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Analyses of PO-Based fuzzy logic-Controlled MPPT and Incremental Conductance MPPT algorithms in PV Systems

ENERGIES 2025年第2期18卷 233-233页

作者： Cakmak, Fevzi Aydogmus, Zafer Tur, Mehmet Rida Mardin Artuklu Univ Midyat Vocat Sch TR-47500 Mardin Turkiye Firat Univ Fac Technol Elect Elect Engn TR-23000 Elazig Turkiye Batman Univ Fac Engn Elect & Elect Engn TR-72000 Batman Turkiye

This manuscript aims to increase the utilization of solar energy, which is both environmentally friendly and easily accessible, to satisfy the energy needs of developing countries. In order to achieve this goal, maximum power generation should be provided from photovoltaic panels. Several maximum power point tracking (MPPT) methods are utilized for maximum power generation in photovoltaic panel systems under different weather conditions. In this paper, a novel intelligent hybrid fuzzy logic-controlled maximum power point tracking algorithm founded on the perturb and observe (PO) algorithm is presented. The proposed fuzzy logic controller algorithm and the incremental conductivity maximum power point tracking algorithm were simulated in a MATLAB(2018b version)/Simulink environment and evaluated by comparing the results. Four Sharp ND-F4Q295 solar panels, two in series and two in parallel, were used for the simulation. In this study, the voltage ripple of the proposed hybrid method was measured at 1% compared to the classical incremental conductivity method, while it was 8.6% in the IncCon method. Similarly, the current ripple was 1.08% in the proposed hybrid FLC method, while the current ripple was 9.27% in the IncCon method. It is observed that the proposed smart method stabilizes the system voltage faster, at 25 ms, in the event of sudden weather changes.

关键词： boost converter fuzzy logic algorithm incremental conductivity algorithm maximum power point trackers photovoltaic systems

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Implementation of fuzzy logic Scheme for Assessment of Power Transformer Oil Deterioration Using Imprecise Information

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ENERGIES 2024年第21期17卷 5412-5412页

作者： Nishtar, Zuhaib Wang, Fangzong China Three Gorges Univ Coll Elect Engn & New Energy Yichang 443002 Peoples R China

This research aims to analyze the implementation of a fuzzy logic-based approach in improving the diagnosis of power transformer oil deterioration, which is critical for maintaining the efficient performance and operational life of transformers. Traditional diagnoses are based on strict measurements that do not account for the factors of variability and uncertainty of the actual data. In this article, we perform six different types of tests in this regard, and data have been collected during the period of 2021 to 2022 of 188 power transformer failures in the New KotLakhpat Lahore unit, whose voltage range is 132/66 kv and rating capacity is 40/50 MVA. In this case, a fuzzy logic-based scheme is developed based upon the membership function, a rule-based and defuzzification method that works with imprecision and the implementation of uncertainty in assessing the condition of transformer oils. Moisture, acidity, and a dissolved gas analysis indicator, along with other indication approaches such as interfacial tension, viscosity, and tangent delta measurement, are used to analyze the deterioration process in transformer oils. In the visual representation, oil samples with the following properties were first fuzzified: 19.9 mm2/s of viscosity, 0.453 mgKOH/g of acidity, 695 ppm of DGA, 20.8 mg/kg of moisture, 19.98 of IFT, and 4.35 x 100.14 of tangent delta. The output that was generated by software using the values entered into the parameters (HI and Age) after defuzzification is 45. fuzzy logic serves as a concrete framework for transforming the diagnostics system and deterring the threats to the entire transformer's health and reliability in the future. By using this technique, various faults were hypothetically and practically analyzed in a transformer to implement early detection technologies with the possibility to reduce maintenance costs and extend operational life up to 45 years. Various case studies indicate the effectiveness of fuzzy logic in comparison to trad

关键词： aging mechanism fuzzy logic algorithm oil-immersed power transformer condition monitoring transformer failure operational life estimation

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A comparative study of the recursive least squares and fuzzy logic estimation methods for the measurement of road adhesion coefficient

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AUSTRALIAN JOURNAL OF MECHANICAL ENGINEERING 2023年第4期21卷 1230-1246页

作者： Qi, Gengxin Fan, Xiaobin Li, Hao Henan Polytech Univ Sch Mech & Power Engn Jiaozuo Henan Peoples R China

