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Sample records for fuzzy logic applied

  1. Fuzzy forecasting based on fuzzy-trend logical relationship groups.

    Science.gov (United States)

    Chen, Shyi-Ming; Wang, Nai-Yi

    2010-10-01

    In this paper, we present a new method to predict the Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX) based on fuzzy-trend logical relationship groups (FTLRGs). The proposed method divides fuzzy logical relationships into FTLRGs based on the trend of adjacent fuzzy sets appearing in the antecedents of fuzzy logical relationships. First, we apply an automatic clustering algorithm to cluster the historical data into intervals of different lengths. Then, we define fuzzy sets based on these intervals of different lengths. Then, the historical data are fuzzified into fuzzy sets to derive fuzzy logical relationships. Then, we divide the fuzzy logical relationships into FTLRGs for forecasting the TAIEX. Moreover, we also apply the proposed method to forecast the enrollments and the inventory demand, respectively. The experimental results show that the proposed method gets higher average forecasting accuracy rates than the existing methods.

  2. Fuzzy forecasting based on two-factors second-order fuzzy-trend logical relationship groups and the probabilities of trends of fuzzy logical relationships.

    Science.gov (United States)

    Chen, Shyi-Ming; Chen, Shen-Wen

    2015-03-01

    In this paper, we present a new method for fuzzy forecasting based on two-factors second-order fuzzy-trend logical relationship groups and the probabilities of trends of fuzzy-trend logical relationships. Firstly, the proposed method fuzzifies the historical training data of the main factor and the secondary factor into fuzzy sets, respectively, to form two-factors second-order fuzzy logical relationships. Then, it groups the obtained two-factors second-order fuzzy logical relationships into two-factors second-order fuzzy-trend logical relationship groups. Then, it calculates the probability of the "down-trend," the probability of the "equal-trend" and the probability of the "up-trend" of the two-factors second-order fuzzy-trend logical relationships in each two-factors second-order fuzzy-trend logical relationship group, respectively. Finally, it performs the forecasting based on the probabilities of the down-trend, the equal-trend, and the up-trend of the two-factors second-order fuzzy-trend logical relationships in each two-factors second-order fuzzy-trend logical relationship group. We also apply the proposed method to forecast the Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX) and the NTD/USD exchange rates. The experimental results show that the proposed method outperforms the existing methods.

  3. Combining fuzzy mathematics with fuzzy logic to solve business management problems

    Science.gov (United States)

    Vrba, Joseph A.

    1993-12-01

    Fuzzy logic technology has been applied to control problems with great success. Because of this, many observers fell that fuzzy logic is applicable only in the control arena. However, business management problems almost never deal with crisp values. Fuzzy systems technology--a combination of fuzzy logic, fuzzy mathematics and a graphical user interface--is a natural fit for developing software to assist in typical business activities such as planning, modeling and estimating. This presentation discusses how fuzzy logic systems can be extended through the application of fuzzy mathematics and the use of a graphical user interface to make the information contained in fuzzy numbers accessible to business managers. As demonstrated through examples from actual deployed systems, this fuzzy systems technology has been employed successfully to provide solutions to the complex real-world problems found in the business environment.

  4. Fuzzy Logic vs. Neutrosophic Logic: Operations Logic

    Directory of Open Access Journals (Sweden)

    Salah Bouzina

    2016-12-01

    Full Text Available The goal of this research is first to show how different, thorough, widespread and effective are the operations logic of the neutrosophic logic compared to the fuzzy logic’s operations logical. The second aim is to observe how a fully new logic, the neutrosophic logic, is established starting by changing the previous logical perspective fuzzy logic, and by changing that, we mean changing changing the truth values from the truth and falsity degrees membership in fuzzy logic, to the truth, falsity and indeterminacy degrees membership in neutrosophic logic; and thirdly, to observe that there is no limit to the logical discoveries - we only change the principle, then the system changes completely.

  5. Fuzzy logic applied to prospecting for areas for installation of wood panel industries.

    Science.gov (United States)

    Dos Santos, Alexandre Rosa; Paterlini, Ewerthon Mattos; Fiedler, Nilton Cesar; Ribeiro, Carlos Antonio Alvares Soares; Lorenzon, Alexandre Simões; Domingues, Getulio Fonseca; Marcatti, Gustavo Eduardo; de Castro, Nero Lemos Martins; Teixeira, Thaisa Ribeiro; Dos Santos, Gleissy Mary Amaral Dino Alves; Juvanhol, Ronie Silva; Branco, Elvis Ricardo Figueira; Mota, Pedro Henrique Santos; da Silva, Lilianne Gomes; Pirovani, Daiani Bernardo; de Jesus, Waldir Cintra; Santos, Ana Carolina de Albuquerque; Leite, Helio Garcia; Iwakiri, Setsuo

    2017-05-15

    Prospecting for suitable areas for forestry operations, where the objective is a reduction in production and transportation costs, as well as the maximization of profits and available resources, constitutes an optimization problem. However, fuzzy logic is an alternative method for solving this problem. In the context of prospecting for suitable areas for the installation of wood panel industries, we propose applying fuzzy logic analysis for simulating the planting of different species and eucalyptus hybrids in Espírito Santo State, Brazil. The necessary methodological steps for this study are as follows: a) agriclimatological zoning of different species and eucalyptus hybrids; b) the selection of the vector variables; c) the application of the Euclidean distance to the vector variables; d) the application of fuzzy logic to matrix variables of the Euclidean distance; and e) the application of overlap fuzzy logic to locate areas for installation of wood panel industries. Among all the species and hybrids, Corymbia citriodora showed the highest percentage values for the combined very good and good classes, with 8.60%, followed by Eucalyptus grandis with 8.52%, Eucalyptus urophylla with 8.35% and Urograndis with 8.34%. The fuzzy logic analysis afforded flexibility in prospecting for suitable areas for the installation of wood panel industries in the Espírito Santo State can bring great economic and social benefits to the local population with the generation of jobs, income, tax revenues and GDP increase for the State and municipalities involved. The proposed methodology can be adapted to other areas and agricultural crops. Copyright © 2017 Elsevier Ltd. All rights reserved.

  6. Fuzzy logic applications in engineering science

    CERN Document Server

    Harris, J

    2006-01-01

    Fuzzy logic is a relatively new concept in science applications. Hitherto, fuzzy logic has been a conceptual process applied in the field of risk management. Its potential applicability is much wider than that, however, and its particular suitability for expanding our understanding of processes and information in science and engineering in our post-modern world is only just beginning to be appreciated. Written as a companion text to the author's earlier volume "An Introduction to Fuzzy Logic Applications", the book is aimed at professional engineers and students and those with an interest in exploring the potential of fuzzy logic as an information processing kit with a wide variety of practical applications in the field of engineering science and develops themes and topics introduced in the author's earlier text.

  7. System for corrosion monitoring in pipeline applying fuzzy logic mathematics

    Science.gov (United States)

    Kuzyakov, O. N.; Kolosova, A. L.; Andreeva, M. A.

    2018-05-01

    A list of factors influencing corrosion rate on the external side of underground pipeline is determined. Principles of constructing a corrosion monitoring system are described; the system performance algorithm and program are elaborated. A comparative analysis of methods for calculating corrosion rate is undertaken. Fuzzy logic mathematics is applied to reduce calculations while considering a wider range of corrosion factors.

  8. Fuzzy logic

    CERN Document Server

    Smets, P

    1995-01-01

    We start by describing the nature of imperfect data, and giving an overview of the various models that have been proposed. Fuzzy sets theory is shown to be an extension of classical set theory, and as such has a proeminent role or modelling imperfect data. The mathematic of fuzzy sets theory is detailled, in particular the role of the triangular norms. The use of fuzzy sets theory in fuzzy logic and possibility theory,the nature of the generalized modus ponens and of the implication operator for approximate reasoning are analysed. The use of fuzzy logic is detailled for application oriented towards process control and database problems.

  9. Metamathematics of fuzzy logic

    CERN Document Server

    Hájek, Petr

    1998-01-01

    This book presents a systematic treatment of deductive aspects and structures of fuzzy logic understood as many valued logic sui generis. Some important systems of real-valued propositional and predicate calculus are defined and investigated. The aim is to show that fuzzy logic as a logic of imprecise (vague) propositions does have well-developed formal foundations and that most things usually named `fuzzy inference' can be naturally understood as logical deduction.

  10. Logical Characterisation of Ontology Construction using Fuzzy Description Logics

    DEFF Research Database (Denmark)

    Badie, Farshad; Götzsche, Hans

    had the extension of ontologies with Fuzzy Logic capabilities which plan to make proper backgrounds for ontology driven reasoning and argumentation on vague and imprecise domains. This presentation conceptualises learning from fuzzy classes using the Inductive Logic Programming framework. Then......, employs Description Logics in characterising and analysing fuzzy statements. And finally, provides a conceptual framework describing fuzzy concept learning in ontologies using the Inductive Logic Programming....

  11. Introduction to fuzzy logic using Matlab

    CERN Document Server

    Sivanandam, SN; Deepa, S N

    2006-01-01

    Fuzzy Logic, at present is a hot topic, among academicians as well various programmers. This book is provided to give a broad, in-depth overview of the field of Fuzzy Logic. The basic principles of Fuzzy Logic are discussed in detail with various solved examples. The different approaches and solutions to the problems given in the book are well balanced and pertinent to the Fuzzy Logic research projects. The applications of Fuzzy Logic are also dealt to make the readers understand the concept of Fuzzy Logic. The solutions to the problems are programmed using MATLAB 6.0 and the simulated results are given. The MATLAB Fuzzy Logic toolbox is provided for easy reference.

  12. Fuzzy logic in management

    CERN Document Server

    Carlsson, Christer; Fullér, Robert

    2004-01-01

    Fuzzy Logic in Management demonstrates that difficult problems and changes in the management environment can be more easily handled by bringing fuzzy logic into the practice of management. This explicit theme is developed through the book as follows: Chapter 1, "Management and Intelligent Support Technologies", is a short survey of management leadership and what can be gained from support technologies. Chapter 2, "Fuzzy Sets and Fuzzy Logic", provides a short introduction to fuzzy sets, fuzzy relations, the extension principle, fuzzy implications and linguistic variables. Chapter 3, "Group Decision Support Systems", deals with group decision making, and discusses methods for supporting the consensus reaching processes. Chapter 4, "Fuzzy Real Options for Strategic Planning", summarizes research where the fuzzy real options theory was implemented as a series of models. These models were thoroughly tested on a number of real life investments, and validated in 2001. Chapter 5, "Soft Computing Methods for Reducing...

  13. A Brief History of Fuzzy Logic

    Directory of Open Access Journals (Sweden)

    Angel Garrido

    2012-04-01

    Full Text Available

    The problems of uncertainty, imprecision and vagueness have been discussed for many years. These problems have been major topics in philosophical circles with much debate, in particular, about the nature of vagueness and the ability of traditional Boolean logic to cope with concepts and perceptions that are imprecise or vague. The Fuzzy Logic (which is usually translated into Castilian by “Lógica Borrosa”, or “Lógica Difusa”, but also by “Lógica Heurística” can be considered a bypass-valued logics (Multi-valued Logic, MVL, its acronym in English. It is founded on, and is closely related to-Fuzzy Sets Theory, and successfully applied on Fuzzy Systems. You might think that fuzzy logic is quite recent and what has worked for a short time, but its origins date back at least to the Greek philosophers and especially Plato (428-347 B.C.. It even seems plausible
    to trace their origins in China and India. Because it seems that they were the first to consider that all things need not be of a certain type or quit, but there are a stopover between. That is, be the pioneers in considering that there may be varying degrees of truth and falsehood. In case of colors, for example, between white and black there is a whole infinite scale: the shades of gray. Some recent theorems show that in principle fuzzy logic can be used to model any continuous system, be it based
    in AI, or physics, or biology, or economics, etc. Investigators in many fields may find that fuzzy, commonsense models are more useful, and many more accurate than are standard mathematical ones. We analyze here the history and development of this problem: Fuzziness, or “Borrosidad” (in Castilian, essential to work with Uncertainty.

  14. Efficiency of particle swarm optimization applied on fuzzy logic DC motor speed control

    Directory of Open Access Journals (Sweden)

    Allaoua Boumediene

    2008-01-01

    Full Text Available This paper presents the application of Fuzzy Logic for DC motor speed control using Particle Swarm Optimization (PSO. Firstly, the controller designed according to Fuzzy Logic rules is such that the systems are fundamentally robust. Secondly, the Fuzzy Logic controller (FLC used earlier was optimized with PSO so as to obtain optimal adjustment of the membership functions only. Finally, the FLC is completely optimized by Swarm Intelligence Algorithms. Digital simulation results demonstrate that in comparison with the FLC the designed FLC-PSO speed controller obtains better dynamic behavior and superior performance of the DC motor, as well as perfect speed tracking with no overshoot.

  15. Fuzzy logic guided inverse treatment planning

    International Nuclear Information System (INIS)

    Yan Hui; Yin Fangfang; Guan Huaiqun; Kim, Jae Ho

    2003-01-01

    A fuzzy logic technique was applied to optimize the weighting factors in the objective function of an inverse treatment planning system for intensity-modulated radiation therapy (IMRT). Based on this technique, the optimization of weighting factors is guided by the fuzzy rules while the intensity spectrum is optimized by a fast-monotonic-descent method. The resultant fuzzy logic guided inverse planning system is capable of finding the optimal combination of weighting factors for different anatomical structures involved in treatment planning. This system was tested using one simulated (but clinically relevant) case and one clinical case. The results indicate that the optimal balance between the target dose and the critical organ dose is achieved by a refined combination of weighting factors. With the help of fuzzy inference, the efficiency and effectiveness of inverse planning for IMRT are substantially improved

  16. Fuzzy forecasting based on two-factors second-order fuzzy-trend logical relationship groups and particle swarm optimization techniques.

    Science.gov (United States)

    Chen, Shyi-Ming; Manalu, Gandhi Maruli Tua; Pan, Jeng-Shyang; Liu, Hsiang-Chuan

    2013-06-01

    In this paper, we present a new method for fuzzy forecasting based on two-factors second-order fuzzy-trend logical relationship groups and particle swarm optimization (PSO) techniques. First, we fuzzify the historical training data of the main factor and the secondary factor, respectively, to form two-factors second-order fuzzy logical relationships. Then, we group the two-factors second-order fuzzy logical relationships into two-factors second-order fuzzy-trend logical relationship groups. Then, we obtain the optimal weighting vector for each fuzzy-trend logical relationship group by using PSO techniques to perform the forecasting. We also apply the proposed method to forecast the Taiwan Stock Exchange Capitalization Weighted Stock Index and the NTD/USD exchange rates. The experimental results show that the proposed method gets better forecasting performance than the existing methods.

  17. French-speaking meeting on fuzzy logic and its applications

    International Nuclear Information System (INIS)

    1997-01-01

    The 1997 edition of LFA'97 meeting for fuzzy logic has been organized by the Pattern Recognition and Computer Vision Laboratory of the National Institute of Applied Sciences. The objective of the meeting was to provide a forum for researchers and users of fuzzy logic and possibility theory to present and discuss theoretical researches and concrete applications. The domains in concern are: the control decision theory, the pattern recognition and image analysis, the artificial intelligence and the information systems. From the 41 papers of this book, two were selected for ETDE and deal with fuzzy regulation systems for heating systems and with fuzzy controllers for gas refining plants, and one was selected for INIS and deal with real-time surveillance and fuzzy logic control systems for nuclear power plants. (J.S.)

  18. Fifty years of fuzzy logic and its applications

    CERN Document Server

    Rishe, Naphtali; Kandel, Abraham

    2015-01-01

    This book presents a comprehensive report on the evolution of Fuzzy Logic since its formulation in Lotfi Zadeh’s seminal paper on “fuzzy sets,” published in 1965. In addition, it features a stimulating sampling from the broad field of research and development inspired by Zadeh’s paper. The chapters, written by pioneers and prominent scholars in the field, show how fuzzy sets have been successfully applied to artificial intelligence, control theory, inference, and reasoning. The book also reports on theoretical issues; features recent applications of Fuzzy Logic in the fields of neural networks, clustering, data mining, and software testing; and highlights an important paradigm shift caused by Fuzzy Logic in the area of uncertainty management. Conceived by the editors as an academic celebration of the fifty years’ anniversary of the 1965 paper, this work is a must-have for students and researchers willing to get an inspiring picture of the potentialities, limitations, achievements and accomplishments...

  19. Application of fuzzy logic to social choice theory

    CERN Document Server

    Mordeson, John N; Clark, Terry D

    2015-01-01

    Fuzzy social choice theory is useful for modeling the uncertainty and imprecision prevalent in social life yet it has been scarcely applied and studied in the social sciences. Filling this gap, Application of Fuzzy Logic to Social Choice Theory provides a comprehensive study of fuzzy social choice theory.The book explains the concept of a fuzzy maximal subset of a set of alternatives, fuzzy choice functions, the factorization of a fuzzy preference relation into the ""union"" (conorm) of a strict fuzzy relation and an indifference operator, fuzzy non-Arrowian results, fuzzy versions of Arrow's

  20. Fuzzy Logic and Arithmetical Hierarchy III

    Czech Academy of Sciences Publication Activity Database

    Hájek, Petr

    2001-01-01

    Roč. 68, č. 1 (2001), s. 129-142 ISSN 0039-3215 R&D Projects: GA AV ČR IAA1030004 Institutional research plan: AV0Z1030915 Keywords : fuzzy logic * basic fuzzy logic * Lukasiewicz logic * Godel logic * product logic * arithmetical hierarchy Subject RIV: BA - General Mathematics

  1. Fuzzy Logic Applied to an Oven Temperature Control System

    Directory of Open Access Journals (Sweden)

    Nagabhushana KATTE

    2011-10-01

    Full Text Available The paper describes the methodology of design and development of fuzzy logic based oven temperature control system. As simple fuzzy logic controller (FLC structure with an efficient realization and a small rule base that can be easily implemented in existing underwater control systems is proposed. The FLC has been designed using bell-shaped membership function for fuzzification, 49 control rules in its rule base and centre of gravity technique for defuzzification. Analog interface card with 16-bits resolution is designed to achieve higher precision in temperature measurement and control. The experimental results of PID and FLC implemented system are drawn for a step input and presented in a comparative fashion. FLC exhibits fast response and it has got sharp rise time and smooth control over conventional PID controller. The paper scrupulously discusses the hardware and software (developed using ‘C’ language features of the system.

  2. Towards the future of fuzzy logic

    CERN Document Server

    Trillas, Enric; Kacprzyk, Janusz

    2015-01-01

    This book provides readers with a snapshot of the state-of-the art in fuzzy logic. Throughout the chapters, key theories developed in the last fifty years as well as important applications to practical problems are presented and discussed from different perspectives, as the authors hail from different disciplines and therefore use fuzzy logic for different purposes.  The book aims at showing how fuzzy logic has evolved since the first theory formulation by Lotfi A. Zadeh in his seminal paper on Fuzzy Sets in 1965. Fuzzy theories and implementation grew at an impressive speed and achieved significant results, especially on the applicative side. The study of fuzzy logic and its practice spread all over the world, from Europe to Asia, America and Oceania. The editors believe that, thanks to the drive of young researchers, fuzzy logic will be able to face the challenging goals posed by computing with words. New frontiers of knowledge are waiting to be explored. In order to motivate young people to engage in the ...

  3. Determination Of Adaptive Control Parameter Using Fuzzy Logic Controller

    Directory of Open Access Journals (Sweden)

    Omur Can Ozguney

    2017-08-01

    Full Text Available The robot industry has developed along with the increasing the use of robots in industry. This has led to increase the studies on robots. The most important part of these studies is that the robots must be work with minimum tracking trajectory error. But it is not easy for robots to track the desired trajectory because of the external disturbances and parametric uncertainty. Therefore adaptive and robust controllers are used to decrease tracking error. The aim of this study is to increase the tracking performance of the robot and minimize the trajectory tracking error. For this purpose adaptive control law for robot manipulator is identified and fuzzy logic controller is applied to find the accurate values for adaptive control parameter. Based on the Lyapunov theory stability of the uncertain system is guaranteed. In this study robot parameters are assumed to be unknown. This controller is applied to a robot model and the results of simulations are given. Controller with fuzzy logic and without fuzzy logic are compared with each other. Simulation results show that the fuzzy logic controller has improved the results.

  4. Development of Fuzzy Logic Controller for Quanser Bench-Top Helicopter

    Science.gov (United States)

    Jafri, M. H.; Mansor, H.; Gunawan, T. S.

    2017-11-01

    Bench-top helicopter is a laboratory scale helicopter that usually used as a testing bench of the real helicopter behavior. This helicopter is a 3 Degree of Freedom (DOF) helicopter which works by three different axes wshich are elevation, pitch and travel. Thus, fuzzy logic controller has been proposed to be implemented into Quanser bench-top helicopter because of its ability to work with non-linear system. The objective for this project is to design and apply fuzzy logic controller for Quanser bench-top helicopter. Other than that, fuzzy logic controller performance system has been simulated to analyze and verify its behavior over existing PID controller by using Matlab & Simulink software. In this research, fuzzy logic controller has been designed to control the elevation angle. After simulation has been performed, it can be seen that simulation result shows that fuzzy logic elevation control is working for 4°, 5° and 6°. These three angles produce zero steady state error and has a fast response. Other than that, performance comparisons have been performed between fuzzy logic controller and PID controller. Fuzzy logic elevation control has a better performance compared to PID controller where lower percentage overshoot and faster settling time have been achieved in 4°, 5° and 6° step response test. Both controller are have zero steady state error but fuzzy logic controller is managed to produce a better performance in term of settling time and percentage overshoot which make the proposed controller is reliable compared to the existing PID controller.

  5. Intelligent control-I: review of fuzzy logic and fuzzy set theory

    International Nuclear Information System (INIS)

    Nagrial, M.H.

    2004-01-01

    In the past decade or so, fuzzy systems have supplanted conventional technologies in many engineering systems, in particular in control systems and pattern recognition. Fuzzy logic has found applications in a variety of consumer products e.g. washing machines, camcorders, digital cameras, air conditioners, subway trains, cement kilns and many others. The fuzzy technology is also being applied in information technology, where it provides decision-support and expert systems with powerful reasoning capabilities. Fuzzy sets, introduced by Zadeh in 1965 as a mathematical way to represent vagueness in linguistics, can be considered a generalisation of classical set theory. Fuzziness is often confused with probability. This lecture will introduce the principal concepts and mathematical notions of fuzzy set theory. (author)

  6. Fuzzy logic: A "simple" solution for complexities in neurosciences?

    Science.gov (United States)

    Godil, Saniya Siraj; Shamim, Muhammad Shahzad; Enam, Syed Ather; Qidwai, Uvais

    2011-02-26

    Fuzzy logic is a multi-valued logic which is similar to human thinking and interpretation. It has the potential of combining human heuristics into computer-assisted decision making, which is applicable to individual patients as it takes into account all the factors and complexities of individuals. Fuzzy logic has been applied in all disciplines of medicine in some form and recently its applicability in neurosciences has also gained momentum. This review focuses on the use of this concept in various branches of neurosciences including basic neuroscience, neurology, neurosurgery, psychiatry and psychology. The applicability of fuzzy logic is not limited to research related to neuroanatomy, imaging nerve fibers and understanding neurophysiology, but it is also a sensitive and specific tool for interpretation of EEGs, EMGs and MRIs and an effective controller device in intensive care units. It has been used for risk stratification of stroke, diagnosis of different psychiatric illnesses and even planning neurosurgical procedures. In the future, fuzzy logic has the potential of becoming the basis of all clinical decision making and our understanding of neurosciences.

