relative humidity by air conditioners.

A Fuzzy Logic Control System for a Robotic Hand Driven by Shape Memory Alloy Wires

This paper presents a robotic hand using wires with shape memory (NiTi) as non-conventional actuators. The mechanical structure of the robot hand was first designed by means of a CAD computer program and afterwards 3D printed using ABS polymer. The robotic hand was designed according to the physiological characteristics of the human hand, with particular attention to the angles formed by the phalanges of the fingers. A mechanical system accommodates the thin NiTi wires compactly, thus forming an artificial muscle. A fuzzy logic based control system allows an accurate positioning of each phalanx. The contribution of the present work to science lies in the practical implementation of known techniques and materials.

A Fuzzy Logic Control System for a Robotic Hand Driven by Shape Memory Alloy Wires

This paper presents a robotic hand using wires with shape memory (NiTi) as non-conventional actuators. The mechanical structure of the robot hand was first designed by means of a CAD computer program and afterwards 3D printed using ABS polymer. The robotic hand was designed according to the physiological characteristics of the human hand, with particular attention to the angles formed by the phalanges of the fingers. A mechanical system accommodates the thin NiTi wires compactly, thus forming an artificial muscle. A fuzzy logic based control system allows an accurate positioning of each phalanx. The contribution of the present work to science lies in the practical implementation of known techniques and materials.

Fuzzy Logic-Based Control for a Morphing Wing Tip Actuation System: Design, Numerical Simulation, and Wind Tunnel Experimental Testing.

The paper presents the design, numerical simulation, and wind tunnel experimental testing of a fuzzy logic-based control system for a new morphing wing actuation system equipped with Brushless DC (BLDC) motors, under the framework of an international project between Canada and Italy. Morphing wing is a prime concern of the aviation industry and, due to the promising results, it can improve fuel optimization. In this idea, a major international morphing wing project has been carried out by our university team from Canada, in collaboration with industrial, research, and university entities from our country, but also from Italy, by using a full-scaled portion of a real aircraft wing equipped with an aileron. The target was to conceive, manufacture, and test an experimental wing model able to be morphed in a controlled manner and to provide in this way an extension of the laminar airflow region over its upper surface, producing a drag reduction with direct impact on the fuel consumption economy. The work presented in the paper aims to describe how the experimental model has been developed, controlled, and tested, to prove the feasibility of the morphing wing technology for the next generation of aircraft.

A hybrid model predictive and fuzzy logic based control method for state of power estimation of series-connected Lithium-ion batteries in HEVs

Abstract Accurate estimation of the State of Power (SoP) can ensure safe and efficient operation of Lithium-ion batteries in Electric Vehicles (EVs) and Hybrid Electric Vehicles (HEVs). The cell-to-cell variation within a battery pack is a major challenge towards accurate estimation of the SoP, particularly when the cells get aged. This paper presents a hybrid model predictive and fuzzy logic based control system to accurately estimate the SoP for series-connected Lithium-ion cells. The estimation strategy consists of two steps; the power capability for a single new cell is first reckoned under the light of the model predictive control algorithm. The second step is devoted to designation of a model-less fuzzy logic based control system to compensate for the concurrent aging state and State of Charge (SoC) differences among the cells. Accordingly, the present approach only utilizes the actual values of current and cell voltages together with the Electric Circuit Model (ECM) parameters of the new cell, which are identified off-line. Moreover, it benefits from a closed-loop framework which ends in an accurate and reliable SoP estimation. An experimental setup consisting of fresh and aged LiFePO4 cell samples is designed and the extracted data are utilized to verify the proposed estimation method in a feed-forward simulation model for a HEV. The results indicate that the proposed method can estimate the pack SoP accurately while the safe operation for the cells is guaranteed.

Simulation, Fuzzy Analysis and Development of ZnO Nanostructure-based Piezoelectric MEMS Energy Harvester

Fuzzy logic-based control systems are widely used in various fields like home appliances, medical instruments, automobiles, textile machinery, agriculture equipment and aviation for process control and data analysis. Fuzzy logic technique has shown great potential to solve the complex problems of physical world due to similarity with human understanding. Its advancements have gained widespread attention in different research areas. In several cases, it is very suitable for electronic devices which need to be precisely self-powered. In this work, an ANSYS-based simulation, fuzzy analysis, development and testing of a microelectromechanical system (MEMS)-based energy harvester have been presented. Zinc oxide (ZnO) nano rods were synthesized on an anodic aluminum oxide (AAO) template to form the MEMS energy harvester and study the effect of energy generation by applying force. The power of 5.16 nano Watts has been obtained by taking the numerical value of voltage (Voc) and current (Isc) as 3.16 mV and 0.985 µA respectively using fuzzy logic tool. Experimental testing of the harvester shows that the range of Voc is 3–6.4 mV and Isc is 0.45–1.5 μA. The results depict that this device can be used for touch screens to generate energy that can be further utilized for charging smart devices.