Vehicle active safety system is the hotspot of current research and development, and the road adhesion coefficient is one of the essential parameters in the development of automobile active safety system, which plays a pivotal role in automobile safety. To improve the real-time performance and accuracy of the road adhesion coefficient, this paper proposes different control methods and compares and analyzes them. To accurately estimate the road adhesion coefficient in real-time, an eight-degree-of-freedom vehicle model was adopted in this paper. According to the tire torque and wheel speed, the adhesion coefficient was estimated based on the second-order nonlinear extended state observer. The experimental data, such as slip rate, using the improved tire model, is based on the recursive least squares method with forgetting factor and fuzzy logic algorithm real-time of tire-road friction coefficient estimation. The results show that the observer can effectively observe utilisation adhesion coefficient, and both control algorithms can estimate the road adhesion coefficient in real-time, effectively and quickly. On different roads, the use of the recursive least squares algorithm resulted in higher estimation accuracy, better robustness, and better control effect than using a fuzzy logic algorithm.

关键词： Road adhesion coefficient Vehicle active safety system Extended state observer Utilisation adhesion coefficient Recursive least squares method fuzzy logic algorithm

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Intelligent Ventilation Management System of Laboratory Based on fuzzy logic 9

Intelligent Ventilation Management System of Laboratory Base...

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9th International Conference on Control, Automation and Robotics (ICCAR)

作者： Zhou, Wei Zeng, Ziqi Bao, Shijie Xiamen Univ Technol Elect & Automat Engn Coll Xiamen Peoples R China

ISBN: (纸本)9798350322514

During the period of regular epidemic prevention, reasonable ventilation management can reduce the probability of virus infection. In the paper, the STM32F429 microcontroller is used as the control center of the whole system, and the AP6181 chip is used to obtain the local weather conditions of the network API, and a screw-based window switch actuator is designed. To comprehensively consider the ventilation requirements and the human comfort which influenced by temperature and humidity, the fuzzy logic algorithm is used to make control strategies, and the system can also be remotely controlled through new designed mobile APP, which realizes the intelligent management of the laboratory ventilation system. In this paper, the simulated windows are tested. The results show that the communication success rate of the system is 96%, and the movement error of the actuator is 5mm, which can meet the requirements of laboratory ventilation system.

关键词： regular epidemic prevention ventilation management fuzzy logic algorithm human comfort

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A fuzzy logic Approach on the Evaluation of Driving Styles and Investigation of Drivability Calibration Effects

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GAZI UNIVERSITY JOURNAL OF SCIENCE 2022年第2期35卷 668-680页

作者： Aksit, Samet Yavuz, Akif Sen, Osman Taha AVL Turkey Res & Engn TR-34885 Istanbul Turkey Istanbul Tech Univ Fac Mech Engn TR-34437 Istanbul Turkey

Increased customer expectations lead the automobile manufacturers to develop innovative solutions, such as mode selection functions that provide different performance and comfort settings for the drivers. Almost all brands have different types of driving modes installed on their vehicles, such as sport mode, economy mode, off-road mode, etc. In the current technology, the mode selection is manually done by the driver. Thus, no effort is taken to match the driver style with available driving modes. However, driving mode selection should be done through an intelligent system such as vehicle control unit, in order to optimize customer expectations related to vehicle performance, driving comfort, and fuel consumption. This can be achieved by the analysis of all drivability maneuvers during any driving cycle. Based on the results of these analyses, drivability calibration settings of the vehicle can be adjusted depending on driver behaviors. In addition, fuel consumption can be improved using suitable calibration for each driver type. In this study, an experimental investigation is carried out in which vehicle data is collected for eleven different drivers at three different drivability calibrations. Furthermore, fuzzy logic algorithms are utilized in order to distinguish the driver characteristics. First, data from nine drivers are used in order to train the fuzzy logic approach. Then, the trained fuzzy logic scheme is used to assess the characteristics of two other drivers, who were left out in the training data set. Hence, it is aimed to obtain an intelligent prediction procedure that can estimate the characteristics of a driver based on their driving styles.