  7. Fuzzy Versions of Epistemic and Deontic Logic

    Science.gov (United States)

    Gounder, Ramasamy S.; Esterline, Albert C.

    1998-01-01

    Epistemic and deontic logics are modal logics, respectively, of knowledge and of the normative concepts of obligation, permission, and prohibition. Epistemic logic is useful in formalizing systems of communicating processes and knowledge and belief in AI (Artificial Intelligence). Deontic logic is useful in computer science wherever we must distinguish between actual and ideal behavior, as in fault tolerance and database integrity constraints. We here discuss fuzzy versions of these logics. In the crisp versions, various axioms correspond to various properties of the structures used in defining the semantics of the logics. Thus, any axiomatic theory will be characterized not only by its axioms but also by the set of properties holding of the corresponding semantic structures. Fuzzy logic does not proceed with axiomatic systems, but fuzzy versions of the semantic properties exist and can be shown to correspond to some of the axioms for the crisp systems in special ways that support dependency networks among assertions in a modal domain. This in turn allows one to implement truth maintenance systems. For the technical development of epistemic logic, and for that of deontic logic. To our knowledge, we are the first to address fuzzy epistemic and fuzzy deontic logic explicitly and to consider the different systems and semantic properties available. We give the syntax and semantics of epistemic logic and discuss the correspondence between axioms of epistemic logic and properties of semantic structures. The same topics are covered for deontic logic. Fuzzy epistemic and fuzzy deontic logic discusses the relationship between axioms and semantic properties for these logics. Our results can be exploited in truth maintenance systems.

  8. Fuzzy logic and neural networks basic concepts & application

    CERN Document Server

    Alavala, Chennakesava R

    2008-01-01

    About the Book: The primary purpose of this book is to provide the student with a comprehensive knowledge of basic concepts of fuzzy logic and neural networks. The hybridization of fuzzy logic and neural networks is also included. No previous knowledge of fuzzy logic and neural networks is required. Fuzzy logic and neural networks have been discussed in detail through illustrative examples, methods and generic applications. Extensive and carefully selected references is an invaluable resource for further study of fuzzy logic and neural networks. Each chapter is followed by a question bank

  9. A SELF-ORGANISING FUZZY LOGIC CONTROLLER

    African Journals Online (AJOL)

    ES Obe

    One major drawback of fuzzy logic controllers is the difficulty encountered in the construction of a rule- base ... The greatest limitation of fuzzy logic control is the lack ..... c(kT)= e(kT)-e((k-1)T). (16) .... with the aid of fuzzy models”, It in Industrial.

  10. Fuzzy Logic in Medicine and Bioinformatics

    Directory of Open Access Journals (Sweden)

    Angela Torres

    2006-01-01

    Full Text Available The purpose of this paper is to present a general view of the current applications of fuzzy logic in medicine and bioinformatics. We particularly review the medical literature using fuzzy logic. We then recall the geometrical interpretation of fuzzy sets as points in a fuzzy hypercube and present two concrete illustrations in medicine (drug addictions and in bioinformatics (comparison of genomes.

  11. Fuzzy logic control of nuclear power plant

    International Nuclear Information System (INIS)

    Yao Liangzhong; Guo Renjun; Ma Changwen

    1996-01-01

    The main advantage of the fuzzy logic control is that the method does not require a detailed mathematical model of the object to be controlled. In this paper, the shortcomings and limitations of the model-based method in nuclear power plant control were presented, the theory of the fuzzy logic control was briefly introduced, and the applications of the fuzzy logic control technology in nuclear power plant controls were surveyed. Finally, the problems to be solved by using the fuzzy logic control in nuclear power plants were discussed

  12. Molecular processors: from qubits to fuzzy logic.

    Science.gov (United States)

    Gentili, Pier Luigi

    2011-03-14

    Single molecules or their assemblies are information processing devices. Herein it is demonstrated how it is possible to process different types of logic through molecules. As long as decoherent effects are maintained far away from a pure quantum mechanical system, quantum logic can be processed. If the collapse of superimposed or entangled wavefunctions is unavoidable, molecules can still be used to process either crisp (binary or multi-valued) or fuzzy logic. The way for implementing fuzzy inference engines is declared and it is supported by the examples of molecular fuzzy logic systems devised so far. Fuzzy logic is drawing attention in the field of artificial intelligence, because it models human reasoning quite well. This ability may be due to some structural analogies between a fuzzy logic system and the human nervous system. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  13. Improvements to Earthquake Location with a Fuzzy Logic Approach

    Science.gov (United States)

    Gökalp, Hüseyin

    2018-01-01

    In this study, improvements to the earthquake location method were investigated using a fuzzy logic approach proposed by Lin and Sanford (Bull Seismol Soc Am 91:82-93, 2001). The method has certain advantages compared to the inverse methods in terms of eliminating the uncertainties of arrival times and reading errors. In this study, adopting this approach, epicentral locations were determined based on the results of a fuzzy logic space concerning the uncertainties in the velocity models. To map the uncertainties in arrival times into the fuzzy logic space, a trapezoidal membership function was constructed by directly using the travel time difference between the two stations for the P- and S-arrival times instead of the P- and S-wave models to eliminate the need for obtaining information concerning the velocity structure of the study area. The results showed that this method worked most effectively when earthquakes occurred away from a network or when the arrival time data contained phase reading errors. In this study, to resolve the problems related to determining the epicentral locations of the events, a forward modeling method like the grid search technique was used by applying different logical operations (i.e., intersection, union, and their combination) with a fuzzy logic approach. The locations of the events were depended on results of fuzzy logic outputs in fuzzy logic space by searching in a gridded region. The process of location determination with the defuzzification of only the grid points with the membership value of 1 obtained by normalizing all the maximum fuzzy output values of the highest values resulted in more reliable epicentral locations for the earthquakes than the other approaches. In addition, throughout the process, the center-of-gravity method was used as a defuzzification operation.

  14. A fuzzy logic pitch angle controller for power system stabilization

    Energy Technology Data Exchange (ETDEWEB)

    Jauch, Clemens; Cronin, Tom; Sorensen, Poul [Wind Energy Department, Riso National Laboratory, PO Box 49, DK-4000 Roskilde, (Denmark); Jensen, Birgitte Bak [Institute of Energy Technology, Aalborg University, Pontoppidanstraede 101, DK-9220 Aalborg East, (Denmark)

    2006-07-12

    In this article the design of a fuzzy logic pitch angle controller for a fixed speed, active-stall wind turbine, which is used for power system stabilization, is presented. The system to be controlled, which is the wind turbine and the power system to which the turbine is connected, is described. The advantages of fuzzy logic control when applied to large-signal control of active-stall wind turbines are outlined. The general steps of the design process for a fuzzy logic controller, including definition of the controller inputs, set-up of the fuzzy rules and the method of defuzzification, are described. The performance of the controller is assessed by simulation, where the wind turbine's task is to dampen power system oscillations. In the scenario simulated for this work, the wind turbine has to ride through a transient short-circuit fault and subsequently contribute to the damping of the grid frequency oscillations that are caused by the transient fault. It is concluded that the fuzzy logic controller enables the wind turbine to dampen power system oscillations. It is also concluded that, owing to the inherent non-linearities in a wind turbine and the unpredictability of the whole system, the fuzzy logic controller is very suitable for this application. (Author).

  15. Intuitionistic fuzzy logics

    CERN Document Server

    T Atanassov, Krassimir

    2017-01-01

    The book offers a comprehensive survey of intuitionistic fuzzy logics. By reporting on both the author’s research and others’ findings, it provides readers with a complete overview of the field and highlights key issues and open problems, thus suggesting new research directions. Starting with an introduction to the basic elements of intuitionistic fuzzy propositional calculus, it then provides a guide to the use of intuitionistic fuzzy operators and quantifiers, and lastly presents state-of-the-art applications of intuitionistic fuzzy sets. The book is a valuable reference resource for graduate students and researchers alike.

  16. Fuzzy logic of Aristotelian forms

    Energy Technology Data Exchange (ETDEWEB)

    Perlovsky, L.I. [Nichols Research Corp., Lexington, MA (United States)

    1996-12-31

    Model-based approaches to pattern recognition and machine vision have been proposed to overcome the exorbitant training requirements of earlier computational paradigms. However, uncertainties in data were found to lead to a combinatorial explosion of the computational complexity. This issue is related here to the roles of a priori knowledge vs. adaptive learning. What is the a-priori knowledge representation that supports learning? I introduce Modeling Field Theory (MFT), a model-based neural network whose adaptive learning is based on a priori models. These models combine deterministic, fuzzy, and statistical aspects to account for a priori knowledge, its fuzzy nature, and data uncertainties. In the process of learning, a priori fuzzy concepts converge to crisp or probabilistic concepts. The MFT is a convergent dynamical system of only linear computational complexity. Fuzzy logic turns out to be essential for reducing the combinatorial complexity to linear one. I will discuss the relationship of the new computational paradigm to two theories due to Aristotle: theory of Forms and logic. While theory of Forms argued that the mind cannot be based on ready-made a priori concepts, Aristotelian logic operated with just such concepts. I discuss an interpretation of MFT suggesting that its fuzzy logic, combining a-priority and adaptivity, implements Aristotelian theory of Forms (theory of mind). Thus, 2300 years after Aristotle, a logic is developed suitable for his theory of mind.

  17. Application of fuzzy logic control in industry

    International Nuclear Information System (INIS)

    Van der Wal, A.J.

    1994-01-01

    An overview is given of the various ways fuzzy logic can be used to improve industrial control. The application of fuzzy logic in control is illustrated by two case studies. The first example shows how fuzzy logic, incorporated in the hardware of an industrial controller, helps to finetune a PID controller, without the operator having any a priori knowledge of the system to be controlled. The second example is from process industry. Here, fuzzy logic supervisory control is implemented in software and enhances the operation of a sintering oven through a subtle combination of priority management and deviation-controlled timing

  18. Fuzzy logic applications to control engineering

    Science.gov (United States)

    Langari, Reza

    1993-12-01

    This paper presents the results of a project presently under way at Texas A&M which focuses on the use of fuzzy logic in integrated control of manufacturing systems. The specific problems investigated here include diagnosis of critical tool wear in machining of metals via a neuro-fuzzy algorithm, as well as compensation of friction in mechanical positioning systems via an adaptive fuzzy logic algorithm. The results indicate that fuzzy logic in conjunction with conventional algorithmic based approaches or neural nets can prove useful in dealing with the intricacies of control/monitoring of manufacturing systems and can potentially play an active role in multi-modal integrated control systems of the future.

  19. Fuzzy logic: A “simple” solution for complexities in neurosciences?

    Science.gov (United States)

    Godil, Saniya Siraj; Shamim, Muhammad Shahzad; Enam, Syed Ather; Qidwai, Uvais

    2011-01-01

    Background: Fuzzy logic is a multi-valued logic which is similar to human thinking and interpretation. It has the potential of combining human heuristics into computer-assisted decision making, which is applicable to individual patients as it takes into account all the factors and complexities of individuals. Fuzzy logic has been applied in all disciplines of medicine in some form and recently its applicability in neurosciences has also gained momentum. Methods: This review focuses on the use of this concept in various branches of neurosciences including basic neuroscience, neurology, neurosurgery, psychiatry and psychology. Results: The applicability of fuzzy logic is not limited to research related to neuroanatomy, imaging nerve fibers and understanding neurophysiology, but it is also a sensitive and specific tool for interpretation of EEGs, EMGs and MRIs and an effective controller device in intensive care units. It has been used for risk stratification of stroke, diagnosis of different psychiatric illnesses and even planning neurosurgical procedures. Conclusions: In the future, fuzzy logic has the potential of becoming the basis of all clinical decision making and our understanding of neurosciences. PMID:21541006

  20. A New Fuzzy Harmony Search Algorithm Using Fuzzy Logic for Dynamic Parameter Adaptation

    Directory of Open Access Journals (Sweden)

    Cinthia Peraza

    2016-10-01

    Full Text Available In this paper, a new fuzzy harmony search algorithm (FHS for solving optimization problems is presented. FHS is based on a recent method using fuzzy logic for dynamic adaptation of the harmony memory accepting (HMR and pitch adjustment (PArate parameters that improve the convergence rate of traditional harmony search algorithm (HS. The objective of the method is to dynamically adjust the parameters in the range from 0.7 to 1. The impact of using fixed parameters in the harmony search algorithm is discussed and a strategy for efficiently tuning these parameters using fuzzy logic is presented. The FHS algorithm was successfully applied to different benchmarking optimization problems. The results of simulation and comparison studies demonstrate the effectiveness and efficiency of the proposed approach.

  1. A fuzzy logic approach to modeling the underground economy in Taiwan

    Science.gov (United States)

    Yu, Tiffany Hui-Kuang; Wang, David Han-Min; Chen, Su-Jane

    2006-04-01

    The size of the ‘underground economy’ (UE) is valuable information in the formulation of macroeconomic and fiscal policy. This study applies fuzzy set theory and fuzzy logic to model Taiwan's UE over the period from 1960 to 2003. Two major factors affecting the size of the UE, the effective tax rate and the degree of government regulation, are used. The size of Taiwan's UE is scaled and compared with those of other models. Although our approach yields different estimates, similar patterns and leading are exhibited throughout the period. The advantage of applying fuzzy logic is twofold. First, it can avoid the complex calculations in conventional econometric models. Second, fuzzy rules with linguistic terms are easy for human to understand.

  2. FUZZY LOGIC IN LEGAL EDUCATION

    Directory of Open Access Journals (Sweden)

    Z. Gonul BALKIR

    2011-04-01

    Full Text Available The necessity of examination of every case within its peculiar conditions in social sciences requires different approaches complying with the spirit and nature of social sciences. Multiple realities require different and various perceptual interpretations. In modern world and social sciences, interpretation of perception of valued and multi-valued have been started to be understood by the principles of fuzziness and fuzzy logic. Having the verbally expressible degrees of truthness such as true, very true, rather true, etc. fuzzy logic provides the opportunity for the interpretation of especially complex and rather vague set of information by flexibility or equivalence of the variables’ of fuzzy limitations. The methods and principles of fuzzy logic can be benefited in examination of the methodological problems of law, especially in the applications of filling the legal loopholes arising from the ambiguities and interpretation problems in order to understand the legal rules in a more comprehensible and applicable way and the efficiency of legal implications. On the other hand, fuzzy logic can be used as a technical legal method in legal education and especially in legal case studies and legal practice applications in order to provide the perception of law as a value and the more comprehensive and more quality perception and interpretation of value of justice, which is the core value of law. In the perception of what happened as it has happened in legal relationships and formations, the understanding of social reality and sociological legal rules with multi valued sense perspective and the their applications in accordance with the fuzzy logic’s methods could create more equivalent and just results. It can be useful for the young lawyers and law students as a facilitating legal method especially in the materialization of the perception and interpretation of multi valued and variables. Using methods and principles of fuzzy logic in legal

  3. Fuzzy Logic and Education: Teaching the Basics of Fuzzy Logic through an Example (By Way of Cycling)

    Science.gov (United States)

    Sobrino, Alejandro

    2013-01-01

    Fuzzy logic dates back to 1965 and it is related not only to current areas of knowledge, such as Control Theory and Computer Science, but also to traditional ones, such as Philosophy and Linguistics. Like any logic, fuzzy logic is concerned with argumentation, but unlike other modalities, which focus on the crisp reasoning of Mathematics, it deals…

  4. Fuzzy Reasoning Based on First-Order Modal Logic,

    NARCIS (Netherlands)

    Zhang, Xiaoru; Zhang, Z.; Sui, Y.; Huang, Z.

    2008-01-01

    As an extension of traditional modal logics, this paper proposes a fuzzy first-order modal logic based on believable degree, and gives out a description of the fuzzy first-order modal logic based on constant domain semantics. In order to make the reasoning procedure between the fuzzy assertions

  5. Implementation of fuzzy logic control algorithm in embedded ...

    African Journals Online (AJOL)

    Fuzzy logic control algorithm solves problems that are difficult to address with traditional control techniques. This paper describes an implementation of fuzzy logic control algorithm using inexpensive hardware as well as how to use fuzzy logic to tackle a specific control problem without any special software tools. As a case ...

  6. Qualitative assessment of environmental impacts through fuzzy logic

    International Nuclear Information System (INIS)

    Peche G, Roberto

    2008-01-01

    The vagueness of many concepts usually utilized in environmental impact studies, along with frequent lack of quantitative information, suggests that fuzzy logic can be applied to carry out qualitative assessment of such impacts. This paper proposes a method for valuing environmental impacts caused by projects, based on fuzzy sets theory and methods of approximate reasoning. First, impacts must be described by a set of features. A linguistic variable is assigned to each feature, whose values are fuzzy sets. A fuzzy evaluation of environmental impacts is achieved using rule based fuzzy inference and the estimated fuzzy value of each feature. Generalized modus ponens has been the inference method. Finally, a crisp value of impact is attained by aggregation and defuzzification of all fuzzy results

  7. Paraconsistency properties in degree-preserving fuzzy logics

    Czech Academy of Sciences Publication Activity Database

    Ertola, R.; Esteva, F.; Flaminio, T.; Godo, L.; Noguera, Carles

    2015-01-01

    Roč. 19, č. 3 (2015), s. 531-546 ISSN 1432-7643 R&D Projects: GA ČR GAP202/10/1826 Institutional support: RVO:67985556 Keywords : Mathematical fuzzy logic * degree-preserving fuzzy logics * paraconsistent logics * logics of formal inconsistency Subject RIV: BA - General Mathematics Impact factor: 1.630, year: 2015 http://library.utia.cas.cz/separaty/2016/MTR/noguera-0469166.pdf

  8. Fuzzy logic as support for security and safety solution in soft targets

    Directory of Open Access Journals (Sweden)

    Ďuricová Lucia

    2016-01-01

    Full Text Available Security and safety situations in objects, which are categorized as soft targets, is difficult. The current solving is based on several different type of solving. Soft targets are specific objects, and it requires special software solution. The proposal is based on fuzzy logic. Fuzzy logic could apply more expert’s knowledges and it could help owners and managers with adequate responses in critical situation, and also definition of adequate preventive actions. System solving could help effectivity of proposed measures. The decision making is based on this fuzzy logic support and aim is explained in paper.

  9. Imperialist Competitive Algorithm with Dynamic Parameter Adaptation Using Fuzzy Logic Applied to the Optimization of Mathematical Functions

    Directory of Open Access Journals (Sweden)

    Emer Bernal

    2017-01-01

    Full Text Available In this paper we are presenting a method using fuzzy logic for dynamic parameter adaptation in the imperialist competitive algorithm, which is usually known by its acronym ICA. The ICA algorithm was initially studied in its original form to find out how it works and what parameters have more effect upon its results. Based on this study, several designs of fuzzy systems for dynamic adjustment of the ICA parameters are proposed. The experiments were performed on the basis of solving complex optimization problems, particularly applied to benchmark mathematical functions. A comparison of the original imperialist competitive algorithm and our proposed fuzzy imperialist competitive algorithm was performed. In addition, the fuzzy ICA was compared with another metaheuristic using a statistical test to measure the advantage of the proposed fuzzy approach for dynamic parameter adaptation.

  10. Autonomous vehicle motion control, approximate maps, and fuzzy logic

    Science.gov (United States)

    Ruspini, Enrique H.

    1993-01-01

    Progress on research on the control of actions of autonomous mobile agents using fuzzy logic is presented. The innovations described encompass theoretical and applied developments. At the theoretical level, results of research leading to the combined utilization of conventional artificial planning techniques with fuzzy logic approaches for the control of local motion and perception actions are presented. Also formulations of dynamic programming approaches to optimal control in the context of the analysis of approximate models of the real world are examined. Also a new approach to goal conflict resolution that does not require specification of numerical values representing relative goal importance is reviewed. Applied developments include the introduction of the notion of approximate map. A fuzzy relational database structure for the representation of vague and imprecise information about the robot's environment is proposed. Also the central notions of control point and control structure are discussed.

  11. Mathematical Fuzzy Logic - State of Art 2001

    Czech Academy of Sciences Publication Activity Database

    Hájek, Petr

    2003-01-01

    Roč. 24, - (2003), s. 71-89 ISSN 0103-9059. [WOLLIC'2001. Brasília, 31.07.2001-03.08.2001] R&D Projects: GA MŠk LN00A056 Keywords : fuzzy logic * many valued logic * basic fuzzy logic BL Subject RIV: BA - General Mathematics http://www.mat.unb.br/~matcont/24_4.pdf

  12. Fuzzy logic based control system for fresh water aquaculture: A MATLAB based simulation approach

    Directory of Open Access Journals (Sweden)

    Rana Dinesh Singh

    2015-01-01

    Full Text Available Fuzzy control is regarded as the most widely used application of fuzzy logic. Fuzzy logic is an innovative technology to design solutions for multiparameter and non-linear control problems. One of the greatest advantages of fuzzy control is that it uses human experience and process information obtained from operator rather than a mathematical model for the definition of a control strategy. As a result, it often delivers solutions faster than conventional control design techniques. The proposed system is an attempt to apply fuzzy logic techniques to predict the stress factor on the fish, based on line data and rule base generated using domain expert. The proposed work includes a use of Data acquisition system, an interfacing device for on line parameter acquisition and analysis, fuzzy logic controller (FLC for inferring the stress factor. The system takes stress parameters on the fish as inputs, fuzzified by using FLC with knowledge base rules and finally provides single output. All the parameters are controlled and calibrated by the fuzzy logic toolbox and MATLAB programming.

  13. On-line tuning of a fuzzy-logic power system stabilizer

    International Nuclear Information System (INIS)

    Hossein-Zadeh, N.; Kalam, A.