퍼지논리제어기 설계를 위한 새로운 비퍼지화 방법과 수치 예를 통한 성능 분석

최근 우주항공분야 등과 같이 제어대상 시스템은 점점 더 복잡하고, 요구되는 제어 성능의 우수성은 더욱 강화되고 있다. 이러한 요구조건에 부합하는 제어기로 퍼지논리 기반의 지능제어기가 널리 활용되고 있다. 퍼지논리 기반의 지능제어기를 퍼지논리제어시스템이라고 부르며, 퍼지논리제어시스템은 크게 3가지의 구성 요소로 이루어진다. 퍼지화기, 지식베이스와 추론엔진, 그리고 비퍼지화기이다. 여기서 비퍼지화기는 퍼지논리제어시스템에서 추론한 최종 제어 입력인 퍼지 신호를 제어대상 플랜트가 이해할 수 있는 보통 신호 형태의 제어 입력으로 변환하는 기능을 담당한다. 현재 비퍼지화를 위한 알고리즘으로 무게중심법과 간략화된 무게 중심법이 널리 사용되고 있다. 본 논문에서는 퍼지논리제어기를 위한 기존의 주요 비퍼지화 방법을 분석하고, 이를 기반으로 새로운 비퍼지화 방법을 제안한다. 그리고 수치 예제를 통하여 제시한 비퍼지화 방법의 유용성을 확인한다.

Fuzzy Logic Based Controller with Dedicated Safety Function for Hybrid Renewable Energy System

For the dual reasons of energy security and environmental and climate preservation, there has been a global campaign for drastic reduction in the use of fossil fuels and a consequential aggressive pursuit for the development of clean energy systems. Hybrid renewable energy systems, ahead of single source renewable energy systems, promise to be an effective alternative to the use of fossil fuels. However, if hybrid renewable energy systems must effectively and reliably serve as an alternative to fossil fuel use, then improvements in the control and management of energy flow among the renewable energy supplies, energy storage components, and the load is of very vital significance. More intelligent and optimized, and easy-to-develop control techniques need to be introduced to replace already existing conventional techniques. And very importantly, extra measures have to be taken to ensure longer battery life and the overall safety of the system. This work is a design of a fuzzy logic-based control system for managing energy flow in a hybrid renewable energy system. A dedicated output was incorporated in the fuzzy controller for controlling the load connection status. The results showed that the fuzzy logic controller accurately emulated expert decisions in monitoring the battery state-of-charge and renewable energy supply capacities, and effectively determining and controlling the battery charging and discharging functions. The employment of fuzzy logic control in the system eliminated the need for complex and tedious mathematical modelling as required in conventional control methods. Thus the system was easier to develop.

On-site monitoring and subjective comfort assessment of a sun shadings and electric lighting controller based on novel High Dynamic Range vision sensors

Electric lighting is responsible of about one fifth of the electricity demand of buildings in Switzerland. Therein, integrated control of sun shadings and artificial lighting can mitigate the electricity demand while maintaining the user comfort and performance. However, the drawback of the existing smart building technologies is that they do not take visual comfort effectively into account, one of the essential aspects of indoor human comfort. An ‘on-the-fly’ measurement of a visual comfort index, Daylight Glare Probability (DGP), by a novel High Dynamic Range (HDR) vision sensor was introduced into the building control system optimizing the sun shadings position and electric lighting status. Two identical office rooms (reference and advance) of the LESO solar experimental building were occupied by 30 human subjects during 15 afternoons and were used to experimentally compare the performance and users acceptance of the fuzzy logic based control system against a best practice reference system. A paper-based and a computer-based visual tests, subjective self-reported visual comfort surveys and precise monitoring of the electric lighting consumptions were carried out.The results indicates that the electricity demand of the advanced system is 32% lower than the reference one. It also shows that, while the subjects’ visual performance remain comparable in the two office rooms, the advanced control system is successful in preventing discomfort glare sensations.