关键词： Drivability calibration fuzzy logic algorithm Driver classification

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An improved analogy-rule based software effort estimation using HTRR-RNN in software project management

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EXPERT SYSTEMS WITH APPLICATIONS 2024年 251卷

作者： Kumar, K. Harish Srinivas, K. Koneru Lakshmaiah Educ Fdn Deemed be Univ Dept Comp Sci & Engn Hyderabad 500075 India Mahatma Gandhi Univ Dept Comp Sci & Informat Nalgonda 508254 Telangana India

To complete a software project, the most realistic effort required is predicted by the process called Software Effort Estimation (SEE). Effort Estimation (EE) in software development is considered a complicated task owing to the variability of variables. Thus, numerous Software Development EE (SDEE) models have been developed;nevertheless, these models ' accuracy rates are not good enough, and the variations among software functionalities were not focused for SEE. Therefore, by considering it as the research gap in Software Project Management (SPM), an enhanced analogy-rule-centric SEE utilizing Hyperbolic Tangent Recurrent Radial - Recurrent Neural Networks (HTRR-RNN) algorithm is proposed in this work. Initially, regarding the project size, the projects are partitioned. Next, the highly vital features are extracted as of the separated projects. By employing Levy FlightRock Hyraxes Swarm (LH-RHS) optimization, the selective quantity of features is chosen from the extracted features. By deploying the Mamdani Method - fuzzy (MM-fuzzy) algorithm, the rules are created regarding the selected features. Lastly, the number of efforts needed for the software development process is determined by the classification algorithm regarding the rules being created. COCOMO81, MAXWELL, and China are the openly accessible datasets utilized in this methodology. Then, the proposed method ' s results are contrasted with the prevailing algorithms. As per the experimental results, the proposed methodology performs SEE with a better accuracy rate;thus, it surpassed the other existing methodologies.

关键词： Software Effort Estimation Recurrent neural network fuzzy logic algorithm Mamdani method Rock hyraxes swarm optimization

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Vibration control of an eleven-story structure with MR and TMD dampers using MAC predictive control, considering nonlinear behavior and time delay in the control system

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STRUCTURES 2024年 60卷

作者： Bathaei, Akbar Zahrai, Seyed Mehdi Univ Tehran Sch Civil Engn Tehran Iran Univ Tehran Coll Engn Sch Civil Engn POB 11155-4563 Tehran Iran

In the last two decades, model predictive control has made significant progress in research and industrial process control. This achievement is through the high ability of model predictive control to solve industrial process control problems in the time domain. It is applicable in many control systems, such as delayed systems, univariate and multivariable systems, non-minimum phase systems, and unstable systems. This strategy is essentially for controlling delayed systems. It is possible to create a time delay in transmitting structure movement data in the systems that use sensors and receivers of sensor-recorded data, which is a factor to reduce the efficiency of the control system and even the instability of the structure. In this study, to investigate and compensate the effect of time delay in the hybrid vibration control system, an 11-story structure with a tuned mass damper and an MR damper was used by model algorithmic control (MAC) and nonlinear behavior of the structure in the control process. The linear and nonlinear structural models are created in OpenSEES, the control system in MATLAB;and the TCP/IP connection method was used to connect two programs. The fuzzy decision system is based on accelerating and decelerating movement. The structure has been subjected to seven earthquakes with maximum accelerations of 0.1 g to 1.0 g with an incremental step of 0.1 g. According to the results of incremental dynamic analysis, the average percentage of the fuzzy control system performance reduction, considering the time delay, is 15.28% and 38.57% for the maximum displacement and base shear in the linear structure, and 8.04% and 5.97% for the nonlinear structure, respectively. The assumed time delays have been effectively overcome using the model algorithmic control system (MAC), determining the prediction horizon of the structural behavior, and optimizing the control force in the control horizon. The performance of the MAC control system has been better than the fu

关键词： Hybrid control Model algorithmic control Nonlinear structure fuzzy logic algorithm Predictive control

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Arduino-based Line Tracking Smart Robot Car Equipped with YOLOv3 and fuzzy logic Controlled Ultraviolet Sterilizer 8

Arduino-based Line Tracking Smart Robot Car Equipped with YO...

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8th International Conference on Automation, Robotics and Applications (ICARA)

作者： Garcia, Ramon G. Manuel, Levin D. Romero, Cesar Quartz L., Jr. Mapua Univ Sch EECE Manila Philippines

ISBN: (纸本)9781665483834

With the increasing number of cases of pathogenic diseases caused by airborne transmission of microorganisms, such as Staphylococcus aureus, interest when it comes to the disinfection of surfaces is increasing. One of the many devices that have been utilized for surface disinfection is the use of Ultraviolet Light radiation, specifically UVC radiation, as a sterilizer or disinfectant. In this study, a UVC disinfecting machine based on Arduino Nano was developed with a mobile application to control and enable the device's functionalities. The UVC disinfecting machine can be manually controlled via the generated mobile application and automatically navigated using the Line Tracking algorithm. To ensure the safety of the people utilizing the device, the UVC disinfecting machine will be encircled with several motion sensors and a Wi-Fi camera module. The sensors and camera automatically disable its UVC lamp once it detects human presence by applying the algorithms of fuzzy logic and YOLOv3. This study provides a versatile, safe, and harmless UVC disinfecting machine while effectively disinfecting objects and surfaces.