    2002-01-01

    A scheme for on-line tuning of a fuzzy-logic power system stabilizer is presented. firstly, a fuzzy-logic power system stabilizer is developed using speed deviation and accelerating power as the controller input variables. The inference mechanism of fuzzy-logic controller is represented by a decision table, constructed of linguistic IF-THEN rules. The Linguistic rules are available from experts and the design procedure is based on these rules. It assumed that an exact model of the plant is not available and it is difficult to extract the exact parameters of the power plant. Thus, the design procedure can not be based on an exact model. This is an advantage of fuzzy logic that makes the design of a controller possible without knowing the exact model of the plant. Secondly, two scaling parameters are introduced to tune the fuzzy-logic power system stabilizer. These scaling parameters are the outputs of another fuzzy-logic system, which gets the operating conditions of power system as inputs. These mechanism of tuning the fuzzy-logic power system stabilizer makes the fuzzy-logic power system stabilizer adaptive to changes in the operating conditions. Therefore, the degradation of the system response, under a wide range of operating conditions, is less compared to the system response with a fixed-parameter fuzzy-logic power system stabilizer and a conventional (linear) power system stabilizer. The tuned stabilizer has been tested by performing nonlinear simulations using a synchronous machine-infinite bus model. The responses are compared with a fixed parameters fuzzy-logic power system stabilizer and a conventional (linear) power system stabilizer. It is shown that the tuned fuzzy-logic power system stabilizer is superior to both of them

  14. Petr Hájek on mathematical fuzzy logic

    CERN Document Server

    Montagna, Franco

    2014-01-01

    This volume celebrates the work of Petr Hájek on mathematical fuzzy logic and presents how his efforts have influenced prominent logicians who are continuing his work. The book opens with a discussion on Hájek's contribution to mathematical fuzzy logic and with a scientific biography of him, progresses to include two articles with a foundation flavour, that demonstrate some important aspects of Hájek's production, namely, a paper on the development of fuzzy sets and another paper on some fuzzy versions of set theory and arithmetic. Articles in the volume also focus on the treatment of vague

  15. Fuzzy Logic and PID control of a 3 DOF Robotic Arm

    Directory of Open Access Journals (Sweden)

    Korhan Kayışlı

    2017-12-01

    Full Text Available The robotic arms are used in many industrial applications at the present time. At this point, high precision control is required for robotics used in fields such as healthcare area. Therefore, the control method applied to robots is also important. In this study, a force was applied to the end function of a three degree-of-freedom robot and the robustness of the controllers are tested. PID and Fuzzy Logic control method are used for this process. The control process of robotic arm which is designed and simulated is obtained by using Fuzzy Logic and classical PID controllers and the results are presented comparatively

  16. Multi-objective decision-making under uncertainty: Fuzzy logic methods

    Science.gov (United States)

    Hardy, Terry L.

    1995-01-01

    Fuzzy logic allows for quantitative representation of vague or fuzzy objectives, and therefore is well-suited for multi-objective decision-making. This paper presents methods employing fuzzy logic concepts to assist in the decision-making process. In addition, this paper describes software developed at NASA Lewis Research Center for assisting in the decision-making process. Two diverse examples are used to illustrate the use of fuzzy logic in choosing an alternative among many options and objectives. One example is the selection of a lunar lander ascent propulsion system, and the other example is the selection of an aeration system for improving the water quality of the Cuyahoga River in Cleveland, Ohio. The fuzzy logic techniques provided here are powerful tools which complement existing approaches, and therefore should be considered in future decision-making activities.

  17. Fuzzy logic an introductory course for engineering students

    CERN Document Server

    Trillas, Enric

    2015-01-01

      This book introduces readers to fundamental concepts in fuzzy logic. It describes the necessary theoretical background and a number of basic mathematical models. Moreover, it makes them familiar with fuzzy control, an important topic in the engineering field. The book offers an unconventional introductory textbook on fuzzy logic, presenting theory together with examples and not always following the typical mathematical style of theorem-corollaries. Primarily intended to support engineers during their university studies, and to spark their curiosity about fuzzy logic and its applications, the book is also suitable for self-study, providing a valuable resource for engineers and professionals who deal with imprecision and non-random uncertainty in real-world applications.  

  18. Comparison of Anti-Virus Programs using Fuzzy Logic

    Directory of Open Access Journals (Sweden)

    Vaclav Bezdek

    2013-07-01

    Full Text Available This work follows the previous author´s paper: Possible use of Fuzzy Logic in Database. It tries to show application of Fuzzy Logic in selecting the best anti-virus software based on testing made by AV-Comparatives.

  19. The first order fuzzy predicate logic (I)

    International Nuclear Information System (INIS)

    Sheng, Y.M.

    1986-01-01

    Some analysis tools of fuzzy measures, Sugeno's integrals, etc. are introduced into the semantic of the first order predicate logic to explain the concept of fuzzy quantifiers. The truth value of a fuzzy quantification proposition is represented by Sugeno's integral. With this framework, several important notions of formation rules, fuzzy valutions and fuzzy validity are discussed

  20. Efficient fuzzy logic controller for magnetic levitation systems | Shu ...

    African Journals Online (AJOL)

    In this paper magnetic levitation controller using fuzzy logic is proposed. The proposed Fuzzy logic controller (FLC) is designed, and developed using triangular membership function with 7×7 rules. The system model was implemented in MATLAB/SIMULINK and the system responses to Fuzzy controller with different input ...

  1. INDONESIA PUBLIC BANKS PERFORMANCE EVALUATION USING FUZZY LOGIC

    Directory of Open Access Journals (Sweden)

    Sugiarto Sugiarto

    2016-10-01

    Full Text Available Return on Asset (ROA is a variable that has the greatest ability in predicting public banks stock prices in Indonesia. The coefficient of determination of ROA on public banks stock prices in Indonesia reached 54.8%. ROA has a significant positive influence on public bank stock prices in Indonesia. Fuzzy logic process on the performance of the 15 public banks in Indonesia have been carried out using the data of ROA for the period 2010 up to 2013. Bank reference performance according to ROA is based on Bank Indonesia Letter No. 6 / 23DPNP / 2011. The performance of each bank was analyzed by conventional methods and as a comparison used fuzzy logic. The evaluation with fuzzy logic method able to provide added value to the currently enforced performance evaluation method. There is significant difference in conclusion between the determination of fuzzy logic models and conventional method

  2. Enric Trillas a passion for fuzzy sets : a collection of recent works on fuzzy logic

    CERN Document Server

    Verdegay, Jose; Esteva, Francesc

    2015-01-01

    This book presents a comprehensive collection of the latest and most significant research advances and applications in the field of fuzzy logic. It covers fuzzy structures, rules, operations and mathematical formalisms, as well as important applications of fuzzy logic in a number of fields, like decision-making, environmental prediction and prevention, communication, controls and many others. Dedicated to Enric Trillas in recognition of his pioneering research in the field, the book also includes a foreword by Lotfi A. Zadeh and an outlook on the future of fuzzy logic.

  3. IDENTIFIKASI SINYAL ECG IRAMA MYOCARDIAL ISCHEMIA DENGAN PENDEKATAN FUZZY LOGIC

    Directory of Open Access Journals (Sweden)

    Azhar A N

    2009-07-01

    Full Text Available The heart is one of vital organs in human body. Incidence of heart disease can be fatal for the patient. Myocardial ischemia, the disease that is often suffered by the human, is a disease due to clogged heart arteries blood vessels. One of the ways to detect this disease is by reading the graph output of electrocardiogram (ECG signal. ECG signal represents the condition and activity of the heart. Specialized knowledge, accuration and expertise are required to read ECG graph. To help expert or doctor, expert system based on artificial intelligent, such as Fuzzy Logic approach, can be applied to improve diagnostic accuracy and thoroughness. Fuzzy logic can be applied because of it flexibility to understand the linguistic variables used in identifying myocardial ischemia disease.

  4. Structural Completeness in Fuzzy Logics

    Czech Academy of Sciences Publication Activity Database

    Cintula, Petr; Metcalfe, G.

    2009-01-01

    Roč. 50, č. 2 (2009), s. 153-183 ISSN 0029-4527 R&D Projects: GA MŠk(CZ) 1M0545 Institutional research plan: CEZ:AV0Z10300504 Keywords : structral logics * fuzzy logics * structural completeness * admissible rules * primitive variety * residuated lattices Subject RIV: BA - General Mathematics

  5. Multi-valued and Fuzzy Logic Realization using TaOx Memristive Devices.

    Science.gov (United States)

    Bhattacharjee, Debjyoti; Kim, Wonjoo; Chattopadhyay, Anupam; Waser, Rainer; Rana, Vikas

    2018-01-08

    Among emerging non-volatile storage technologies, redox-based resistive switching Random Access Memory (ReRAM) is a prominent one. The realization of Boolean logic functionalities using ReRAM adds an extra edge to this technology. Recently, 7-state ReRAM devices were used to realize ternary arithmetic circuits, which opens up the computing space beyond traditional binary values. In this manuscript, we report realization of multi-valued and fuzzy logic operators with a representative application using ReRAM devices. Multi-valued logic (MVL), such as Łukasiewicz logic generalizes Boolean logic by allowing more than two truth values. MVL also permits operations on fuzzy sets, where, in contrast to standard crisp logic, an element is permitted to have a degree of membership to a given set. Fuzzy operations generally model human reasoning better than Boolean logic operations, which is predominant in current computing technologies. When the available information for the modelling of a system is imprecise and incomplete, fuzzy logic provides an excellent framework for the system design. Practical applications of fuzzy logic include, industrial control systems, robotics, and in general, design of expert systems through knowledge-based reasoning. Our experimental results show, for the first time, that it is possible to model fuzzy logic natively using multi-state memristive devices.

  6. Regression Models and Fuzzy Logic Prediction of TBM Penetration Rate

    Directory of Open Access Journals (Sweden)

    Minh Vu Trieu

    2017-03-01

    Full Text Available This paper presents statistical analyses of rock engineering properties and the measured penetration rate of tunnel boring machine (TBM based on the data of an actual project. The aim of this study is to analyze the influence of rock engineering properties including uniaxial compressive strength (UCS, Brazilian tensile strength (BTS, rock brittleness index (BI, the distance between planes of weakness (DPW, and the alpha angle (Alpha between the tunnel axis and the planes of weakness on the TBM rate of penetration (ROP. Four (4 statistical regression models (two linear and two nonlinear are built to predict the ROP of TBM. Finally a fuzzy logic model is developed as an alternative method and compared to the four statistical regression models. Results show that the fuzzy logic model provides better estimations and can be applied to predict the TBM performance. The R-squared value (R2 of the fuzzy logic model scores the highest value of 0.714 over the second runner-up of 0.667 from the multiple variables nonlinear regression model.

  7. Regression Models and Fuzzy Logic Prediction of TBM Penetration Rate

    Science.gov (United States)

    Minh, Vu Trieu; Katushin, Dmitri; Antonov, Maksim; Veinthal, Renno

    2017-03-01

    This paper presents statistical analyses of rock engineering properties and the measured penetration rate of tunnel boring machine (TBM) based on the data of an actual project. The aim of this study is to analyze the influence of rock engineering properties including uniaxial compressive strength (UCS), Brazilian tensile strength (BTS), rock brittleness index (BI), the distance between planes of weakness (DPW), and the alpha angle (Alpha) between the tunnel axis and the planes of weakness on the TBM rate of penetration (ROP). Four (4) statistical regression models (two linear and two nonlinear) are built to predict the ROP of TBM. Finally a fuzzy logic model is developed as an alternative method and compared to the four statistical regression models. Results show that the fuzzy logic model provides better estimations and can be applied to predict the TBM performance. The R-squared value (R2) of the fuzzy logic model scores the highest value of 0.714 over the second runner-up of 0.667 from the multiple variables nonlinear regression model.

  8. A study of photovoltaic/thermal (PVT)-ground source heat pump hybrid system by using fuzzy logic control

    International Nuclear Information System (INIS)

    Andrew Putrayudha, S.; Kang, Eun Chul; Evgueniy, E.; Libing, Y.; Lee, Euy Joon

    2015-01-01

    Renewable Heat Obligation (RHO) implementation in every country becomes an important issue to utilize more renewable energy sources while reducing the usage of fossil fuel. In 2014, South Korea has a target that every commercial building construction that exceeding 10,000 m 2 has to have on-site new & renewable power generation such as combined heat in the beginning of 2016. Photovoltaic/Thermal (PVT) and Geothermal hybrid systems have been introduced in previous research (E.J. Lee et al.) and it showed a great result from its efficiency and also its power consumption for single and multi-building cases. In this paper, Fuzzy Logic control has been applied to optimize the energy consumption of the system. By comparing it with conventional on–off control, fuzzy logic control system shows a better result in reducing primary energy consumption for both heating and cooling systems annually. Two cases were introduced in this paper, GSHP system and PVT–GSHP system with both on–off and fuzzy logic applied respectively. As a result, it shows that fuzzy logic control consumed 13.3% less energy compared with on–off controller for GSHP system annually and 18.3% less energy compared to on–off controller for PVT–GSHP system annually. - Highlights: • Two renewable systems were designed to produce heating, cooling and electricity. • System optimization by applying Fuzzy Logic in terms of energy saving. • Conventional on–off control system vs advance fuzzy logic control system. • Assumption used based on previous research experience, guidelines.

  9. A practical introduction to fuzzy logic using LISP

    CERN Document Server

    Argüelles Mendez, Luis

    2016-01-01

    This book makes use of the LISP programming language to provide readers with the necessary background to understand and use fuzzy logic to solve simple to medium-complexity real-world problems. It introduces the basics of LISP required to use a Fuzzy LISP programming toolbox, which was specifically implemented by the author to “teach” the theory behind fuzzy logic and at the same time equip readers to use their newly-acquired knowledge to build fuzzy models of increasing complexity. The book fills an important gap in the literature, providing readers with a practice-oriented reference guide to fuzzy logic that offers more complexity than popular books yet is more accessible than other mathematical treatises on the topic. As such, students in first-year university courses with a basic tertiary mathematical background and no previous experience with programming should be able to easily follow the content. The book is intended for students and professionals in the fields of computer science and engineering, ...

  10. Fuzzy Logic Controller Design for Intelligent Robots

    Directory of Open Access Journals (Sweden)

    Ching-Han Chen

    2017-01-01

    Full Text Available This paper presents a fuzzy logic controller by which a robot can imitate biological behaviors such as avoiding obstacles or following walls. The proposed structure is implemented by integrating multiple ultrasonic sensors into a robot to collect data from a real-world environment. The decisions that govern the robot’s behavior and autopilot navigation are driven by a field programmable gate array- (FPGA- based fuzzy logic controller. The validity of the proposed controller was demonstrated by simulating three real-world scenarios to test the bionic behavior of a custom-built robot. The results revealed satisfactorily intelligent performance of the proposed fuzzy logic controller. The controller enabled the robot to demonstrate intelligent behaviors in complex environments. Furthermore, the robot’s bionic functions satisfied its design objectives.

  11. Application of fuzzy logic operation and control to BWRs

    International Nuclear Information System (INIS)

    Junichi Tanji; Mitsuo Kinoshita; Takaharu Fukuzaki; Yasuhiro Kobayashi

    1993-01-01

    Fuzzy logic control schemes employing linguistic decision rules for flexible operator control strategies have undergone application tests in dynamic systems. The advantages claimed for fuzzy logic control are its abilities: (a) to facilitate direct use of skillful operator know-how for automatic operation and control of the systems and (b) to provide robust multivariable control for complex plants. The authors have also studied applications of fuzzy logic control to automatic startup operations and load-following control in boiling water reactors, pursuing these same advantages

  12. Fuzzy logic and intelligent technologies in nuclear science

    International Nuclear Information System (INIS)

    Ruan, D.

    1998-01-01

    The research project on Fuzzy Logic and Intelligent technologies (FLINS) aims to bridge the gap between novel technologies and the nuclear industry. It aims to initiate research and development programs for solving intricate problems pertaining to the nuclear environment by using modern technologies as additional tool. The major achievements for 1997 include the application of the fuzzy-logic to the BR-1 reactor, the elaboration of a Fuzzy-control model as well as contributions to several workshops and publications

  13. Possible use of fuzzy logic in database

    Directory of Open Access Journals (Sweden)

    Vaclav Bezdek

    2011-04-01

    Full Text Available The article deals with fuzzy logic and its possible use in database systems. At first fuzzy thinking style is shown on a simple example. Next the advantages of the fuzzy approach to database searching are considered on the database of used cars in the Czech Republic.

  14. Bicycle Frame Prediction Techniques with Fuzzy Logic Method

    Directory of Open Access Journals (Sweden)

    Rafiuddin Syam

    2015-03-01

    Full Text Available In general, an appropriate size bike frame would get comfort to the rider while biking. This study aims to predict the simulation system on the bike frame sizes with fuzzy logic. Testing method used is the simulation test. In this study, fuzzy logic will be simulated using Matlab language to test their performance. Mamdani fuzzy logic using 3 variables and 1 output variable intake. Triangle function for the input and output. The controller is designed in the type mamdani with max-min composition and the method deffuzification using center of gravity method. The results showed that height, inseam and Crank Size generating appropriate frame size for the rider associated with comfort. Has a height range between 142 cm and 201 cm. Inseam has a range between 64 cm and 97 cm. Crank has a size range between 175 mm and 180 mm. The simulation results have a range of frame sizes between 13 inches and 22 inches. By using the fuzzy logic can be predicted the size frame of bicycle suitable for the biker.

  15. Bicycle Frame Prediction Techniques with Fuzzy Logic Method

    Directory of Open Access Journals (Sweden)

    Rafiuddin Syam

    2017-03-01

    Full Text Available In general, an appropriate size bike frame would get comfort to the rider while biking. This study aims to predict the simulation system on the bike frame sizes with fuzzy logic. Testing method used is the simulation test. In this study, fuzzy logic will be simulated using Matlab language to test their performance. Mamdani fuzzy logic using 3 variables and 1 output variable intake. Triangle function for the input and output. The controller is designed in the type mamdani with max-min composition and the method deffuzification using center of gravity method. The results showed that height, inseam and Crank Size generating appropriate frame size for the rider associated with comfort. Has a height range between 142 cm and 201 cm. Inseam has a range between 64 cm and 97 cm. Crank has a size range between 175 mm and 180 mm. The simulation results have a range of frame sizes between 13 inches and 22 inches. By using the fuzzy logic can be predicted the size frame of bicycle suitable for the biker.

  16. Self-tuning fuzzy logic nuclear reactor controller

    International Nuclear Information System (INIS)

    Sharif Heger, A.; Alang-Rashid, N.K.

    1996-01-01

    We present a method for self-tuning of fuzzy logic controllers based on the estimation of the optimum value of the centroids of its output fuzzy set. The method can be implemented on-line and does not require modification of membership functions and control rules. The main features of this method are: the rules are left intact to retain the operator's expertise in the FLC rule base, and the parameters that require any adjustment are identifiable in advance and their number is kept at a minimum. Therefore, the use of this method preserves the control statements in the original form. Results of simulation and actual tests show that this tuning method improves the performance of fuzzy logic controllers in following the desired reactor power level trajectories. In addition, this method demonstrates a similar improvement for power up and power down experiments, based on both simulation and actual case studies. For these experiments, the control rules for the fuzzy logic controller were derived from control statements that expressed the relationships between error, rate of error change, and duration of direction of control rod movements

  17. Wide-range nuclear reactor temperature control using automatically tuned fuzzy logic controller

    International Nuclear Information System (INIS)

    Ramaswamy, P.; Edwards, R.M.; Lee, K.Y.

    1992-01-01

    In this paper, a fuzzy logic controller design for optimal reactor temperature control is presented. Since fuzzy logic controllers rely on an expert's knowledge of the process, they are hard to optimize. An optimal controller is used in this paper as a reference model, and a Kalman filter is used to automatically determine the rules for the fuzzy logic controller. To demonstrate the robustness of this design, a nonlinear six-delayed-neutron-group plant is controlled using a fuzzy logic controller that utilizes estimated reactor temperatures from a one-delayed-neutron-group observer. The fuzzy logic controller displayed good stability and performance robustness characteristics for a wide range of operation

  18. modelling room cooling capacity with fuzzy logic procedure

    African Journals Online (AJOL)

    The primary aim of this study is to develop a model for estimation of the cooling requirement of residential rooms. Fuzzy logic was employed to model four input variables (window area (m2), roof area (m2), external wall area (m2) and internal load (Watt). The algorithm of the inference engine applied sets of 81 linguistic ...

  19. A Hedge for Gödel Fuzzy Logic

    Czech Academy of Sciences Publication Activity Database

    Hájek, Petr; Harmancová, Dagmar

    2000-01-01

    Roč. 8, č. 4 (2000), s. 495-498 ISSN 0218-4885 Grant - others:COST(XE) Action 15 Institutional research plan: AV0Z1030915 Keywords : fuzzy logic * Gödel logic * intuitionistic logic * hedges Subject RIV: BA - General Mathematics Impact factor: 0.145, year: 2000

  20. Edge detection methods based on generalized type-2 fuzzy logic

    CERN Document Server

    Gonzalez, Claudia I; Castro, Juan R; Castillo, Oscar

    2017-01-01

    In this book four new methods are proposed. In the first method the generalized type-2 fuzzy logic is combined with the morphological gra-dient technique. The second method combines the general type-2 fuzzy systems (GT2 FSs) and the Sobel operator; in the third approach the me-thodology based on Sobel operator and GT2 FSs is improved to be applied on color images. In the fourth approach, we proposed a novel edge detec-tion method where, a digital image is converted a generalized type-2 fuzzy image. In this book it is also included a comparative study of type-1, inter-val type-2 and generalized type-2 fuzzy systems as tools to enhance edge detection in digital images when used in conjunction with the morphologi-cal gradient and the Sobel operator. The proposed generalized type-2 fuzzy edge detection methods were tested with benchmark images and synthetic images, in a grayscale and color format. Another contribution in this book is that the generalized type-2 fuzzy edge detector method is applied in the preproc...

  1. Integrated development environment for fuzzy logic applications

    Science.gov (United States)

    Pagni, Andrea; Poluzzi, Rinaldo; Rizzotto, GianGuido; Lo Presti, Matteo

    1993-12-01

    During the last five years, Fuzzy Logic has gained enormous popularity, both in the academic and industrial worlds, breaking up the traditional resistance against changes thanks to its innovative approach to problems formalization. The success of this new methodology is pushing the creation of a brand new class of devices, called Fuzzy Machines, to overcome the limitations of traditional computing systems when acting as Fuzzy Systems and adequate Software Tools to efficiently develop new applications. This paper aims to present a complete development environment for the definition of fuzzy logic based applications. The environment is also coupled with a sophisticated software tool for semiautomatic synthesis and optimization of the rules with stability verifications. Later it is presented the architecture of WARP, a dedicate VLSI programmable chip allowing to compute in real time a fuzzy control process. The article is completed with two application examples, which have been carried out exploiting the aforementioned tools and devices.

  2. Type-2 fuzzy logic uncertain systems’ modeling and control

    CERN Document Server

    Antão, Rómulo

    2017-01-01

    This book focuses on a particular domain of Type-2 Fuzzy Logic, related to process modeling and control applications. It deepens readers’understanding of Type-2 Fuzzy Logic with regard to the following three topics: using simpler methods to train a Type-2 Takagi-Sugeno Fuzzy Model; using the principles of Type-2 Fuzzy Logic to reduce the influence of modeling uncertainties on a locally linear n-step ahead predictor; and developing model-based control algorithms according to the Generalized Predictive Control principles using Type-2 Fuzzy Sets. Throughout the book, theory is always complemented with practical applications and readers are invited to take their learning process one step farther and implement their own applications using the algorithms’ source codes (provided). As such, the book offers avaluable referenceguide for allengineers and researchers in the field ofcomputer science who are interested in intelligent systems, rule-based systems and modeling uncertainty.

  3. An automatic tuning method of a fuzzy logic controller for nuclear reactors

    International Nuclear Information System (INIS)

    Ramaswamy, P.; Lee, K.Y.; Edwards, R.M.

    1993-01-01

    The design and evaluation by simulation of an automatically tuned fuzzy logic controller is presented. Typically, fuzzy logic controllers are designed based on an expert's knowledge of the process. However, this approach has its limitations in the fact that the controller is hard to optimize or tune to get the desired control action. A method to automate the tuning process using a simplified Kalman filter approach is presented for the fuzzy logic controller to track a suitable reference trajectory. Here, for purposes of illustration an optimal controller's response is used as a reference trajectory to determine automatically the rules for the fuzzy logic controller. To demonstrate the robustness of this design approach, a nonlinear six-delayed neutron group plant is controlled using a fuzzy logic controller that utilizes estimated reactor temperatures from a one-delayed neutron group observer. The fuzzy logic controller displayed good stability and performance robustness characteristics for a wide range of operation

  4. Fuzzy knowledge base construction through belief networks based on Lukasiewicz logic

    Science.gov (United States)

    Lara-Rosano, Felipe

    1992-01-01

    In this paper, a procedure is proposed to build a fuzzy knowledge base founded on fuzzy belief networks and Lukasiewicz logic. Fuzzy procedures are developed to do the following: to assess the belief values of a consequent, in terms of the belief values of its logical antecedents and the belief value of the corresponding logical function; and to update belief values when new evidence is available.

  5. Design a Fuzzy Logic Controller for a Rotary Flexible Joint Robotic Arm

    Directory of Open Access Journals (Sweden)

    Jalani Jamaludin

    2018-01-01

    Full Text Available The purpose of this research is to design a fuzzy logic feedback controller (FLC in order to control a desired tip angle position a rotary flexible joint robotic arm. The FLC is also employed to dampen the vibration emanated from a rotary flexible joint robotic arm when reaching a desired tip angle position. The performance of FLC is tested in simulation and experiment. It is found that the FLC is successfully designed, applied and tested. The results show that fuzzy logic controller performed satisfactorily control a desired tip angle position and reduce the oscillations.

  6. Redundant sensor validation by using fuzzy logic

    International Nuclear Information System (INIS)

    Holbert, K.E.; Heger, A.S.; Alang-Rashid, N.K.

    1994-01-01

    This research is motivated by the need to relax the strict boundary of numeric-based signal validation. To this end, the use of fuzzy logic for redundant sensor validation is introduced. Since signal validation employs both numbers and qualitative statements, fuzzy logic provides a pathway for transforming human abstractions into the numerical domain and thus coupling both sources of information. With this transformation, linguistically expressed analysis principles can be coded into a classification rule-base for signal failure detection and identification

  7. SISTEM PENGEMBANGAN KENDALI FUZZY LOGIC BERBASIS MIKROKONTROLER KELUARGA MCS51 (PetraFuz

    Directory of Open Access Journals (Sweden)

    Thiang Thiang

    1999-01-01

    Full Text Available This paper presents a Fuzzy Logic Development Tool called PetraFuz which has been developed at Control System Laboratory, Electrical Engineering Department, Petra Christian University. The system consists of a hardware target based on MCS51 microcontroller and a software support running under PC Windows. The system is targeted for developing fuzzy logic based systems. It supports fuzzy logic design, evaluation, assembly language generator and downloading process to the target hardware to perform on-line fuzzy process. Process action and fuzzy parameters could be transferred to PC monitor via RS-232 serial communication, this on-line process parameters is used for fuzzy tuning, i.e. fuzzy if-then rules and fuzzy membership functions. The PetraFuz tool helps very much for Fuzzy system developments, it could reduce development time significantly. The tool could spur the development of fuzzy systems based on microcontroller systems such as fuzzy control systems, fuzzy information processing, etc. Abstract in Bahasa Indonesia : Makalah ini menyajikan sebuah sistem pengembangan kendali fuzzy logic (PetraFuz, Petra Fuzzy Development System yang dikembangkan oleh laboratorium Sistem Kontrol, Jurusan Teknik Elektro, Universitas Kristen Petra Surabaya. Sistem ini terdiri dari perangkat keras sistem mikrokontroler MCS51 dan perangkat lunak pendukung yang berjalan pada PC. Sistem PetraFuz digunakan untuk mengembangkan sistem berbasis fuzzy logic utamanya pada bidang kendali. Kemampuan sistem meliputi pengembangan pada fase perancangan kendali, evaluasi kendali, pembentukan program bahasa assembly MCS51 dan proses downloading program menuju target sistem mikrokontroler MCS51 untuk dieksekusi melakukan kendali pada plant yang nyata. Aksi kendali dapat diakuisi oleh program PC melalui komunikasi serial RS232 sehingga respon kendali dapat digambarkan pada layar monitor untuk dilakukan analisis lebih lanjut yang diperlukan pada proses tuning if-then fuzzy rules

  8. Answer Sets in a Fuzzy Equilibrium Logic

    Science.gov (United States)

    Schockaert, Steven; Janssen, Jeroen; Vermeir, Dirk; de Cock, Martine

    Since its introduction, answer set programming has been generalized in many directions, to cater to the needs of real-world applications. As one of the most general “classical” approaches, answer sets of arbitrary propositional theories can be defined as models in the equilibrium logic of Pearce. Fuzzy answer set programming, on the other hand, extends answer set programming with the capability of modeling continuous systems. In this paper, we combine the expressiveness of both approaches, and define answer sets of arbitrary fuzzy propositional theories as models in a fuzzification of equilibrium logic. We show that the resulting notion of answer set is compatible with existing definitions, when the syntactic restrictions of the corresponding approaches are met. We furthermore locate the complexity of the main reasoning tasks at the second level of the polynomial hierarchy. Finally, as an illustration of its modeling power, we show how fuzzy equilibrium logic can be used to find strong Nash equilibria.

  9. Application of fuzzy logic in multicomponent analysis by optodes.

    Science.gov (United States)

    Wollenweber, M; Polster, J; Becker, T; Schmidt, H L

    1997-01-01

    Fuzzy logic can be a useful tool for the determination of substrate concentrations applying optode arrays in combination with flow injection analysis, UV-VIS spectroscopy and kinetics. The transient diffuse reflectance spectra in the visible wavelength region from four optodes were evaluated to carry out the simultaneous determination of artificial mixtures of ampicillin and penicillin. The discrimination of the samples was achieved by changing the composition of the receptor gel and working pH. Different algorithms of pre-processing were applied on the data to reduce the spectral information to a few analytic-specific variables. These variables were used to develop the fuzzy model. After calibration the model was validated by an independent test data set.

  10. Advanced Concepts in Fuzzy Logic and Systems with Membership Uncertainty

    CERN Document Server

    Starczewski, Janusz T

    2013-01-01

    This book generalizes fuzzy logic systems for different types of uncertainty, including - semantic ambiguity resulting from limited perception or lack of knowledge about exact membership functions - lack of attributes or granularity arising from discretization of real data - imprecise description of membership functions - vagueness perceived as fuzzification of conditional attributes. Consequently, the membership uncertainty can be modeled by combining methods of conventional and type-2 fuzzy logic, rough set theory and possibility theory.            In particular, this book provides a number of formulae for implementing the operation extended on fuzzy-valued fuzzy sets and presents some basic structures of generalized uncertain fuzzy logic systems, as well as introduces several of methods to generate fuzzy membership uncertainty. It is desirable as a reference book for under-graduates in higher education, master and doctor graduates in the courses of computer science, computational intelligence, or...

  11. A real time fuzzy logic power management strategy for a fuel cell vehicle

    International Nuclear Information System (INIS)

    Hemi, Hanane; Ghouili, Jamel; Cheriti, Ahmed

    2014-01-01

    Highlights: • We present a real time fuzzy logic power management strategy. • This strategy is applied to hybrid electric vehicle dynamic model. • Three configurations evaluated during a drive cycle. • The hydrogen consumption is analysed for the three configurations. - Abstract: This paper presents real time fuzzy logic controller (FLC) approach used to design a power management strategy for a hybrid electric vehicle and to protect the battery from overcharging during the repetitive braking energy accumulation. The fuel cell (FC) and battery (B)/supercapacitor (SC) are the primary and secondary power sources, respectively. This paper analyzes and evaluates the performance of the three configurations, FC/B, FC/SC and FC/B/SC during real time driving conditions and unknown driving cycle. The MATLAB/Simulink and SimPowerSystems software packages are used to model the electrical and mechanical elements of hybrid vehicles and implement a fuzzy logic strategy

  12. Intelligent neural network and fuzzy logic control of industrial and power systems

    Science.gov (United States)

    Kuljaca, Ognjen

    The main role played by neural network and fuzzy logic intelligent control algorithms today is to identify and compensate unknown nonlinear system dynamics. There are a number of methods developed, but often the stability analysis of neural network and fuzzy control systems was not provided. This work will meet those problems for the several algorithms. Some more complicated control algorithms included backstepping and adaptive critics will be designed. Nonlinear fuzzy control with nonadaptive fuzzy controllers is also analyzed. An experimental method for determining describing function of SISO fuzzy controller is given. The adaptive neural network tracking controller for an autonomous underwater vehicle is analyzed. A novel stability proof is provided. The implementation of the backstepping neural network controller for the coupled motor drives is described. Analysis and synthesis of adaptive critic neural network control is also provided in the work. Novel tuning laws for the system with action generating neural network and adaptive fuzzy critic are given. Stability proofs are derived for all those control methods. It is shown how these control algorithms and approaches can be used in practical engineering control. Stability proofs are given. Adaptive fuzzy logic control is analyzed. Simulation study is conducted to analyze the behavior of the adaptive fuzzy system on the different environment changes. A novel stability proof for adaptive fuzzy logic systems is given. Also, adaptive elastic fuzzy logic control architecture is described and analyzed. A novel membership function is used for elastic fuzzy logic system. The stability proof is proffered. Adaptive elastic fuzzy logic control is compared with the adaptive nonelastic fuzzy logic control. The work described in this dissertation serves as foundation on which analysis of particular representative industrial systems will be conducted. Also, it gives a good starting point for analysis of learning abilities of

  13. Introduction to type-2 fuzzy logic control theory and applications

    CERN Document Server

    Mendel, Jerry M; Tan, Woei-Wan; Melek, William W; Ying, Hao

    2014-01-01

    Written by world-class leaders in type-2 fuzzy logic control, this book offers a self-contained reference for both researchers and students. The coverage provides both background and an extensive literature survey on fuzzy logic and related type-2 fuzzy control. It also includes research questions, experiment and simulation results, and downloadable computer programs on an associated website. This key resource will prove useful to students and engineers wanting to learn type-2 fuzzy control theory and its applications.

  14. On logical, algebraic, and probabilistic aspects of fuzzy set theory

    CERN Document Server

    Mesiar, Radko

    2016-01-01

    The book is a collection of contributions by leading experts, developed around traditional themes discussed at the annual Linz Seminars on Fuzzy Set Theory. The different chapters have been written by former PhD students, colleagues, co-authors and friends of Peter Klement, a leading researcher and the organizer of the Linz Seminars on Fuzzy Set Theory. The book also includes advanced findings on topics inspired by Klement’s research activities, concerning copulas, measures and integrals, as well as aggregation problems. Some of the chapters reflect personal views and controversial aspects of traditional topics, while others deal with deep mathematical theories, such as the algebraic and logical foundations of fuzzy set theory and fuzzy logic. Originally thought as an homage to Peter Klement, the book also represents an advanced reference guide to the mathematical theories related to fuzzy logic and fuzzy set theory with the potential to stimulate important discussions on new research directions in the fiel...

  15. Fuzzy Logic and Intelligent Technologies in Nuclear Science

    International Nuclear Information System (INIS)

    Da Ruan

    1998-01-01

    FLINS is the acronym for Fuzzy Logic and Intelligent Technologies in Nuclear Science. The main task for FLINS is to solve intricate problems pertaining to the nuclear environment by using modern technologies as additional tools and to bridge the gap between novel technologies and the industrial nuclear world. In 1997, major efforts went to the specific prototyping of Fuzzy Logic Control of SCK-CEN's BR1 research Reactor. Progress and achievements are reported

  16. PENGGUNAAN FUZZY LOGIC UNTUK KONTROL PARALLEL CONVERTER DC-DC

    Directory of Open Access Journals (Sweden)

    Bambang Prio Hartono

    2012-09-01

    Full Text Available Abstract: Using system fuzzy logic as control  technology have been used on low load dc-dc converter with combined parallel compiled  dc-dc converter can  obtain big load.   With existence of differrence of component parameter and each parallel compiled converter can obtained different current  and voltage output.  Function of controller  for to do adjustment, so that current which is applied  to  load by each converter  can be obtained  difference error as small as possible or same. The object of research is developing design of large signal dc-dc converter which is  combined with using  FLC so that  obtain  better performance.  To get better performance have been made plant model and simulation with CDE method.  The more systematic  system and design is needed to overcome bigger load  on dc-dc converter, so that parallel  compiled current master slave control system on dc-dc converter with using fuzzy logic  controller is used. Result of  research showed that error or difference of  current  which is applied to load can handled by fuzzy logic  controller.  Technic of current and voltage controller co to do adjustment current and voltage distribution  equally to load.  Distribution of iL1,iL2 and  output voltage Vo on dc-dc  converter with load 2,25 until  7,875 and voltage  100  until 120 volt,  load current beetwen  12 until 48, % relatif  error  Vo  0,4% until  0,9%.

  17. Wavelet zero crossings and paraconsistent fuzzy logic in the diagnostic of rolling bearings

    Energy Technology Data Exchange (ETDEWEB)

    Masotti, Paulo Henrique Ferraz; Ting, Daniel Kao Sun [Instituto de Pesquisas Energeticas e Nucleares (IPEN), Sao Paulo, SP (Brazil)

    2002-07-01

    A new defect characteristic extraction method for rolling bearings vibration signals based on wavelet transform is presented. A more robust automated diagnostic system for defects in bearings based on paraconsistent fuzzy logic is also presented which deals with inconsistent and ambiguous information. There is a need for the optimization of diagnosis systems in order to increase precision and to reduce human errors. Automatic diagnosis systems should be robust to a point where it must operate with a diversified source of information allowing for analysis of different equipment and existing defects. The paraconsistent fuzzy logic is applied in the present work. This technique is a flexible tool which allows the modeling of uncertain and ambiguous data frequently found in real situations. Experimental data were used to test the methodology. The results obtained by using wavelet zero crossings for characteristic extraction and Paraconsistent fuzzy logic for defect classification were conclusive showing that the system is capable to identify and to classify defects in bearings. (author)

  18. Perancangan Kendali Robot pada Smartphone Menggunakan Sensor Accelerometer Berbasis Metode Fuzzy Logic

    Directory of Open Access Journals (Sweden)

    Mohamad Agung Prawira Negara

    2017-08-01

    Full Text Available Telecommunications and robotics technology is being developed to assist and facilitate the work of a human. In the field of telecommunications particularly smartphone has reached the planting of operating systems like android until planting sensors such as an accelerometer, gyro, proximity, etc. We would like to take advantage of the accelerometer sensor on a smartphone as robot control. We will compare the use of Sugeno Fuzzy Logic and Mamdani Fuzzy Logic to determine the best control method. The basic components of the robot are the Bluetooth module HC-05 as a medium of communication with the android, arduino as the control system and actuators such as DC motors drive the rear wheels to adjust the speed of the robot, and servo motor drives the front wheels to adjust the degree of turn robot. In robot’s movement test, 4 of 8 trials or approximately 50% stated better Sugeno Fuzzy Logic than Mamdani Fuzzy Logic in terms of linearity. In robot's controller response test, for Sugeno Fuzzy Logic method the average delay is 0.41 seconds, and for Mamdani Fuzzy Logic method the average delay is 10.80 seconds.

  19. Implementation of a Fuzzy Logic Speed Controller for a Permanent ...

    African Journals Online (AJOL)

    In this paper DC motor control models were mathematically extracted and implemented using fuzzy logic speed controller. All control systems suffer from problems related to undesirable overshoot, longer settling times and vibrations while going from one state to another. To overcome the maximum overshoot, fuzzy logic ...

  20. Computational intelligence synergies of fuzzy logic, neural networks and evolutionary computing

    CERN Document Server

    Siddique, Nazmul

    2013-01-01

    Computational Intelligence: Synergies of Fuzzy Logic, Neural Networks and Evolutionary Computing presents an introduction to some of the cutting edge technological paradigms under the umbrella of computational intelligence. Computational intelligence schemes are investigated with the development of a suitable framework for fuzzy logic, neural networks and evolutionary computing, neuro-fuzzy systems, evolutionary-fuzzy systems and evolutionary neural systems. Applications to linear and non-linear systems are discussed with examples. Key features: Covers all the aspect

  1. Quantified moving average strategy of crude oil futures market based on fuzzy logic rules and genetic algorithms

    Science.gov (United States)

    Liu, Xiaojia; An, Haizhong; Wang, Lijun; Guan, Qing

    2017-09-01

    The moving average strategy is a technical indicator that can generate trading signals to assist investment. While the trading signals tell the traders timing to buy or sell, the moving average cannot tell the trading volume, which is a crucial factor for investment. This paper proposes a fuzzy moving average strategy, in which the fuzzy logic rule is used to determine the strength of trading signals, i.e., the trading volume. To compose one fuzzy logic rule, we use four types of moving averages, the length of the moving average period, the fuzzy extent, and the recommend value. Ten fuzzy logic rules form a fuzzy set, which generates a rating level that decides the trading volume. In this process, we apply genetic algorithms to identify an optimal fuzzy logic rule set and utilize crude oil futures prices from the New York Mercantile Exchange (NYMEX) as the experiment data. Each experiment is repeated for 20 times. The results show that firstly the fuzzy moving average strategy can obtain a more stable rate of return than the moving average strategies. Secondly, holding amounts series is highly sensitive to price series. Thirdly, simple moving average methods are more efficient. Lastly, the fuzzy extents of extremely low, high, and very high are more popular. These results are helpful in investment decisions.

  2. A modeling of fuzzy logic controller on gamma scanning device

    International Nuclear Information System (INIS)

    Arjoni Amir

    2010-01-01

    Modeling and simulation of controller to set the high position and direction of the source of gamma radiation isotope Co-60 and Nal(TL) detector of gamma scanning device by using fuzzy logic controller FLC have been done. The high positions and in the right direction of gamma radiation and Nal (TI) detector obtained the optimal enumeration. The counting data obtained from gamma scanning device counting system is affected by the instability of high position and direction of the gamma radiation source and Nal(TI) detector or the height and direction are not equal between the gamma radiation source and Nal(TI) detector. Assumed a high position and direction of radiation sources can be fixed while the high position detector h (2, 1,0, -1, -2) can be adjusted up and down and the detector can be changed direction to the left or right angle ω (2, 1 , 0, -1, -2) when the position and direction are no longer aligned with the direction of the source of gamma radiation, the counting results obtained will not be optimal. Movement detector direction towards the left or right and the high detector arranged by the DC motor using fuzzy logic control in order to obtain the amount of output fuzzy logic control which forms the optimal output quantity count. The variation of height difference h between the source position of the gamma radiation detector and change direction with the detector angle ω becomes the input variable membership function (member function) whereas the fuzzy logic for the output variable membership function of fuzzy logic control output is selected scale fuzzy logic is directly proportional to the amount of optimal counting. From the simulation results obtained by the relationship between the amount of data output variable of fuzzy logic controller and the amount of data input variable height h and direction detector ω is depicted in graphical form surface. (author)

  3. Localized and Energy-Efficient Topology Control in Wireless Sensor Networks Using Fuzzy-Logic Control Approaches

    Directory of Open Access Journals (Sweden)

    Yuanjiang Huang

    2014-01-01

    Full Text Available The sensor nodes in the Wireless Sensor Networks (WSNs are prone to failures due to many reasons, for example, running out of battery or harsh environment deployment; therefore, the WSNs are expected to be able to maintain network connectivity and tolerate certain amount of node failures. By applying fuzzy-logic approach to control the network topology, this paper aims at improving the network connectivity and fault-tolerant capability in response to node failures, while taking into account that the control approach has to be localized and energy efficient. Two fuzzy controllers are proposed in this paper: one is Learning-based Fuzzy-logic Topology Control (LFTC, of which the fuzzy controller is learnt from a training data set; another one is Rules-based Fuzzy-logic Topology Control (RFTC, of which the fuzzy controller is obtained through designing if-then rules and membership functions. Both LFTC and RFTC do not rely on location information, and they are localized. Comparing them with other three representative algorithms (LTRT, List-based, and NONE through extensive simulations, our two proposed fuzzy controllers have been proved to be very energy efficient to achieve desired node degree and improve the network connectivity when sensor nodes run out of battery or are subject to random attacks.

  4. On Witnessed Models in Fuzzy Logic III - Witnessed Gödel Logics

    Czech Academy of Sciences Publication Activity Database

    Hájek, Petr

    2010-01-01

    Roč. 56, č. 2 (2010), s. 171-174 ISSN 0942-5616 R&D Projects: GA MŠk(CZ) 1M0545 Institutional research plan: CEZ:AV0Z10300504 Keywords : mathematical fuzzy logic * Gödel logic * witnessed models * arithmetical complexity Subject RIV: BA - General Mathematics Impact factor: 0.361, year: 2010

  5. On the Difference between Traditional and Deductive Fuzzy Logic

    Czech Academy of Sciences Publication Activity Database

    Běhounek, Libor

    2008-01-01

    Roč. 159, č. 10 (2008), s. 1153-1164 ISSN 0165-0114 R&D Projects: GA AV ČR KJB100300502 Institutional research plan: CEZ:AV0Z10300504 Keywords : deductive fuzzy logic * fuzzy elements * gradual sets * entropy of fuzzy sets * aggregation * membership degrees * methodology of fuzzy mathematics Subject RIV: BA - General Mathematics Impact factor: 1.833, year: 2008

  6. Fuzzy logic controller for weaning neonates from mechanical ventilation.

    Science.gov (United States)

    Hatzakis, G E; Davis, G M

    2002-01-01

    Weaning from mechanical ventilation is the gradual detachment from any ventilatory support till normal spontaneous breathing can be fully resumed. To date, we have developed a fuzzy logic controller for weaning COPD adults using pressure support ventilation (PS). However, adults and newborns differ in the pathophysiology of lung disease. We therefore used our fuzzy logic-based weaning platform to develop modularized components for weaning newborns with lung disease. Our controller uses the heart rate (HR), respiratory rate (RR), tidal volume (VT) and oxygen saturation (SaO2) and their trends deltaHR/deltat, deltaVT/deltat and deltaSaO2/deltat to evaluate, respectively, the Current and Trend weaning status of the newborn. Through appropriate fuzzification of these vital signs, Current and Trend weaning status can quantitatively determine the increase/decrease in the synchronized intermittent mandatory ventilation (SIMV) setting. The post-operative weaning courses of 10 newborns, 82+/-162 days old, were assessed at 2-hour intervals for 68+/-39 days. The SIMV levels, proposed by our algorithm, were matched to those levels actually applied. For 60% of the time both values coincided. For the remaining 40%, our algorithm suggested lower SIMV support than what was applied. The Area Under the Curve for integrated ventilatory support over time was 1203+/-846 for standard ventilatory strategies and 1152+/-802 for fuzzy controller. This suggests that the algorithm, approximates the actual weaning progression, and may advocate a more aggressive strategy. Moreover, the core of the fuzzy controller facilitates adaptation for body size and diversified disease patterns and sets the premises as an infant-weaning tool.