关键词： staphylococcus Aureus ultraviolet light UVC radiation disinfecting machine Arduino Nano mobile application line tracking algorithm motion sensors Wi-Fi Camera Module fuzzy logic algorithm YOLOv3 algorithm

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Hierarchical energy-saving routing algorithm using fuzzy logic in wireless sensor networks

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EURASIP JOURNAL ON INFORMATION SECURITY 2023年第1期2023卷 9-9页

作者： Wang, Dan Wu, Qing Hu, Ming State Grid Informat & Telecommun Grp Co Ltd Beijing 102211 Peoples R China

Currently, sensor energy assembly in wireless sensor networks is limited, and clustering methods are not effective to improve sensor energy consumption rate. Thus, a hierarchical energy-saving routing algorithm based on fuzzy logic was constructed by considering three aspects: residual energy value, centrality, and distance value between nodes and base stations. The remaining sensor nodes selected by fuzzy logic algorithm have a longer time to live and greater residual energy than those selected by low-power adaptive clustering hierarchical protocol algorithm, fuzzy unequal clustering algorithm, and fuzzy logic cluster head election algorithm. For network life cycle, the number of rounds in which the first dead node appears, in descending order, is studied: energy-saving routing algorithm (400 rounds) > new geographic cellular structure algorithm (300 rounds) > virtual grid based dynamic routes adjustment algorithm (100 rounds). Under the same experimental round, energy-saving routing algorithm's remaining energy curve always reaches its maximum. The energy-saving routing algorithm by fuzzy logic constructed by this research institute can significantly improve network energy utilization, which has certain reference value.

关键词： Wireless sensor network fuzzy logic algorithm Virtual network technology Remaining nodes number Network energy consumption

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Object-oriented and fuzzy logic classification methods for mapping reforested areas with exotic species in Rio Canoas State Park-Santa Catarina, Brazil

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ENVIRONMENT DEVELOPMENT AND SUSTAINABILITY 2021年第5期23卷 7791-7807页

作者： Lopes, Manoela Sacchis Saldanha, Dejanira Luderitz Veettil, Bijeesh Kozhikkodan Univ Fed Santa Maria Santa Maria RS Brazil Univ Fed Rio Grande do Sul Ctr Estadual Pesquisas Sensoriamento Remoto & Met Programa Posgrad Sensoriamento Remoto Porto Alegre RS Brazil Ton Duc Thang Univ Dept Management Sci & Technol Dev Ho Chi Minh City Vietnam Ton Duc Thang Univ Fac Environm & Labour Safety Ho Chi Minh City Vietnam

Reforestation with exotic plans may alter the natural flora due to uncontrolled expansion of the inserted species. This study evaluated the potential of the object-oriented classification method using fuzzy logic algorithm for the differentiation of forest areas in intermediate/advanced stage and areas reforested with exotic species around the Rio Canoas State Park in Santa Catarina State of Brazil, using high spatial resolution SPOT6 imagery. The study region has regional importance for the preservation of mixed ombrophilous forest remnants and is belonging to the Biosphere Reserve of the Atlantic Rainforest, and hence, it is important to monitor the advance of exotic species in the region. The methodology consisted of the creation of the hierarchical network and process tree with numerous descriptor tests in Trimble Ecognition software, principal component analysis, multi-resolution segmentation algorithm and fuzzy logic functions. It was concluded that the use of principal components associated with the red band by a simple ratio of digital levels is extremely effective for identifying the areas reforested with exotic species. fuzzy logic pertinence functions are the key in discriminating natural forest areas and areas reforested with exotic species in the study region accurately. The object-oriented classification was validated by points collected in the field and presented an overall accuracy level of 0.83 and Kappa index of 0.78, concluding that it is an efficient methodology in the delimitation of exotic species reforestation areas around Rio Canoas State Park.

关键词： Vegetation mapping Conservation areas Exotic species invasion Atlantic rain forest fuzzy logic algorithm

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