  7. Fuzzy logic system for BBT based fertility prediction | Yazed | Journal ...

    African Journals Online (AJOL)

    ... been obtained with the accuracy of 95 % and 80 respectively. Besides, this prediction system using fuzzy logic could improve the current practice in the FAM technique by integrating it with an Internet of Things (IoT) technology for automatic BBT charting and monitoring. Keywords: family planning; fertility; BBT; fuzzy logic.

  8. Towards rational closure for fuzzy logic: The case of propositional Godel logic

    CSIR Research Space (South Africa)

    Casini, G

    2013-12-01

    Full Text Available In the field of non-monotonic logics, the notion of rational closure is acknowledged as a landmark and we are going to see whether such a construction can be adopted in the context of mathematical fuzzy logic, a so far (apparently) unexplored...

  9. Control of beam halo-chaos using fuzzy logic controller

    International Nuclear Information System (INIS)

    Gao Yuan; Yuan Haiying; Tan Guangxing; Luo Wenguang

    2012-01-01

    Considering the ion beam with initial K-V distribution in the periodic focusing magnetic filed channels (PFCs) as a typical sample, a fuzzy control method for control- ling beam halo-chaos was studied. A fuzzy proportional controller, using output of fuzzy inference as a control factor, was presented for adjusting exterior focusing magnetic field. The stability of controlled system was proved by fuzzy phase plane analysis. The simulation results demonstrate that the chaotic radius of envelope can be controlled to the matched radius via controlling magnetic field. This method was also applied to the multi-particle model. Under the control condition, the beam halos and its regeneration can be eliminated effectively, and that both the compactness and the uniformity of ion beam are improved evidently. Since the exterior magnetic field can be rather easily adjusted by proportional control and the fuzzy logic controller is independent to the mathematical model, this method has adaptive ability and is easily realized in experiment. The research offers a valuable reference for the design of the PFCs in the high- current linear ion accelerators. (authors)

  10. Fuzzy Logic Temperature Control System For The Induction Furnace

    Directory of Open Access Journals (Sweden)

    Lei Lei Hnin

    2015-08-01

    Full Text Available This research paper describes the fuzzy logic temperature control system of the induction furnace. Temperature requirement of the heating system varies during the heating process. In the conventional control schemes the switching losses increase with the change in the load. A closed loop control is required to have a smooth control on the system. In this system pulse width modulation based power control scheme for the induction heating system is developed using the fuzzy logic controller. The induction furnace requires a good voltage regulation to have efficient response. The controller controls the temperature depending upon weight of meat water and time. This control system is implemented in hardware system using microcontroller. Here the fuzzy logic controller is designed and simulated in MATLAB to get the desire condition.

  11. Nuclear reactor control with fuzzy logic approaches - strengths, weakness, opportunities, and threats

    International Nuclear Information System (INIS)

    Ruan, Da

    2004-01-01

    As part of the special track on 'Lessons learned from computational intelligence in nuclear applications' at the forthcoming FLINS 2004 conference on Applied Computational Intelligence (Blankenberge, Belgium, September 1-3, 2004), research experiences on fuzzy logic techniques in applications of nuclear reactor control operation are critically reviewed in this presentation. Assessment of four real fuzzy control applications at the MIT research reactor in the US, the FUGEN heavy water reactor in Japan, the BR1 research reactor in Belgium, and a TRIGA Mark III reactor in Mexico will be examined thought a SWOT analysis (strengths, weakness, opportunities, and threats). Special attention will be paid to the current cooperation between the Belgian Nuclear Research Centre (SCK-CEN) and the Mexican Nuclear Centre (ININ) on the fuzzy logic control for nuclear reactor control project under the partial support of the National Council for Science and Technology of Mexico (CONACYT). (Author)

  12. Fuzzy logic control of water level in advanced boiling water reactor

    International Nuclear Information System (INIS)

    Lin, Chaung; Lee, Chi-Szu; Raghavan, R.; Fahrner, D.M.

    1995-01-01

    The feedwater control system in the Advanced Boiling Water Reactor (ABWR) is more challenging to design compared to other control systems in the plant, due to the possible change in level from void collapses and swells during transient events. A basic fuzzy logic controller is developed using a simplified ABWR mathematical model to demonstrate and compare the performance of this controller with a simplified conventional controller. To reduce the design effort, methods are developed to automatically tune the scaling factors and control rules. As a first step in developing the fuzzy controller, a fuzzy controller with a limited number of rules is developed to respond to normal plant transients such as setpoint changes of plant parameters and load demand changes. Various simulations for setpoint and load demand changes of plant performances were conducted to evaluate the modeled fuzzy logic design against the simplified ABWR model control system. The simulation results show that the performance of the fuzzy logic controller is comparable to that of the Proportional-Integral (PI) controller, However, the fuzzy logic controller produced shorter settling time for step setpoint changes compared to the simplified conventional controller

  13. Hybrid fuzzy logic control of laser surface heat treatments

    International Nuclear Information System (INIS)

    Perez, Jose Antonio; Ocana, Jose Luis; Molpeceres, Carlos

    2007-01-01

    This paper presents an advanced hybrid fuzzy logic control system for laser surface heat treatments, which allows to increase significantly the uniformity and final quality of the obtained product, reducing the rejection rate and increasing the productivity and efficiency of the treatment. Basically, the proposed hybrid control structure combines a fuzzy logic controller, with a pure integral action, both fully decoupled, improving the performances of the process with a reasonable design cost, since the system nonlinearities are fully compensated by the fuzzy component of the controller, while the integral action contributes to eliminate the steady-state error

  14. Fuzzy logic control for camera tracking system

    Science.gov (United States)

    Lea, Robert N.; Fritz, R. H.; Giarratano, J.; Jani, Yashvant

    1992-01-01

    A concept utilizing fuzzy theory has been developed for a camera tracking system to provide support for proximity operations and traffic management around the Space Station Freedom. Fuzzy sets and fuzzy logic based reasoning are used in a control system which utilizes images from a camera and generates required pan and tilt commands to track and maintain a moving target in the camera's field of view. This control system can be implemented on a fuzzy chip to provide an intelligent sensor for autonomous operations. Capabilities of the control system can be expanded to include approach, handover to other sensors, caution and warning messages.

  15. Spatial analysis of groundwater levels using Fuzzy Logic and geostatistical tools

    Science.gov (United States)

    Theodoridou, P. G.; Varouchakis, E. A.; Karatzas, G. P.

    2017-12-01

    The spatial variability evaluation of the water table of an aquifer provides useful information in water resources management plans. Geostatistical methods are often employed to map the free surface of an aquifer. In geostatistical analysis using Kriging techniques the selection of the optimal variogram is very important for the optimal method performance. This work compares three different criteria to assess the theoretical variogram that fits to the experimental one: the Least Squares Sum method, the Akaike Information Criterion and the Cressie's Indicator. Moreover, variable distance metrics such as the Euclidean, Minkowski, Manhattan, Canberra and Bray-Curtis are applied to calculate the distance between the observation and the prediction points, that affects both the variogram calculation and the Kriging estimator. A Fuzzy Logic System is then applied to define the appropriate neighbors for each estimation point used in the Kriging algorithm. The two criteria used during the Fuzzy Logic process are the distance between observation and estimation points and the groundwater level value at each observation point. The proposed techniques are applied to a data set of 250 hydraulic head measurements distributed over an alluvial aquifer. The analysis showed that the Power-law variogram model and Manhattan distance metric within ordinary kriging provide the best results when the comprehensive geostatistical analysis process is applied. On the other hand, the Fuzzy Logic approach leads to a Gaussian variogram model and significantly improves the estimation performance. The two different variogram models can be explained in terms of a fractional Brownian motion approach and of aquifer behavior at local scale. Finally, maps of hydraulic head spatial variability and of predictions uncertainty are constructed for the area with the two different approaches comparing their advantages and drawbacks.

  16. Fuzzy logic electric vehicle regenerative antiskid braking and traction control system

    Science.gov (United States)

    Cikanek, Susan R.

    1994-01-01

    An regenerative antiskid braking and traction control system using fuzzy logic for an electric or hybrid vehicle having a regenerative braking system operatively connected to an electric traction motor, and a separate hydraulic braking system includes sensors for monitoring present vehicle parameters and a processor, responsive to the sensors, for calculating vehicle parameters defining the vehicle behavior not directly measurable by the sensor and determining if regenerative antiskid braking control, requiring hydraulic braking control, and requiring traction control are required. The processor then employs fuzzy logic based on the determined vehicle state and provides command signals to a motor controller to control operation of the electric traction motor and to the brake controller to control fluid pressure applied at each vehicle wheel to provide the appropriate regenerative braking control, hydraulic braking control, and traction control.

  17. Virtual reality simulation of fuzzy-logic control during underwater dynamic positioning

    Science.gov (United States)

    Thekkedan, Midhin Das; Chin, Cheng Siong; Woo, Wai Lok

    2015-03-01

    In this paper, graphical-user-interface (GUI) software for simulation and fuzzy-logic control of a remotely operated vehicle (ROV) using MATLAB™ GUI Designing Environment is proposed. The proposed ROV's GUI platform allows the controller such as fuzzy-logic control systems design to be compared with other controllers such as proportional-integral-derivative (PID) and sliding-mode controller (SMC) systematically and interactively. External disturbance such as sea current can be added to improve the modelling in actual underwater environment. The simulated results showed the position responses of the fuzzy-logic control exhibit reasonable performance under the sea current disturbance.

  18. Fuzzy logic based ELF magnetic field estimation in substations

    International Nuclear Information System (INIS)

    Kosalay, I.

    2008-01-01

    This paper examines estimation of the extremely low frequency magnetic fields (MF) in the power substation. First, the results of the previous relevant research studies and the MF measurements in a sample power substation are presented. Then, a fuzzy logic model based on the geometric definitions in order to estimate the MF distribution is explained. Visual software, which has a three-dimensional screening unit, based on the fuzzy logic technique, has been developed. (authors)

  19. Fuzzy logic controller for weaning neonates from mechanical ventilation.

    OpenAIRE

    Hatzakis, G. E.; Davis, G. M.

    2002-01-01

    Weaning from mechanical ventilation is the gradual detachment from any ventilatory support till normal spontaneous breathing can be fully resumed. To date, we have developed a fuzzy logic controller for weaning COPD adults using pressure support ventilation (PS). However, adults and newborns differ in the pathophysiology of lung disease. We therefore used our fuzzy logic-based weaning platform to develop modularized components for weaning newborns with lung disease. Our controller uses the he...

  20. use of fuzzy logic to investigate weather parameter impact

    African Journals Online (AJOL)

    user

    2016-07-03

    Jul 3, 2016 ... developed in the Simulink environment of a MATLAB software. The model ... smoothing, stochastic process, ARMA (autoregressive integrated moving .... 2.3 Building of Fuzzy Logic Simulation Model. The fuzzy model is ...

  1. Stock and option portfolio using fuzzy logic approach

    Science.gov (United States)

    Sumarti, Novriana; Wahyudi, Nanang

    2014-03-01

    Fuzzy Logic in decision-making process has been widely implemented in various problems in industries. It is the theory of imprecision and uncertainty that was not based on probability theory. Fuzzy Logic adds values of degree between absolute true and absolute false. It starts with and builds on a set of human language rules supplied by the user. The fuzzy systems convert these rules to their mathematical equivalents. This could simplify the job of the system designer and the computer, and results in much more accurate representations of the way systems behave in the real world. In this paper we examine the decision making process of stock and option trading by the usage of MACD (Moving Average Convergence Divergence) technical analysis and Option Pricing with Fuzzy Logic approach. MACD technical analysis is for the prediction of the trends of underlying stock prices, such as bearish (going downward), bullish (going upward), and sideways. By using Fuzzy C-Means technique and Mamdani Fuzzy Inference System, we define the decision output where the value of MACD is high then decision is "Strong Sell", and the value of MACD is Low then the decision is "Strong Buy". We also implement the fuzzification of the Black-Scholes option-pricing formula. The stock and options methods are implemented on a portfolio of one stock and its options. Even though the values of input data, such as interest rates, stock price and its volatility, cannot be obtain accurately, these fuzzy methods can give a belief degree of the calculated the Black-Scholes formula so we can make the decision on option trading. The results show the good capability of the methods in the prediction of stock price trends. The performance of the simulated portfolio for a particular period of time also shows good return.

  2. Fuzzy logic controllers and chaotic natural convection loops

    International Nuclear Information System (INIS)

    Theler, German

    2007-01-01

    The study of natural circulation loops is a subject of special concern for the engineering design of advanced nuclear reactors, as natural convection provides an efficient and completely passive heat removal system. However, under certain circumstances thermal-fluid-dynamical instabilities may appear, threatening the reactor safety as a whole.On the other hand, fuzzy logic controllers provide an ideal framework to approach highly non-linear control problems. In the present work, we develop a software-based fuzzy logic controller and study its application to chaotic natural convection loops.We numerically analyse the linguistic control of the loop known as the Welander problem in such conditions that, if the controller were not present, the circulation flow would be non-periodic unstable.We also design a Taka gi-Sugeno fuzzy controller based on a fuzzy model of a natural convection loop with a toroidal geometry, in order to stabilize a Lorenz-chaotic behaviour.Finally, we show experimental results obtained in a rectangular natural circulation loop [es

  3. Fuzzy logic based power-efficient real-time multi-core system

    CERN Document Server

    Ahmed, Jameel; Najam, Shaheryar; Najam, Zohaib

    2017-01-01

    This book focuses on identifying the performance challenges involved in computer architectures, optimal configuration settings and analysing their impact on the performance of multi-core architectures. Proposing a power and throughput-aware fuzzy-logic-based reconfiguration for Multi-Processor Systems on Chip (MPSoCs) in both simulation and real-time environments, it is divided into two major parts. The first part deals with the simulation-based power and throughput-aware fuzzy logic reconfiguration for multi-core architectures, presenting the results of a detailed analysis on the factors impacting the power consumption and performance of MPSoCs. In turn, the second part highlights the real-time implementation of fuzzy-logic-based power-efficient reconfigurable multi-core architectures for Intel and Leone3 processors. .

  4. Implementation of Fuzzy Logic Based Temperature-Controlled Heat ...

    African Journals Online (AJOL)

    This research then compares the control performance of PID (Proportional Integral and Derivative) and Fuzzy logic controllers. Conclusions are made based on these control performances. The results show that the control performance for a Fuzzy controller is quite similar to PID controller but comparatively gives a better ...

  5. FUZZY LOGIC CONTROL OF ELECTRIC MOTORS AND MOTOR DRIVES: FEASIBILITY STUDY

    Science.gov (United States)

    The report gives results of a study (part 1) of fuzzy logic motor control (FLMC). The study included: 1) reviews of existing applications of fuzzy logic, of motor operation, and of motor control; 2) a description of motor control schemes that can utilize FLMC; 3) selection of a m...

  6. Fuzzy Logic and Intelligent Technologies in Nuclear Science (FLINS)

    International Nuclear Information System (INIS)

    Da Ruan

    2000-01-01

    FLINS is the acronym for Fuzzy Logic and Intelligent Technologies in Nuclear Science. In 1994, SCK-CEN launched a programme on FLINS. The first FLINS project dealt with the specific prototyping of fuzzy logic control (FLC) of the BR-1 research reactor. This project focussed on controlling the power level of the BR1 reactor added value of FLC for both safety and economic aspects for a nuclear reactor control operation. Main achievements in 1999 are reported

  7. Development of a fuzzy logic method to build objective functions in optimization problems: application to BWR fuel lattice design

    International Nuclear Information System (INIS)

    Martin-del-Campo, C.; Francois, J.L.; Barragan, A.M.; Palomera, M.A.

    2005-01-01

    In this paper we develop a methodology based on the use of the Fuzzy Logic technique to build multi-objective functions to be used in optimization processes applied to in-core nuclear fuel management. As an example, we selected the problem of determining optimal radial fuel enrichment and gadolinia distributions in a typical 'Boiling Water Reactor (BWR)' fuel lattice. The methodology is based on the use of the mathematical capability of Fuzzy Logic to model nonlinear functions of arbitrary complexity. The utility of Fuzzy Logic is to map an input space into an output space, and the primary mechanism for doing this is a list of if-then statements called rules. The rules refer to variables and adjectives that describe those variables and, the Fuzzy Logic technique interprets the values in the input vectors and, based on the set of rules assigns values to the output vector. The methodology was developed for the radial optimization of a BWR lattice where the optimization algorithm employed is Tabu Search. The global objective is to find the optimal distribution of enrichments and burnable poison concentrations in a 10*10 BWR lattice. In order to do that, a fuzzy control inference system was developed using the Fuzzy Logic Toolbox of Matlab and it has been linked to the Tabu Search optimization process. Results show that Tabu Search combined with Fuzzy Logic performs very well, obtaining lattices with optimal fuel utilization. (authors)

  8. Indoor signal attenuation assessment via fuzzy logic

    Directory of Open Access Journals (Sweden)

    Alexandre de Assis Mota

    2011-09-01

    Full Text Available This work focuses on the analysis of signal´s attenuation in indoor environments using a fuzzy logic approach based on the Shadowing Signal Propagation Model (SSPM. The SSPM allows the characterization of the attenuation caused by the environment through the ? parameter present in this model. In addition to this, the Fuzzy Logic provides a form of approximate reasoning that allows the treatment of problems with incomplete, vague and imprecise information. Also, it offers a simple way to obtain a possible solution for a problem using the heuristic knowledge about a particular situation. The results show that the methodology produced satisfactory results, close to the ones yielded by experimental methods.

  9. Neural-Network-Based Fuzzy Logic Navigation Control for Intelligent Vehicles

    Directory of Open Access Journals (Sweden)

    Ahcene Farah

    2002-06-01

    Full Text Available This paper proposes a Neural-Network-Based Fuzzy logic system for navigation control of intelligent vehicles. First, the use of Neural Networks and Fuzzy Logic to provide intelligent vehicles  with more autonomy and intelligence is discussed. Second, the system  for the obstacle avoidance behavior is developed. Fuzzy Logic improves Neural Networks (NN obstacle avoidance approach by handling imprecision and rule-based approximate reasoning. This system must make the vehicle able, after supervised learning, to achieve two tasks: 1- to make one’s way towards its target by a NN, and 2- to avoid static or dynamic obstacles by a Fuzzy NN capturing the behavior of a human expert. Afterwards, two association phases between each task and the appropriate actions are carried out by Trial and Error learning and their coordination allows to decide the appropriate action. Finally, the simulation results display the generalization and adaptation abilities of the system by testing it in new unexplored environments.

  10. Fuzzy logic and neural networks in artificial intelligence and pattern recognition

    Science.gov (United States)

    Sanchez, Elie

    1991-10-01

    With the use of fuzzy logic techniques, neural computing can be integrated in symbolic reasoning to solve complex real world problems. In fact, artificial neural networks, expert systems, and fuzzy logic systems, in the context of approximate reasoning, share common features and techniques. A model of Fuzzy Connectionist Expert System is introduced, in which an artificial neural network is designed to construct the knowledge base of an expert system from, training examples (this model can also be used for specifications of rules in fuzzy logic control). Two types of weights are associated with the synaptic connections in an AND-OR structure: primary linguistic weights, interpreted as labels of fuzzy sets, and secondary numerical weights. Cell activation is computed through min-max fuzzy equations of the weights. Learning consists in finding the (numerical) weights and the network topology. This feedforward network is described and first illustrated in a biomedical application (medical diagnosis assistance from inflammatory-syndromes/proteins profiles). Then, it is shown how this methodology can be utilized for handwritten pattern recognition (characters play the role of diagnoses): in a fuzzy neuron describing a number for example, the linguistic weights represent fuzzy sets on cross-detecting lines and the numerical weights reflect the importance (or weakness) of connections between cross-detecting lines and characters.

  11. Fuzzy-logic based strategy for validation of multiplex methods: example with qualitative GMO assays.

    Science.gov (United States)

    Bellocchi, Gianni; Bertholet, Vincent; Hamels, Sandrine; Moens, W; Remacle, José; Van den Eede, Guy

    2010-02-01

    This paper illustrates the advantages that a fuzzy-based aggregation method could bring into the validation of a multiplex method for GMO detection (DualChip GMO kit, Eppendorf). Guidelines for validation of chemical, bio-chemical, pharmaceutical and genetic methods have been developed and ad hoc validation statistics are available and routinely used, for in-house and inter-laboratory testing, and decision-making. Fuzzy logic allows summarising the information obtained by independent validation statistics into one synthetic indicator of overall method performance. The microarray technology, introduced for simultaneous identification of multiple GMOs, poses specific validation issues (patterns of performance for a variety of GMOs at different concentrations). A fuzzy-based indicator for overall evaluation is illustrated in this paper, and applied to validation data for different genetically modified elements. Remarks were drawn on the analytical results. The fuzzy-logic based rules were shown to be applicable to improve interpretation of results and facilitate overall evaluation of the multiplex method.

  12. Fuzzy logic electric vehicle regenerative antiskid braking and traction control system

    Science.gov (United States)

    Cikanek, S.R.

    1994-10-25

    An regenerative antiskid braking and traction control system using fuzzy logic for an electric or hybrid vehicle having a regenerative braking system operatively connected to an electric traction motor, and a separate hydraulic braking system includes sensors for monitoring present vehicle parameters and a processor, responsive to the sensors, for calculating vehicle parameters defining the vehicle behavior not directly measurable by the sensor and determining if regenerative antiskid braking control, requiring hydraulic braking control, and requiring traction control are required. The processor then employs fuzzy logic based on the determined vehicle state and provides command signals to a motor controller to control operation of the electric traction motor and to the brake controller to control fluid pressure applied at each vehicle wheel to provide the appropriate regenerative braking control, hydraulic braking control, and traction control. 123 figs.

  13. Optimization of the Fermentation Process in a Brewery with a Fuzzy Logic Controller

    Directory of Open Access Journals (Sweden)

    Philip B. OSOFISAN

    2007-08-01

    Full Text Available In this research work, the fermentation process in a Brewery will be optimized, with the application of Fuzzy Logic Controller (FLC. Fermentation is controlled by regulating the temperature, the oxygen content and the pitch rate; but the temperature plays a dominant role in the optimization of the fermentation process. For our case study (Guinness Nigeria Plc the optimal fermentation temperature is 16ºC, so the FLC has been designed to maintain this temperature. The designed FLC can also be applied to maintain any other optimal fermentation temperature e.g. 20ºC. These two cases have been investigated. The FLC has been stimulated on a digital computer using MATLAB 5.0 Fuzzy Logic Tool Box.

  14. Use of fuzzy logic in signal processing and validation

    International Nuclear Information System (INIS)

    Heger, A.S.; Alang-Rashid, N.K.; Holbert, K.E.

    1993-01-01

    The advent of fuzzy logic technology has afforded another opportunity to reexamine the signal processing and validation process (SPV). The features offered by fuzzy logic can lend themselves to a more reliable and perhaps fault-tolerant approach to SPV. This is particularly attractive to complex system operations, where optimal control for safe operation depends on reliable input data. The reason for the use of fuzzy logic as the tool for SPV is its ability to transform information from the linguistic domain to a mathematical domain for processing and then transformation of its result back into the linguistic domain for presentation. To ensure the safe and optimal operation of a nuclear plant, for example, reliable and valid data must be available to the human and computer operators. Based on these input data, the operators determine the current state of the power plant and project corrective actions for future states. This determination is based on available data and the conceptual and mathematical models for the plant. A fault-tolerant SPV based on fuzzy logic can help the operators meet the objective of effective, efficient, and safe operation of the nuclear power plant. The ultimate product of this project will be a code that will assist plant operators in making informed decisions under uncertain conditions when conflicting signals may be present

  15. Fuzzy logic based variable speed wind generation system

    Energy Technology Data Exchange (ETDEWEB)

    Simoes, M.G. [Sao Paulo Univ., SP (Brazil). Escola Politecnica. PMC - Mecatronica; Bose, B.K. [Tennessee Univ., Knoxville, TN (United States). Dept. of Electrical Engineering; Spiegel, Ronal J. [Environmental Protection Agency, Research Triangle Park, NC (United States). Air and Energy Engineering Research Lab.

    1996-12-31

    This work demonstrates the successful application of fuzzy logic to enhance the performance and control of a variable speed wind generation system. A maximum power point tracker control is performed with three fuzzy controllers, without wind velocity measurement, and robust to wind vortex and turbine torque ripple. A squirrel cage induction generator feeds the power to a double-sided PWM converter system which pumps the power to a utility grid or supplies to an autonomous system. The fuzzy logic controller FLC-1 searches on-line the generator speed so that the aerodynamic efficiency of the wind turbine is optimized. A second fuzzy controller FLC-2 programs the machine flux by on-line search so as to optimize the machine-converter system wind vortex. Detailed analysis and simulation studies were performed for development of the control strategy and fuzzy algorithms, and a DSP TMS320C30 based hardware with C control software was built for the performance evaluation of a laboratory experimental set-up. The theoretical development was fully validated and the system is ready to be reproduced in a higher power installation. (author) 7 refs., 3 figs., 1 tab.

  16. Fuzzy logic approach for energetic and economic evaluation of hydroelectric projects

    International Nuclear Information System (INIS)

    Iliev, Atanas M.

    2003-01-01

    A mathematical model for energetic and economic evaluation of hydroelectric projects is developed. The main advantage of the proposed methodology is that the model considers uncertainty and vagueness which appears during the decision making process. Due to modeling of variables that are non statistical in their character, fuzzy logic approach is fully incorporated in the model. The first step in energetic evaluation of the hydro power projects is determination of the characteristic of the efficiency of the units to be installed in hydro power plants. For this purpose the model which uses the best characteristics of Artificial Network Fuzzy Inference System (ANFIS) is applied. The method is tested on real systems: HPP Tikves- the power plant in operation and HPP Kozjak - the power plant in construction. The results obtained from practical implementation show that the proposed approach gives superior results than classical polynomial approximation. The model for determining the consumption characteristic of hydro power plant is developed by Sugeno Fuzzy Logic System with polynomials in the consequent part of the rules. Model takes into account the variable gross head of HPP, as well as, the number of units which will be in operation for given output. Modeling of the gross head and power output are performed by expert's design membership functions. This model is practically applied on HPP Tikves for determination of the consumption characteristic for several gross head. The plausible yearly production of electricity from hydro power project, which is important for estimation of the benefit from the project, is calculated by mixed fuzzy-statistical model. hi this approach fuzzy set of the inflow is constructed according to the statistical parameters. The calculation of the production of electricity is realized for a several hydrological conditions which are described by linguistic variables. Finally, Mamdani Fuzzy Inference System with fuzzy number in consequent part

  17. Fuzzy logic applied to the control of the energy consumption in intelligent buildings; Logica fuzzy aplicada ao controle do consumo de energia eletrica em edificios inteligentes

    Energy Technology Data Exchange (ETDEWEB)

    Costa, Herbert R. do N.

    1998-02-01

    This work shows a study on the using of fuzzy control algorithms for the energy optimization of a standard building. The simulation of this type of control was performed using a central conditioned air model and the fuzzy control architecture already used in various control projects. This situation allowed a comparative study among the the control algorithms normally used in conditioned air installations, and the control performed through the building automation system, using an algorithm based on fuzzy logic.

  18. Systematic methods for the design of a class of fuzzy logic controllers

    Science.gov (United States)

    Yasin, Saad Yaser

    2002-09-01

    Fuzzy logic control, a relatively new branch of control, can be used effectively whenever conventional control techniques become inapplicable or impractical. Various attempts have been made to create a generalized fuzzy control system and to formulate an analytically based fuzzy control law. In this study, two methods, the left and right parameterization method and the normalized spline-base membership function method, were utilized for formulating analytical fuzzy control laws in important practical control applications. The first model was used to design an idle speed controller, while the second was used to control an inverted control problem. The results of both showed that a fuzzy logic control system based on the developed models could be used effectively to control highly nonlinear and complex systems. This study also investigated the application of fuzzy control in areas not fully utilizing fuzzy logic control. Three important practical applications pertaining to the automotive industries were studied. The first automotive-related application was the idle speed of spark ignition engines, using two fuzzy control methods: (1) left and right parameterization, and (2) fuzzy clustering techniques and experimental data. The simulation and experimental results showed that a conventional controller-like performance fuzzy controller could be designed based only on experimental data and intuitive knowledge of the system. In the second application, the automotive cruise control problem, a fuzzy control model was developed using parameters adaptive Proportional plus Integral plus Derivative (PID)-type fuzzy logic controller. Results were comparable to those using linearized conventional PID and linear quadratic regulator (LQR) controllers and, in certain cases and conditions, the developed controller outperformed the conventional PID and LQR controllers. The third application involved the air/fuel ratio control problem, using fuzzy clustering techniques, experimental

  19. Fuzzy Logic Approach to Diagnosis of Feedwater Heater Performance Degradation

    International Nuclear Information System (INIS)

    Kang, Yeon Kwan; Kim, Hyeon Min; Heo, Gyun Young; Sang, Seok Yoon

    2014-01-01

    Since failure in, damage to, and performance degradation of power generation components in operation under harsh environment of high pressure and high temperature may cause both economic and human loss at power plants, highly reliable operation and control of these components are necessary. Therefore, a systematic method of diagnosing the condition of these components in its early stages is required. There have been many researches related to the diagnosis of these components, but our group developed an approach using a regression model and diagnosis table, specializing in diagnosis relating to thermal efficiency degradation of power plant. However, there was a difficulty in applying the method using the regression model to power plants with different operating conditions because the model was sensitive to value. In case of the method that uses diagnosis table, it was difficult to find the level at which each performance degradation factor had an effect on the components. Therefore, fuzzy logic was introduced in order to diagnose performance degradation using both qualitative and quantitative results obtained from the components' operation data. The model makes performance degradation assessment using various performance degradation variables according to the input rule constructed based on fuzzy logic. The purpose of the model is to help the operator diagnose performance degradation of components of power plants. This paper makes an analysis of power plant feedwater heater by using fuzzy logic. Feedwater heater is one of the core components that regulate life-cycle of a power plant. Performance degradation has a direct effect on power generation efficiency. It is not easy to observe performance degradation of feedwater heater. However, on the other hand, troubles such as tube leakage may bring simultaneous damage to the tube bundle and therefore it is the object of concern in economic aspect. This study explains the process of diagnosing and verifying typical

  20. Fuzzy Logic Approach to Diagnosis of Feedwater Heater Performance Degradation

    Energy Technology Data Exchange (ETDEWEB)

    Kang, Yeon Kwan; Kim, Hyeon Min; Heo, Gyun Young [Kyung Hee University, Yongin (Korea, Republic of); Sang, Seok Yoon [Engineering and Technical Center, Korea Hydro, Daejeon (Korea, Republic of)

    2014-08-15

    Since failure in, damage to, and performance degradation of power generation components in operation under harsh environment of high pressure and high temperature may cause both economic and human loss at power plants, highly reliable operation and control of these components are necessary. Therefore, a systematic method of diagnosing the condition of these components in its early stages is required. There have been many researches related to the diagnosis of these components, but our group developed an approach using a regression model and diagnosis table, specializing in diagnosis relating to thermal efficiency degradation of power plant. However, there was a difficulty in applying the method using the regression model to power plants with different operating conditions because the model was sensitive to value. In case of the method that uses diagnosis table, it was difficult to find the level at which each performance degradation factor had an effect on the components. Therefore, fuzzy logic was introduced in order to diagnose performance degradation using both qualitative and quantitative results obtained from the components' operation data. The model makes performance degradation assessment using various performance degradation variables according to the input rule constructed based on fuzzy logic. The purpose of the model is to help the operator diagnose performance degradation of components of power plants. This paper makes an analysis of power plant feedwater heater by using fuzzy logic. Feedwater heater is one of the core components that regulate life-cycle of a power plant. Performance degradation has a direct effect on power generation efficiency. It is not easy to observe performance degradation of feedwater heater. However, on the other hand, troubles such as tube leakage may bring simultaneous damage to the tube bundle and therefore it is the object of concern in economic aspect. This study explains the process of diagnosing and verifying typical

  1. CONTROL SYSTEM DESIGN WITH FUZZY LOGIC PID-СONTROLLER TYPE 2

    Directory of Open Access Journals (Sweden)

    A. Tунік

    2011-04-01

    Full Text Available This paper presents a fuzzy logic PID-controller synthesis method for solid body guidance. Formany nonlinear systems with nonlinearities and uncertainties, the performance of fuzzy controllertype 1 may not be satisfactory. Therefore, in this work, fuzzy logic type 2 controller design isintroduced. These controllers capture the advantage of a linear controller in terms of simplicity andalso can handle nonlinearity because of their inference mechanism.The main feature of the proposedmethod constitutes in a membership functions type 2 applications. The membership function type 2is represented by upper and lower membership functions of type 1. The interval between these twofunctions represent the footprint of uncertainty, which give an opportunity to synthesize commonregulator for set of a models. The structure of fuzzy logic controller for solid body control isgrounded. Simulation results confirm the effectiveness of the proposed approach.

  2. Fuzzy logic-based advanced on–off control for thermal comfort in residential buildings

    International Nuclear Information System (INIS)

    Kang, Chang-Soon; Hyun, Chang-Ho; Park, Mignon

    2015-01-01

    Highlights: • Fuzzy logic-based advanced on–off control is proposed. • An anticipative control mechanism is implemented by using fuzzy theory. • Novel thermal analysis program including solar irradiation as a factor is developed. • The proposed controller solves over-heating and under-heating thermal problems. • Solar energy compensation method is applied to compensate for the solar energy. - Abstract: In this paper, an advanced on–off control method based on fuzzy logic is proposed for maintaining thermal comfort in residential buildings. Due to the time-lag of the control systems and the late building thermal response, an anticipative control mechanism is required to reduce energy loss and thermal discomfort. The proposed controller is implemented based on an on–off controller combined with a fuzzy algorithm. On–off control was chosen over other conventional control methods because of its structural simplicity. However, because conventional on–off control has a fixed operating range and a limited ability for improvements in control performance, fuzzy theory can be applied to overcome these limitations. Furthermore, a fuzzy-based solar energy compensation algorithm can be applied to the proposed controller to compensate for the energy gained from solar radiation according to the time of day. Simulations were conducted to compare the proposed controller with a conventional on–off controller under identical external conditions such as outdoor temperature and solar energy; these simulations were carried out by using a previously reported thermal analysis program that was modified to consider such external conditions. In addition, experiments were conducted in a residential building called Green Home Plus, in which hydronic radiant floor heating is used; in these experiments, the proposed system performed better than a system employing conventional on–off control methods

  3. Fuzzy Logic Controlled Solar Module for Driving Three- Phase Induction Motor

    Science.gov (United States)

    Afiqah Zainal, Nurul; Sooi Tat, Chan; Ajisman

    2016-02-01

    Renewable energy produced by solar module gives advantages for generated three- phase induction motor in remote area. But, solar module's ou tput is uncertain and complex. Fuzzy logic controller is one of controllers that can handle non-linear system and maximum power of solar module. Fuzzy logic controller used for Maximum Power Point Tracking (MPPT) technique to control Pulse-Width Modulation (PWM) for switching power electronics circuit. DC-DC boost converter used to boost up photovoltaic voltage to desired output and supply voltage source inverter which controlled by three-phase PWM generated by microcontroller. IGBT switched Voltage source inverter (VSI) produced alternating current (AC) voltage from direct current (DC) source to control speed of three-phase induction motor from boost converter output. Results showed that, the output power of solar module is optimized and controlled by using fuzzy logic controller. Besides that, the three-phase induction motor can be drive and control using VSI switching by the PWM signal generated by the fuzzy logic controller. This concluded that the non-linear system can be controlled and used in driving three-phase induction motor.

  4. Modelling Of Anticipated Damage Ratio On Breakwaters Using Fuzzy Logic

    Science.gov (United States)

    Mercan, D. E.; Yagci, O.; Kabdasli, S.

    2003-04-01

    In breakwater design the determination of armour unit weight is especially important in terms of the structure's life. In a typical experimental breakwater stability study, different wave series composed of different wave heights; wave period and wave steepness characteristics are applied in order to investigate performance the structure. Using a classical approach, a regression equation is generated for damage ratio as a function of characteristic wave height. The parameters wave period and wave steepness are not considered. In this study, differing from the classical approach using a fuzzy logic, a relationship between damage ratio as a function of mean wave period (T_m), wave steepness (H_s/L_m) and significant wave height (H_s) was further generated. The system's inputs were mean wave period (T_m), wave steepness (H_s/L_m) and significant wave height (H_s). For fuzzification all input variables were divided into three fuzzy subsets, their membership functions were defined using method developed by Mandani (Mandani, 1974) and the rules were written. While for defuzzification the centroid method was used. In order to calibrate and test the generated models an experimental study was conducted. The experiments were performed in a wave flume (24 m long, 1.0 m wide and 1.0 m high) using 20 different irregular wave series (P-M spectrum). Throughout the study, the water depth was 0.6 m and the breakwater cross-sectional slope was 1V/2H. In the armour layer, a type of artificial armour unit known as antifer cubes were used. The results of the established fuzzy logic model and regression equation model was compared with experimental data and it was determined that the established fuzzy logic model gave a more accurate prediction of the damage ratio on this type of breakwater. References Mandani, E.H., "Application of Fuzzy Algorithms for Control of Simple Dynamic Plant", Proc. IEE, vol. 121, no. 12, December 1974.

  5. Application of fuzzy logic control system for reactor feed-water control

    International Nuclear Information System (INIS)

    Iijima, T.; Nakajima, Y.

    1994-01-01

    The successful actual application of a fuzzy logic control system to the a nuclear Fugen nuclear power reactor is described. Fugen is a heavy-water moderated, light-water cooled reactor. The introduction of fuzzy logic control system has enabled operators to control the steam drum water level more effectively in comparison to a conventional proportional-integral (PI) control system

  6. Fuzzy logics acquisition and simulation modules for expert systems to assist operator's decision for nuclear power stations

    International Nuclear Information System (INIS)

    Averkin, A.A.

    1994-01-01

    A new type of fuzzy expert system for assisting the operator's decisions in nuclear power plant system in non-standard situations is proposed. This expert system is based on new approaches to fuzzy logics acquisition and to fuzzy logics testing. Fuzzy logics can be generated by a T-norms axiomatic system to choose the most suitable to operator's way of thinking. Then the chosen fuzzy logic is tested by simulation of inference process in expert system. The designed logic is the input of inference module of expert system

  7. Design of a fuzzy logic based controller for neutron power regulation

    International Nuclear Information System (INIS)

    Velez D, D.

    2000-01-01

    This work presents a fuzzy logic controller design for neutron power control, from its source to its full power level, applied to a nuclear reactor model. First, we present the basic definitions on fuzzy sets as generalized definitions of the crisp (non fuzzy) set theory. Likewise, we define the basic operations on fuzzy sets (complement, union, and intersection), and the operations on fuzzy relations such as projection and cylindrical extension operations. Furthermore, some concepts of the fuzzy control theory, such as the main modules of the typical fuzzy controller structure and its internal variables, are defined. After the knowledge base is obtained by simulation of the reactor behavior, where the controlled system is modeled by a simple nonlinear reactor model, this model is used to infer a set of fuzzy rules for the reactor response to different insertions of reactivity. The reduction of the response time, using fuzzy rule based controllers on this reactor, is possible by adjusting the output membership functions, by selecting fuzzy rule sets, or by increasing the number of crisp inputs to the fuzzy controller. System characteristics, such as number of rules, response times, and safety parameter values, were considered in the evaluation of each controller merits. Different fuzzy controllers are designed to attain the desired power level, to maintain a constant level for long periods of time, and to keep the reactor away from a shutdown condition. The basic differences among the controllers are the number of crisp inputs and the novel implementation of a crisp power level-based selection of different sets of output membership functions. Simulation results highlight, mainly: (1) A decrease of the response variations at low power level, and (2) a decrease in the time required to attain the desired neutron power. Finally, we present a comparative study of different fuzzy control algorithms applied to a nuclear model. (Author)

  8. Fault Diagnosis in Deaerator Using Fuzzy Logic

    Directory of Open Access Journals (Sweden)

    S Srinivasan

    2007-01-01

    Full Text Available In this paper a fuzzy logic based fault diagnosis system for a deaerator in a power plant unit is presented. The system parameters are obtained using the linearised state space deaerator model. The fuzzy inference system is created and rule base are evaluated relating the parameters to the type and severity of the faults. These rules are fired for specific changes in system parameters and the faults are diagnosed.

  9. Fuzzy Logic-Based Filter for Removing Additive and Impulsive Noise from Color Images

    Science.gov (United States)

    Zhu, Yuhong; Li, Hongyang; Jiang, Huageng

    2017-12-01

    This paper presents an efficient filter method based on fuzzy logics for adaptively removing additive and impulsive noise from color images. The proposed filter comprises two parts including noise detection and noise removal filtering. In the detection part, the fuzzy peer group concept is applied to determine what type of noise is added to each pixel of the corrupted image. In the filter part, the impulse noise is deducted by the vector median filter in the CIELAB color space and an optimal fuzzy filter is introduced to reduce the Gaussian noise, while they can work together to remove the mixed Gaussian-impulse noise from color images. Experimental results on several color images proves the efficacy of the proposed fuzzy filter.

  10. Fuzzy logic controller implementation for a solar air-conditioning system

    International Nuclear Information System (INIS)

    Lygouras, J.N.; Botsaris, P.N.; Vourvoulakis, J.; Kodogiannis, V.

    2007-01-01

    The implementation of a variable structure fuzzy logic controller for a solar powered air conditioning system and its advantages are investigated in this paper. Two DC motors are used to drive the generator pump and the feed pump of the solar air-conditioner. Two different control schemes for the DC motors rotational speed adjustment are implemented and tested: the first one is a pure fuzzy controller, its output being the control signal for the DC motor driver. A 7 x 7 fuzzy matrix assigns the controller output with respect to the error value and the derivative of the error. The second scheme is a two-level controller. The lower level is a conventional PID controller, and the higher level is a fuzzy controller acting over the parameters of the low level controller. Step response of the two control loops are presented as experimental results. The contribution of this design is that in the control system, the fuzzy logic is implemented through software in a common, inexpensive, 16-bit microcontroller, which does not have special abilities for fuzzy control

  11. Fuzzy logic controller implementation for a solar air-conditioning system

    Energy Technology Data Exchange (ETDEWEB)

    Lygouras, J.N.; Vourvoulakis, J. [Laboratory of Electronics, School of Electrical and Computer Engineering, Democritus University of Thrace, Vas. Sofias 12, 67100 Xanthi (Greece); Botsaris, P.N. [Laboratory of Materials, Processes and Mechanical Design, School of Production and Management Engineering, Democritus University of Thrace 67100 Xanthi (Greece); Kodogiannis, V. [Centre for Systems Analysis, School of Computer Science, University of Westminster, London, HA1 3TP (United Kingdom)

    2007-12-15

    The implementation of a variable structure fuzzy logic controller for a solar powered air conditioning system and its advantages are investigated in this paper. Two DC motors are used to drive the generator pump and the feed pump of the solar air-conditioner. Two different control schemes for the DC motors rotational speed adjustment are implemented and tested: the first one is a pure fuzzy controller, its output being the control signal for the DC motor driver. A 7 x 7 fuzzy matrix assigns the controller output with respect to the error value and the derivative of the error. The second scheme is a two-level controller. The lower level is a conventional PID controller, and the higher level is a fuzzy controller acting over the parameters of the low level controller. Step response of the two control loops are presented as experimental results. The contribution of this design is that in the control system, the fuzzy logic is implemented through software in a common, inexpensive, 16-bit microcontroller, which does not have special abilities for fuzzy control. (author)

  12. Clinical Outcome Prediction in Aneurysmal Subarachnoid Hemorrhage Using Bayesian Neural Networks with Fuzzy Logic Inferences

    Directory of Open Access Journals (Sweden)

    Benjamin W. Y. Lo

    2013-01-01

    Full Text Available Objective. The novel clinical prediction approach of Bayesian neural networks with fuzzy logic inferences is created and applied to derive prognostic decision rules in cerebral aneurysmal subarachnoid hemorrhage (aSAH. Methods. The approach of Bayesian neural networks with fuzzy logic inferences was applied to data from five trials of Tirilazad for aneurysmal subarachnoid hemorrhage (3551 patients. Results. Bayesian meta-analyses of observational studies on aSAH prognostic factors gave generalizable posterior distributions of population mean log odd ratios (ORs. Similar trends were noted in Bayesian and linear regression ORs. Significant outcome predictors include normal motor response, cerebral infarction, history of myocardial infarction, cerebral edema, history of diabetes mellitus, fever on day 8, prior subarachnoid hemorrhage, admission angiographic vasospasm, neurological grade, intraventricular hemorrhage, ruptured aneurysm size, history of hypertension, vasospasm day, age and mean arterial pressure. Heteroscedasticity was present in the nontransformed dataset. Artificial neural networks found nonlinear relationships with 11 hidden variables in 1 layer, using the multilayer perceptron model. Fuzzy logic decision rules (centroid defuzzification technique denoted cut-off points for poor prognosis at greater than 2.5 clusters. Discussion. This aSAH prognostic system makes use of existing knowledge, recognizes unknown areas, incorporates one's clinical reasoning, and compensates for uncertainty in prognostication.

  13. Investigation of the Flutter Suppression by Fuzzy Logic Control for Hypersonic Wing

    Science.gov (United States)

    Li, Dongxu; Luo, Qing; Xu, Rui

    This paper presents a fundamental study of flutter characteristics and control performance of an aeroelastic system based on a two-dimensional double wedge wing in the hypersonic regime. Dynamic equations were established based on the modified third order nonlinear piston theory and some nonlinear structural effects are also included. A set of important parameters are observed. And then aeroelastic control law is designed to suppress the amplitude of the LCOs for the system in the sub/supercritical speed range by applying fuzzy logic control on the input of the deflection of the flap. The overall effects of the parameters on the aeroelastic system were outlined. Nonlinear aeroelastic responses in the open- and closed-loop system are obtained through numerical methods. The simulations show fuzzy logic control methods are effective in suppressing flutter and provide a smart approach for this complicated system.

  14. Estimation and Comparison of Underground Economy in Croatia and European Union Countries: Fuzzy Logic Approach

    Directory of Open Access Journals (Sweden)

    Kristina Marsic

    2016-06-01

    The purpose of this paper is to address this issue in three ways. First, we review existing estimates of the size of the underground economy. Second, we apply a novel calculation method for estimation: fuzzy logic. Third, we calculated and compared underground economy index for 25 European Union countries and compared it, with special focus on Croatian underground economy index. Results indicated that Croatia has the thirteenth largest underground economy among measured members of the European Union. This study is the first of its kind with recent data to measure the size of underground economy in European Union countries by employing fuzzy logic approach.

  15. Fuzzy Logic Controlled Solar Module for Driving Three- Phase Induction Motor

    International Nuclear Information System (INIS)

    Zainal, Nurul Afiqah; Tat, Chan Sooi; Ajisman

    2016-01-01

    Renewable energy produced by solar module gives advantages for generated three- phase induction motor in remote area. But, solar module's output is uncertain and complex. Fuzzy logic controller is one of controllers that can handle non-linear system and maximum power of solar module. Fuzzy logic controller used for Maximum Power Point Tracking (MPPT) technique to control Pulse-Width Modulation (PWM) for switching power electronics circuit. DC-DC boost converter used to boost up photovoltaic voltage to desired output and supply voltage source inverter which controlled by three-phase PWM generated by microcontroller. IGBT switched Voltage source inverter (VSI) produced alternating current (AC) voltage from direct current (DC) source to control speed of three-phase induction motor from boost converter output. Results showed that, the output power of solar module is optimized and controlled by using fuzzy logic controller. Besides that, the three-phase induction motor can be drive and control using VSI switching by the PWM signal generated by the fuzzy logic controller. This concluded that the non-linear system can be controlled and used in driving three-phase induction motor. (paper)

  16. A Note on Axiomatizations of Pavelka-style Complete Fuzzy Logics

    Czech Academy of Sciences Publication Activity Database

    Cintula, Petr

    2016-01-01

    Roč. 292, 1 June (2016), s. 160-174 ISSN 0165-0114 R&D Projects: GA ČR GAP202/10/1826 Institutional support: RVO:67985807 Keywords : mathematical fuzzy logic * Pavelka-style completeness * MTL logic * Lukasiewicz logics * Product Logic * truth constants * Monteiro–Baaz delta Subject RIV: BA - General Mathematics Impact factor: 2.718, year: 2016

  17. FAULT DIAGNOSIS IN ROTATING MACHINE USING FULL SPECTRUM OF VIBRATION AND FUZZY LOGIC

    Directory of Open Access Journals (Sweden)

    ROGER R. DA SILVA

    2017-11-01

    Full Text Available Industries are always looking for more efficient maintenance systems to minimize machine downtime and productivity liabilities. Among several approaches, artificial intelligence techniques have been increasingly applied to machine diagnosis. Current paper forwards the development of a system for the diagnosis of mechanical faults in the rotating structures of machines, based on fuzzy logic, using rules foregrounded on the full spectrum of the machine´s complex vibration signal. The diagnostic system was developed in Matlab and it was applied to a rotor test rig where different faults were introduced. Results showed that the diagnostic system based on full spectra and fuzzy logic is capable of identifying with precision different types of faults, which have similar half spectrum. The methodology has a great potential to be implemented in predictive maintenance programs in industries and may be expanded to include the identification of other types of faults not covered in the case study under analysis.

  18. Fuzzy, crisp, and human logic in e-commerce marketing data mining

    Science.gov (United States)

    Hearn, Kelda L.; Zhang, Yanqing

    2001-03-01

    In today's business world there is an abundance of available data and a great need to make good use of it. Many businesses would benefit from examining customer habits and trends and making marketing and product decisions based on that analysis. However, the process of manually examining data and making sound decisions based on that data is time consuming and often impractical. Intelligent systems that can make judgments similar to human judgments are sorely needed. Thus, systems based on fuzzy logic present themselves as an option to be seriously considered. The work described in this paper attempts to make an initial comparison between fuzzy logic and more traditional hard or crisp logic to see which would make a better substitute for human intervention. In this particular case study, customers are classified into categories that indicate how desirable the customer would be as a prospect for marketing. This classification is based on a small set of customer data. The results from these investigations make it clear that fuzzy logic is more able to think for itself and make decisions that more closely match human decision and is therefore significantly closer to human logic than crisp logic.

  19. Fuzzy Logic as a Tool for Assessing Students’ Knowledge and Skills

    Directory of Open Access Journals (Sweden)

    Michael Gr. Voskoglou

    2013-05-01

    Full Text Available Fuzzy logic, which is based on fuzzy sets theory introduced by Zadeh in 1965, provides a rich and meaningful addition to standard logic. The applications which may be generated from or adapted to fuzzy logic are wide-ranging and provide the opportunity for modeling under conditions which are imprecisely defined. In this article we develop a fuzzy model for assessing student groups’ knowledge and skills. In this model the students’ characteristics under assessment (knowledge of the subject matter, problem solving skills and analogical reasoning abilities are represented as fuzzy subsets of a set of linguistic labels characterizing their performance, and the possibilities of all student profiles are calculated. In this way, a detailed quantitative/qualitative study of the students’ group performance is obtained. The centroid method and the group’s total possibilistic uncertainty are used as defuzzification methods in converting our fuzzy outputs to a crisp number. According to the centroid method, the coordinates of the center of gravity of the graph of the membership function involved provide a measure of the students’ performance. Techniques of assessing the individual students’ abilities are also studied and examples are presented to illustrate the use of our results in practice.

  20. LA LÓGICA DIFUSA COMPENSATORIA / THE COMPENSATORY FUZZY LOGIC

    Directory of Open Access Journals (Sweden)

    Jesús Cejas-Montero

    2011-06-01

    Full Text Available

    La Lógica Difusa Compensatoria es un modelo lógico que permite la modelación simultánea de los procesos deductivos y de toma de decisiones. Sus características más importantes son: la flexibilidad, la tolerancia con la imprecisión, la capacidad para moldear problemas no-lineales y su fundamento en el lenguaje de sentido común. El artículo pretende llevar a la comunidad académico-empresarial las ideas fundamentales de la Lógica Difusa Compensatoria, ilustrándola en sus posibles campos de aplicación para lograr la competitividad de una organización.

    Abstract

    The Compensatory Fuzzy Logic is a logical model that allows the simultaneous modeling of the deductive and decision-making processes. The most important characteristics of Compensatory Fuzzy Logic are: the flexibility, the tolerance with the inaccuracy, the capacity to model no-lineal problems and its foundation in the language of common sense. The article seeks to bring the basic ideas of the Compensatory Fuzzy Logic to the academic–managerial community, illustrating it in its possible fields of application, in order to achieve the competitiveness of an organization.

  1. Classification of Children Intelligence with Fuzzy Logic Method

    Science.gov (United States)

    Syahminan; ika Hidayati, Permata

    2018-04-01

    Intelligence of children s An Important Thing To Know The Parents Early on. Typing Can be done With a Child’s intelligence Grouping Dominant Characteristics Of each Type of Intelligence. To Make it easier for Parents in Determining The type of Children’s intelligence And How to Overcome them, for It Created A Classification System Intelligence Grouping Children By Using Fuzzy logic method For determination Of a Child’s degree of intelligence type. From the analysis We concluded that The presence of Intelligence Classification systems Pendulum Children With Fuzzy Logic Method Of determining The type of The Child’s intelligence Can be Done in a way That is easier And The results More accurate Conclusions Than Manual tests.

  2. Fuzzy logic and A* algorithm implementation on goat foraging games

    Science.gov (United States)

    Harsani, P.; Mulyana, I.; Zakaria, D.

    2018-03-01

    Goat foraging is one of the games that apply the search techniques within the scope of artificial intelligence. This game involves several actors including players and enemies. The method used in this research is fuzzy logic and Algorithm A*. Fuzzy logic is used to determine enemy behaviour. The A* algorithm is used to search for the shortest path. There are two input variables: the distance between the player and the enemy and the anger level of the goat. The output variable that has been defined is the enemy behaviour. The A* algorithm is used to determine the closest path between the player and the enemy and define the enemy's escape path to avoid the player. There are 4 types of enemies namely farmers, planters, farmers and sellers of plants. Players are goats that aims to find a meal that is a plant. In this game goats aim to spend grass in the garden in the form of a maze while avoiding the enemy. The game provides an application of artificial intelligence and is made in four difficulty levels.

  3. Fuzzy Logic and Its Application in Football Team Ranking

    Directory of Open Access Journals (Sweden)

    Wenyi Zeng

    2014-01-01

    some certain rules, we propose four parameters to calculate fuzzy similar matrix, obtain fuzzy equivalence matrix and the ranking result for our numerical example, T7, T3, T1, T9, T10, T8, T11, T12, T2, T6, T5, T4, and investigate four parameters sensitivity analysis. The study shows that our fuzzy logic method is reliable and stable when the parameters change in certain range.

  4. A fuzzy-logic antiswing controller for three-dimensional overhead cranes.

    Science.gov (United States)

    Cho, Sung-Kun; Lee, Ho-Hoon

    2002-04-01

    In this paper, a new fuzzy antiswing control scheme is proposed for a three-dimensional overhead crane. The proposed control consists of a position servo control and a fuzzy-logic control. The position servo control is used to control crane position and rope length, and the fuzzy-logic control is used to suppress load swing. The proposed control guarantees not only prompt suppression of load swing but also accurate control of crane position and rope length for simultaneous travel, traverse, and hoisting motions of the crane. Furthermore, the proposed control provides practical gain tuning criteria for easy application. The effectiveness of the proposed control is shown by experiments with a three-dimensional prototype overhead crane.

  5. Fuzzy logic controller for stabilization of biped robot gait

    Directory of Open Access Journals (Sweden)

    Ryadchikov I.V.

    2018-01-01

    Full Text Available The article centers round the problem of stabilization of biped robot gait through smoothing out the jumps of first and second order derivatives of a biped robot control vector using the fuzzy logic approach. The structure of a composite Takagi-Sugeno fuzzy logic controller developed by the authors is presented. The simulation study of a robot gait with climbing an obstacle is carried out and the results provided in the article showed that the developed controller performed significantly better than the analytical formula model in terms of smoothing out the derivatives of the control vector.

  6. Fuzzy logic model to quantify risk perception

    International Nuclear Information System (INIS)

    Bukh, Julia; Dickstein, Phineas

    2008-01-01

    The aim of this study is a quantification of public risk perception towards the nuclear field so as to be considered in decision making whenever the public involvement is sought. The proposed model includes both qualitative factors such as familiarity and voluntariness and numerical factors influencing risk perception, such as probability of occurrence and severity of consequence. Since part of these factors can be characterized only by qualitative expressions and the determination of them are linked with vagueness, imprecision and uncertainty, the most suitable method for the risk level assessment is Fuzzy Logic, which models qualitative aspects of knowledge and reasoning processes without employing precise quantitative analyses. This work, then, offers a Fuzzy-Logic based mean of representing the risk perception by a single numerical feature, which can be weighted and accounted for in decision making procedures. (author)

  7. Design of a Tele-Control Electrical Vehicle System Using a Fuzzy Logic Control

    Directory of Open Access Journals (Sweden)

    M. Boukhnifer

    2012-11-01

    Full Text Available This paper presents a fuzzy logic design of a tele-control electrical vehicle system. We showed that the application of fuzzy logic control allows the stability of tele-vehicle system in spite of communication delays between the operator and the vehicle. A robust bilateral controller design using fuzzy logic frameworks was proposed. This approach allows a convenient means to trade off robustness and stability for a pre-specified time-delay margin. Both the performance and robustness of the proposed method were demonstrated by simulation results for a constant time delay between the operator and the electrical vehicle system.

  8. Fuzzy Logic Decoupled Lateral Control for General Aviation Airplanes

    Science.gov (United States)

    Duerksen, Noel

    1997-01-01

    It has been hypothesized that a human pilot uses the same set of generic skills to control a wide variety of aircraft. If this is true, then it should be possible to construct an electronic controller which embodies this generic skill set such that it can successfully control different airplanes without being matched to a specific airplane. In an attempt to create such a system, a fuzzy logic controller was devised to control aileron or roll spoiler position. This controller was used to control bank angle for both a piston powered single engine aileron equipped airplane simulation and a business jet simulation which used spoilers for primary roll control. Overspeed, stall and overbank protection were incorporated in the form of expert systems supervisors and weighted fuzzy rules. It was found that by using the artificial intelligence techniques of fuzzy logic and expert systems, a generic lateral controller could be successfully used on two general aviation aircraft types that have very different characteristics. These controllers worked for both airplanes over their entire flight envelopes. The controllers for both airplanes were identical except for airplane specific limits (maximum allowable airspeed, throttle ]ever travel, etc.). This research validated the fact that the same fuzzy logic based controller can control two very different general aviation airplanes. It also developed the basic controller architecture and specific control parameters required for such a general controller.

  9. An Innovative Fuzzy-Logic-Based Methodology for Trend Identification

    International Nuclear Information System (INIS)

    Wang Xin; Tsoukalas, Lefteri H.; Wei, Thomas Y.C.; Reifman, Jaques

    2001-01-01

    A new fuzzy-logic-based methodology for on-line signal trend identification is introduced. The methodology may be used for detecting the onset of nuclear power plant (NPP) transients at the earliest possible time and could be of great benefit to diagnostic, maintenance, and performance-monitoring programs. Although signal trend identification is complicated by the presence of noise, fuzzy methods can help capture important features of on-line signals, integrate the information included in these features, and classify incoming NPP signals into increasing, decreasing, and steady-state trend categories. A computer program named PROTREN is developed and tested for the purpose of verifying this methodology using NPP and simulation data. The results indicate that the new fuzzy-logic-based methodology is capable of detecting transients accurately, it identifies trends reliably and does not misinterpret a steady-state signal as a transient one

  10. A Note on the Notion of Truth in Fuzzy Logic

    Czech Academy of Sciences Publication Activity Database

    Hájek, Petr; Shepherdson, J.

    2001-01-01

    Roč. 109, 1-2 (2001), s. 65-69 ISSN 0168-0072 Institutional research plan: AV0Z1030915 Keywords : many-valued logic * fuzzy logic Subject RIV: BA - General Mathematics Impact factor: 0.519, year: 2001

  11. A fuzzy-logic-based approach to qualitative safety modelling for marine systems

    International Nuclear Information System (INIS)

    Sii, H.S.; Ruxton, Tom; Wang Jin

    2001-01-01

    Safety assessment based on conventional tools (e.g. probability risk assessment (PRA)) may not be well suited for dealing with systems having a high level of uncertainty, particularly in the feasibility and concept design stages of a maritime or offshore system. By contrast, a safety model using fuzzy logic approach employing fuzzy IF-THEN rules can model the qualitative aspects of human knowledge and reasoning processes without employing precise quantitative analyses. A fuzzy-logic-based approach may be more appropriately used to carry out risk analysis in the initial design stages. This provides a tool for working directly with the linguistic terms commonly used in carrying out safety assessment. This research focuses on the development and representation of linguistic variables to model risk levels subjectively. These variables are then quantified using fuzzy sets. In this paper, the development of a safety model using fuzzy logic approach for modelling various design variables for maritime and offshore safety based decision making in the concept design stage is presented. An example is used to illustrate the proposed approach

  12. Application of fuzzy logic to determine the odour intensity of model gas mixtures using electronic nose

    Science.gov (United States)

    Szulczyński, Bartosz; Gębicki, Jacek; Namieśnik, Jacek

    2018-01-01

    The paper presents the possibility of application of fuzzy logic to determine the odour intensity of model, ternary gas mixtures (α-pinene, toluene and triethylamine) using electronic nose prototype. The results obtained using fuzzy logic algorithms were compared with the values obtained using multiple linear regression (MLR) model and sensory analysis. As the results of the studies, it was found the electronic nose prototype along with the fuzzy logic pattern recognition system can be successfully used to estimate the odour intensity of tested gas mixtures. The correctness of the results obtained using fuzzy logic was equal to 68%.

  13. Fuzzy logic prediction of dew point pressure of selected Iranian gas condensate reservoirs

    Energy Technology Data Exchange (ETDEWEB)

    Nowroozi, Saeed [Shahid Bahonar Univ. of Kerman (Iran); Iranian Offshore Oil Company (I.O.O.C.) (Iran); Ranjbar, Mohammad; Hashemipour, Hassan; Schaffie, Mahin [Shahid Bahonar Univ. of Kerman (Iran)

    2009-12-15

    The experimental determination of dew point pressure in a window PVT cell is often difficult especially in the case of lean retrograde gas condensate. Besides all statistical, graphical and experimental methods, the fuzzy logic method can be useful and more reliable for estimation of reservoir properties. Fuzzy logic can overcome uncertainty existent in many reservoir properties. Complexity, non-linearity and vagueness are some reservoir parameter characteristics, which can be propagated simply by fuzzy logic. The fuzzy logic dew point pressure modeling system used in this study is a multi input single output (MISO) Mamdani system. The model was developed using experimentally constant volume depletion (CVD) measured samples of some Iranian fields. The performance of the model is compared against the performance of some of the most accurate and general correlations for dew point pressure calculation. Results show that this novel method is more accurate and reliable with an average absolute deviation of 1.33% and 2.68% for developing and checking, respectively. (orig.)

  14. Design of stability-guaranteed fuzzy logic controller for nuclear steam generators

    International Nuclear Information System (INIS)

    Cho, B.H.; No, H.C.

    1996-01-01

    A fuzzy logic controller (FLC) and a fuzzy logic filter (FLF), which have a special type of fuzzifier, inference engine, and defuzzifier, are applied to the water level control of a nuclear steam generator (S/G). It is shown that arbitrary two-input, single-output linear controllers can be adequately expressed by this FLC. A procedure to construct stability-guaranteed FLC rules is proposed. It contains the following steps: (1) the stable sector of linear feedback gains is obtained from the suboptimal concept based on LQR theory and the Lyapunov's stability criteria; (2) the stable sector of linear gains is mapped into two linear rule tables that are used as limits for the FLC rules; and (3) the construction of an FLC rule table is done by choosing certain rules that lie between these limits. This type of FLC guarantees asymptotic stability of the control system. The FLF generates a feedforward signal of S/G feedwater from the steam flow measurement using a fuzzy concept. Through computer simulation, it is found that the FLC with the FLF works better than a well-tuned PID controller with variable gains to reduce swell/shrink phenomena, especially for the water level deviation and abrupt steam flow disturbances that are typical in the existing power plants

  15. DC motor speed control using fuzzy logic controller

    Science.gov (United States)

    Ismail, N. L.; Zakaria, K. A.; Nazar, N. S. Moh; Syaripuddin, M.; Mokhtar, A. S. N.; Thanakodi, S.

    2018-02-01

    The automatic control has played a vital role in the advance of engineering and science. Nowadays in industries, the control of direct current (DC) motor is a common practice thus the implementation of DC motor controller speed is important. The main purpose of motor speed control is to keep the rotation of the motor at the present speed and to drive a system at the demand speed. The main purpose of this project is to control speed of DC Series Wound Motor using Fuzzy Logic Controller (FLC). The expectation of this project is the Fuzzy Logic Controller will get the best performance compared to dc motor without controller in terms of settling time (Ts), rise time (Tr), peak time (Tp) and percent overshoot (%OS).

  16. A geographic information system for gas power plant location using analytical hierarchy process and fuzzy logic

    International Nuclear Information System (INIS)

    Alavipoor, F. S.; Karimi, S.; Balist, J.; Khakian, A. H.

    2016-01-01

    This research recommends a geographic information system-based and multi-criteria evaluation for locating a gas power plant in Natanz City in Iran. The multi-criteria decision framework offers a hierarchy model to select a suitable place for a gas power plant. This framework includes analytic hierarchy process, fuzzy set theory and weighted linear combination. The analytic hierarchy process was applied to compare the importance of criteria among hierarchy elements classified by environmental group criteria. In the next step, the fuzzy logic was used to regulate the criteria through various fuzzy membership functions and fuzzy layers were formed by using fuzzy operators in the Arc-GIS environment. Subsequently, they were categorized into 6 classes using reclassify function. Then weighted linear combination was applied to combine the research layers. Finally, the two approaches were analyzed to find the most suitable place to set up a gas power plant. According to the results, the utilization of GAMMA fuzzy operator was shown to be suitable for this site selection.

  17. Fuzzy logic and image processing techniques for the interpretation of seismic data

    International Nuclear Information System (INIS)

    Orozco-del-Castillo, M G; Ortiz-Alemán, C; Rodríguez-Castellanos, A; Urrutia-Fucugauchi, J

    2011-01-01

    Since interpretation of seismic data is usually a tedious and repetitive task, the ability to do so automatically or semi-automatically has become an important objective of recent research. We believe that the vagueness and uncertainty in the interpretation process makes fuzzy logic an appropriate tool to deal with seismic data. In this work we developed a semi-automated fuzzy inference system to detect the internal architecture of a mass transport complex (MTC) in seismic images. We propose that the observed characteristics of a MTC can be expressed as fuzzy if-then rules consisting of linguistic values associated with fuzzy membership functions. The constructions of the fuzzy inference system and various image processing techniques are presented. We conclude that this is a well-suited problem for fuzzy logic since the application of the proposed methodology yields a semi-automatically interpreted MTC which closely resembles the MTC from expert manual interpretation

  18. Consumer Behavior Modeling: Fuzzy Logic Model for Air Purifiers Choosing

    Directory of Open Access Journals (Sweden)

    Oleksandr Dorokhov

    2017-12-01

    Full Text Available At the beginning, the article briefly describes the features of the marketing complex household goods. Also provides an overview of some aspects of the market for indoor air purifiers. The specific subject of the study was the process of consumer choice of household appliances for cleaning air in living quarters. The aim of the study was to substantiate and develop a computer model for evaluating by the potential buyers devices for air purification in conditions of vagueness and ambiguity of their consumer preferences. Accordingly, the main consumer criteria are identified, substantiated and described when buyers choose air purifiers. As methods of research, approaches based on fuzzy logic, fuzzy sets theory and fuzzy modeling were chosen. It was hypothesized that the fuzzy-multiple model allows rather accurately reflect consumer preferences and potential consumer choice in conditions of insufficient and undetermined information. Further, a computer model for estimating the consumer qualities of air cleaners by customers is developed. A proposed approach based on the application of fuzzy logic theory and practical modeling in the specialized computer software MATLAB. In this model, the necessary membership functions and their terms are constructed, as well as a set of rules for fuzzy inference to make decisions on the estimation of a specific air purifier. A numerical example of a comparative evaluation of air cleaners presented on the Ukrainian market is made and is given. Numerical simulation results confirmed the applicability of the proposed approach and the correctness of the hypothesis advanced about the possibility of modeling consumer behavior using fuzzy logic. The analysis of the obtained results is carried out and the prospects of application, development, and improvement of the developed model and the proposed approach are determined.

  19. Fuzzy logic application for extruders replacement problem

    Directory of Open Access Journals (Sweden)

    Edison Conde Perez dos Santos

    2017-03-01

    Full Text Available In a scenario of uncertainty and imprecision, before taking the replacement analysis, a manager needs to consider the uncertain reality of a problem. In this scenario, the fuzzy logic makes an excellent option. Therefore, it is necessary to make a decision based on the fuzzy model. This study is based on the comparison of two methodologies used in the problem of asset replacement. The study, thus, was based on a comparison between two extruders for polypropylene yarn bibliopegy, comparing mainly the costs involved in maintaining the equipment.

  20. A fuzzy logic sliding mode controlled electronic differential for a direct wheel drive EV

    Science.gov (United States)

    Ozkop, Emre; Altas, Ismail H.; Okumus, H. Ibrahim; Sharaf, Adel M.

    2015-11-01

    In this study, a direct wheel drive electric vehicle based on an electronic differential system with a fuzzy logic sliding mode controller (FLSMC) is studied. The conventional sliding surface is modified using a fuzzy rule base to obtain fuzzy dynamic sliding surfaces by changing its slopes using the global error and its derivative in a fuzzy logic inference system. The controller is compared with proportional-integral-derivative (PID) and sliding mode controllers (SMCs), which are usually preferred to be used in industry. The proposed controller provides robustness and flexibility to direct wheel drive electric vehicles. The fuzzy logic sliding mode controller, electronic differential system and the overall electrical vehicle mechanism are modelled and digitally simulated by using the Matlab software. Simulation results show that the system with FLSMC has better efficiency and performance compared to those of PID and SMCs.

  1. Automating Software Development Process using Fuzzy Logic

    NARCIS (Netherlands)

    Marcelloni, Francesco; Aksit, Mehmet; Damiani, Ernesto; Jain, Lakhmi C.; Madravio, Mauro

    2004-01-01

    In this chapter, we aim to highlight how fuzzy logic can be a valid expressive tool to manage the software development process. We characterize a software development method in terms of two major components: artifact types and methodological rules. Classes, attributes, operations, and inheritance

  2. Fuzzy-logic based learning style prediction in e-learning using web ...

    Indian Academy of Sciences (India)

    tion, especially in web environments and proposes to use Fuzzy rules to handle the uncertainty in .... learning in safe and supportive environment ... working of the proposed Fuzzy-logic based learning style prediction in e-learning. Section 4.

  3. Decision model on the demographic profile for tuberculosis control using fuzzy logic

    Directory of Open Access Journals (Sweden)

    Laisa Ribeiro de Sá

    2015-06-01

    Full Text Available This study aimed to describe the relationship between demographic factors and the involvement of tuberculosis by applying a decision support model based on fuzzy logic to classify the regions as priority and non-priority in the city of João Pessoa, state of Paraíba (PB. As data source, we used the Notifiable Diseases Information System between 2009 and 2011. We chose the descriptive analysis, relative risk (RR, spatial distribution and fuzzy logic. The total of 1,245 cases remained in the study, accounting for 37.02% of cases in 2009. High and low risk clusters were identified, and the RR was higher among men (8.47, with 12 clusters, and among those uneducated (11.65, with 13 clusters. To demonstrate the functionality of the model was elected the year with highest number of cases, and the municipality district with highest population. The methodology identified priority areas, guiding managers to make decisions that respect the local particularities.

  4. Fuzzy Logic Unmanned Air Vehicle Motion Planning

    Directory of Open Access Journals (Sweden)

    Chelsea Sabo

    2012-01-01

    Full Text Available There are a variety of scenarios in which the mission objectives rely on an unmanned aerial vehicle (UAV being capable of maneuvering in an environment containing obstacles in which there is little prior knowledge of the surroundings. With an appropriate dynamic motion planning algorithm, UAVs would be able to maneuver in any unknown environment towards a target in real time. This paper presents a methodology for two-dimensional motion planning of a UAV using fuzzy logic. The fuzzy inference system takes information in real time about obstacles (if within the agent's sensing range and target location and outputs a change in heading angle and speed. The FL controller was validated, and Monte Carlo testing was completed to evaluate the performance. Not only was the path traversed by the UAV often the exact path computed using an optimal method, the low failure rate makes the fuzzy logic controller (FLC feasible for exploration. The FLC showed only a total of 3% failure rate, whereas an artificial potential field (APF solution, a commonly used intelligent control method, had an average of 18% failure rate. These results highlighted one of the advantages of the FLC method: its adaptability to complex scenarios while maintaining low control effort.

  5. Assessment of Seismic Damage on The Exist Buildings Using Fuzzy Logic

    Science.gov (United States)

    Pınar, USTA; Nihat, MOROVA; EVCİ, Ahmet; ERGÜN, Serap

    2018-01-01

    Earthquake as a natural disaster could damage the lives of many people and buildings all over the world. These is micvulnerability of the buildings needs to be evaluated. Accurate evaluation of damage sustained by buildings during natural disaster events is critical to determine the buildings safety and their suitability for future occupancy. The earthquake is one of the disasters that structures face the most. There fore, there is a need to evaluate seismic damage and vulnerability of the buildings to protect them. These days fuzzy systems have been widely used in different fields of science because of its simpli city and efficiency. Fuzzy logic provides a suitable framework for reasoning, deduction, and decision making in fuzzy conditions. In this paper, studies on earthquake hazard evaluation of buildings by fuzzy logic modeling concepts in the literature have been investigated and evaluated, as a whole.

  6. Research on fault diagnosis of nuclear power plants based on genetic algorithms and fuzzy logic

    International Nuclear Information System (INIS)

    Zhou Yangping; Zhao Bingquan

    2001-01-01

    Based on genetic algorithms and fuzzy logic and using expert knowledge, mini-knowledge tree model and standard signals from simulator, a new fuzzy-genetic method is developed to fault diagnosis in nuclear power plants. A new replacement method of genetic algorithms is adopted. Fuzzy logic is used to calculate the fitness of the strings in genetic algorithms. Experiments on the simulator show it can deal with the uncertainty and the fuzzy factor

  7. A logical approach to fuzzy truth hedges

    Czech Academy of Sciences Publication Activity Database

    Esteva, F.; Godo, L.; Noguera, Carles

    2013-01-01

    Roč. 232, č. 1 (2013), s. 366-385 ISSN 0020-0255 Institutional support: RVO:67985556 Keywords : Mathematical fuzzy logic * Standard completeness * Truth hedges Subject RIV: BA - General Mathematics Impact factor: 3.893, year: 2013 http://library.utia.cas.cz/separaty/2016/MTR/noguera-0469148.pdf

  8. FUZZY LOGIC CONTROLLER AS MODELING TOOL FOR THE BURNING PROCESS OF A CEMENT PRODUCTION PLANT

    Directory of Open Access Journals (Sweden)

    P.B. Osofisan

    2012-01-01

    Full Text Available

    ENGLISH ABSTRACT: A comprehensive optimisation of the cement production process presents a problem since the input variables as well as the output variables are non-linear, interdependent and contain uncertainties. To arrive at a solution, a Fuzzy Logic controller has been designed to achieve a well-defined relationship between the main and vital variables through the instrumentality of a Fuzzy Model. The Fuzzy Logic controller has been simulated on a digital computer using MATLAB 5.0 Fuzzy Logic Tool Box, using data from a local cement production plant.

    AFRIKAANSE OPSOMMING: Die omvattende optimisering van 'n proses wat sement vervaardig, word beskryf deur nie-linieêre inset- en uitsetveranderlikes wat onderling afhanklik is, en ook van onsekere aard is. Om 'n optimum oplossing te verkry, word 'n Wasigheidsmodel gebruik. Die model word getoets deur gebruik te maak van die MATLAB 5.0 Fuzzy Logic Tool Box en data vanaf 'n lokale sementvervaardigingsaanleg.

  9. [New horizons in medicine. The application of "fuzzy logic" in clinical and experimental medicine].

    Science.gov (United States)

    Guarini, G

    1994-06-01

    In medicine, the study of physiological and physiopathological problems is generally programmed by elaborating models which respond to the principals of formal logic. This gives the advantage of favouring the transformation of the formal model into a mathematical model of reference which responds to the principles of the set theories. All this is in the utopian wish to obtain as a result of each research, a net answer whether positive or negative, according to the Aristotelian principal of tertium non datur. Taking this into consideration, the A. briefly traces the principles of modal logic and, in particular, those of fuzzy logic, proposing that the latter substitute the actual definition of "logic with more truth values", with that perhaps more pertinent of "logic of conditioned possibilities". After a brief synthesis on the state of the art on the application of fuzzy logic, the A. reports an example of graphic expression of fuzzy logic by demonstrating how the basic glycemic data (expressed by the vectors magnitude) revealed in a sample of healthy individuals, constituted on the whole an unbroken continuous stream of set partials. The A. calls attention to fuzzy logic as a useful instrument to elaborate in a new way the analysis of scenario qualified to acquire the necessary information to single out the critical points which characterize the potential development of any biological phenomenon.

  10. Complexity of Some Language Fragments of Fuzzy Logics

    Czech Academy of Sciences Publication Activity Database

    Haniková, Zuzana

    2017-01-01

    Roč. 21, č. 1 (2017), s. 69-77 ISSN 1432-7643 R&D Projects: GA ČR GAP202/11/1632 Institutional support: RVO:67985807 Keywords : fuzzy logic * propositional logic * language fragment * implicational fragment * commutative semigroup * equational theory * computational complexity Subject RIV: BA - General Mathematics OBOR OECD: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8) Impact factor: 2.472, year: 2016

  11. Fuzzy logic of quasi-truth an algebraic treatment

    CERN Document Server

    Di Nola, Antonio; Turunen, Esko

    2016-01-01

    This book presents the first algebraic treatment of quasi-truth fuzzy logic and covers the algebraic foundations of many-valued logic. It offers a comprehensive account of basic techniques and reports on important results showing the pivotal role played by perfect many-valued algebras (MV-algebras). It is well known that the first-order predicate Łukasiewicz logic is not complete with respect to the canonical set of truth values. However, it is complete with respect to all linearly ordered MV –algebras. As there are no simple linearly ordered MV-algebras in this case, infinitesimal elements of an MV-algebra are allowed to be truth values. The book presents perfect algebras as an interesting subclass of local MV-algebras and provides readers with the necessary knowledge and tools for formalizing the fuzzy concept of quasi true and quasi false. All basic concepts are introduced in detail to promote a better understanding of the more complex ones. It is an advanced and inspiring reference-guide for graduate s...

  12. Indeterminacy, linguistic semantics and fuzzy logic

    Energy Technology Data Exchange (ETDEWEB)

    Novak, V. [Univ. of Ostrava (Czech Republic)

    1996-12-31

    In this paper, we discuss the indeterminacy phenomenon which has two distinguished faces, namely uncertainty modeled especially by the probability theory and vagueness, modeled by fuzzy logic. Other important mathematical model of vagueness is provided by the Alternative Set Theory. We focus on some of the basic concepts of these theories in connection with mathematical modeling of the linguistic semantics.

  13. Priority-based queuing and transmission rate management using a fuzzy logic controller in WSNs

    Directory of Open Access Journals (Sweden)

    Imen Bouazzi

    2017-06-01

    Full Text Available Wireless sensor networks (WSNs operate under challenging conditions, such as maintaining message latency and the reliability of data transmission and maximizing the battery life of sensor nodes. The aim of this study is to propose a fuzzy logic algorithm for solving these issues, which are difficult to address with traditional techniques. The idea, in this study, is to employ a fuzzy logic scheme to optimize energy consumption and minimize packet drops. We demonstrated how fuzzy logic can be used to tackle this specific communication problem with minimal computational complexity. In this context, the implementation of a fuzzy logic in the Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA mechanism is achieved through filling the queue length and the traffic rate at each node. Through simulations, we show that our proposed technique has a better performance in terms of energy consumption compared to the basic implementation of CSMA/CA.

  14. Predicting recycling behaviour: Comparison of a linear regression model and a fuzzy logic model.

    Science.gov (United States)

    Vesely, Stepan; Klöckner, Christian A; Dohnal, Mirko

    2016-03-01

    In this paper we demonstrate that fuzzy logic can provide a better tool for predicting recycling behaviour than the customarily used linear regression. To show this, we take a set of empirical data on recycling behaviour (N=664), which we randomly divide into two halves. The first half is used to estimate a linear regression model of recycling behaviour, and to develop a fuzzy logic model of recycling behaviour. As the first comparison, the fit of both models to the data included in estimation of the models (N=332) is evaluated. As the second comparison, predictive accuracy of both models for "new" cases (hold-out data not included in building the models, N=332) is assessed. In both cases, the fuzzy logic model significantly outperforms the regression model in terms of fit. To conclude, when accurate predictions of recycling and possibly other environmental behaviours are needed, fuzzy logic modelling seems to be a promising technique. Copyright © 2015 Elsevier Ltd. All rights reserved.

  15. A Fuzzy-Logic Generalization of a Data Mining Approach

    Czech Academy of Sciences Publication Activity Database

    Holeňa, Martin

    2001-01-01

    Roč. 11, č. 6 (2001), s. 595-610 ISSN 1210-0552. [SOFSEM 2001 Workshop on Soft Computing. Piešťany, 29.11.2001-30.11.2001] R&D Projects: GA AV ČR IAA1030004 Institutional research plan: AV0Z1030915 Keywords : data analysis * vague hypotheses * vague significante level * fuzzy prediacate calculus * basic fuzzy logic * generalized quantifiers * method GUHA Subject RIV: BA - General Mathematics

  16. Feasibility analysis of fuzzy logic control for ITER Poloidal field (PF) AC/DC converter system

    Energy Technology Data Exchange (ETDEWEB)

    Hassan, Mahmood Ul; Fu, Peng [Institute of Plasma Physics, Chinese Academy of Sciences, Hefei 230031 (China); University of Science and Technology of China (China); Song, Zhiquan, E-mail: zhquansong@ipp.ac.cn [Institute of Plasma Physics, Chinese Academy of Sciences, Hefei 230031 (China); Chen, Xiaojiao [Institute of Plasma Physics, Chinese Academy of Sciences, Hefei 230031 (China); University of Science and Technology of China (China); Zhang, Xiuqing [Institute of Plasma Physics, Chinese Academy of Sciences, Hefei 230031 (China); Humayun, Muhammad [Shanghai Jiaotong University (China)

    2017-05-15

    Highlights: • The implementation of the Fuzzy controller for the ITER PF converter system is presented. • The comparison of the FLC and PI simulation are investigated. • The FLC single and parallel bridge operation are presented. • Fuzzification and Defuzzification algorithms are presented using FLC controller. - Abstract: This paper describes the feasibility analysis of the fuzzy logic control to increase the performance of the ITER poloidal field (PF) converter systems. A fuzzy-logic-based controller is designed for ITER PF converter system, using the traditional PI controller and Fuzzy controller (FC), the dynamic behavior and transient response of the PF converter system are compared under normal operation by analysis and simulation. The analysis results show that the fuzzy logic control can achieve better operation performance than PI control.

  17. Searching the Arcane Origins of Fuzzy Logic

    Directory of Open Access Journals (Sweden)

    Angel Garrido

    2011-05-01

    Full Text Available It is well-known that Artificial Intelligence requires Logic. But its Classical version shows too many insufficiencies. So, it is very necessary to introduce more sophisticated tools, as may be
    Fuzzy Logic, Modal Logic, Non-Monotonic Logic, and so on. When you are searching the possible precedent of such new ideas, we may found that they are not totally new, because some ancient thinkers have suggested many centuries ago similar concepts, certainly without adequate mathematical formulation, but in the same line: against the dogmatism and the dualistic vision of
    the world: absolutely true vs. absolutely false, black vs. white, good or bad by nature, 0 vs.1, etc. We attempt to analyze here some of these greatly unexplored, and very interesting early origins.

  18. IMPLEMENTING FUZZY LOGIC IN DETERMINING SELLING PRICE

    Directory of Open Access Journals (Sweden)

    Danny Prabowo Soetanto

    2000-01-01

    Full Text Available The determination of the price should meet certain criteria, both from the society and the company itself. The combination of various criteria will result in another problem. Fuzzy Logic covers all influencing factors and displays the membership function graphic. Furthermore, by implementing fuzzy rules and fuzzy operator, the right price can be determined which covers all the factors above. The determination of the rules is based on the raw material cost, direct labor cost, distribution cost and the customers' opinion regarding the appropriate price. Then, the model is designed with the help of Matlab software. The result is finally obtained in the form of a model performed by Matlab software. The model displays the output concerning the selling price of the product for each change in the dominant factors.

  19. Adaptive Interval Type-2 Fuzzy Logic Control for PMSM Drives with a Modified Reference Frame

    KAUST Repository

    Chaoui, Hicham; Khayamy, Mehdy; Aljarboua, Abdullah Abdulaziz

    2017-01-01

    In this paper, an adaptive interval type-2 fuzzy logic control scheme is proposed for high-performance permanent magnet synchronous machine drives. This strategy combines the power of type-2 fuzzy logic systems with the adaptive control theory

  20. Sensitivity-based self-learning fuzzy logic control for a servo system

    NARCIS (Netherlands)

    Balenovic, M.

    1998-01-01

    Describes an experimental verification of a self-learning fuzzy logic controller (SLFLC). The SLFLC contains a learning algorithm that utilizes a second-order reference model and a sensitivity model related to the fuzzy controller parameters. The effectiveness of the proposed controller has been

  1. Incorporating fuzzy data and logical relations in the design of expert systems for nuclear reactors

    International Nuclear Information System (INIS)

    Guth, M.A.S.

    1987-01-01

    This paper applies the method of assigning probability in Dempster-Shafer Theory (DST) to the components of rule-based expert systems used in the control of nuclear reactors. Probabilities are assigned to premises, consequences, and rules themselves. This paper considers how uncertainty can propagate through a system of Boolean equations, such as fault trees or expert systems. The probability masses assigned to primary initiating events in the expert system can be derived from observing a nuclear reactor in operation or based on engineering knowledge of the reactor parts. Use of DST mass assignments offers greater flexibility to the construction of expert systems in two important respects. First, DST mass assignments have the advantage over classical probability methods of accommodating when necessary uncommitted probability assignments. Thus the DST probability framework can incorporate expert system inputs from imprecise or fuzzy data. Second, DST applied to the Boolean rules themselves leads to a probabilistic logic, where a given rule may be valid with probability less than unity: fuzzy logical rules

  2. Vrednovanje lokacija za uspostavljanje mosnog mesta prelaska preko vodenih prepreka primenom fuzzy logike / Evaluating locations for river crossing using fuzzy logic

    Directory of Open Access Journals (Sweden)

    Darko I. Božanić

    2010-01-01

    pontoon bridge location for the purpose of overcoming water obstacles. The decision making process includes a higher or lower level of indefiniteness of criteria needed for making a relevant decision. Since the fuzzy logic is very suitable for expressing indefiniteness and uncertainty, the decision making process using a fuzzy logic approach is shown in the paper. Characteristics of multi-criteria methods and selection of methods for evaluation With the development of the evaluation theory, evaluation models were being developed as well. Different objectives of evaluation and other differences in the whole procedure had an impact on the development of the majority of evaluation models adapted to different requests. The main objective of multi-criteria methods is to define the priority between particular variants or criteria in the situation with a large number of decision makers and a large number of decision making criteria in repeated periods of time. Main notions of fuzzy logic and fuzzy sets In a larger sense, the fuzzy logic is a synonym for the fuzzy sets theory which refers to the class of objects with unclear borders the membership of which is measured by certain value. It is important to realize that the essence of the fuzzy logic is different from the essence of the traditional logic system. This logic, based on clear and precisely defined rules, has its foundation in the set theory. An element can or cannot be a part of a set, which means that sets have clearly determined borders. Contrary to the conventional logic, the fuzzy logic does not define precisely the membership of an element to a set. The membership value is expressed in percentage, for example. The fuzzy logic is very close to human perception. Fuzzy system modeling for evaluation of selected locations The fuzzy logic is usually used for complex system modeling, when it is difficult to define interdependences between certain variables by other methods. The criteria for the selection of locations for

  3. Evaluation of a Multi-Variable Self-Learning Fuzzy Logic Controller ...

    African Journals Online (AJOL)

    In spite of the usefulness of fuzzy control, its main drawback comes from lack of a systematic control design methodology. The most challenging aspect of the design of a fuzzy logic controller is the elicitation of the control rules for its rule base. In this paper, a scheme capable of elicitation of acceptable rules for multivariable ...

  4. Real Time Implementation of a DC Motor Speed Control by Fuzzy Logic Controller and PI Controller Using FPGA

    Directory of Open Access Journals (Sweden)

    G. Sakthivel

    2010-10-01

    Full Text Available Fuzzy logic control has met with growing interest in many motor control applications due to its non-linearity, handling features and independence of plant modelling. The hardware implementation of fuzzy logic controller (FLC on FPGA is very important because of the increasing number of fuzzy applications requiring highly parallel and high speed fuzzy processing. Implementation of a fuzzy logic controller and conventional PI controller on an FPGA using VHDL for DC motor speed control is presented in this paper. The proposed scheme is to improve tracking performance of D.C. motor as compared to the conventional (PI control strategy .This paper describes the hardware implementation of two inputs (error and change in error, one output fuzzy logic controller based on PI controller and conventional PI controller using VHDL. Real time implementation FLC and conventional PI controller is made on Spartan-3A DSP FPGA (XC3SD1800A FPGA for the speed control of DC motor. It is observed that fuzzy logic based controllers give better responses than the conventional PI controller for the speed control of dc motor.

  5. A new approach of active compliance control via fuzzy logic control for multifingered robot hand

    Science.gov (United States)

    Jamil, M. F. A.; Jalani, J.; Ahmad, A.

    2016-07-01

    Safety is a vital issue in Human-Robot Interaction (HRI). In order to guarantee safety in HRI, a model reference impedance control can be a very useful approach introducing a compliant control. In particular, this paper establishes a fuzzy logic compliance control (i.e. active compliance control) to reduce impact and forces during physical interaction between humans/objects and robots. Exploiting a virtual mass-spring-damper system allows us to determine a desired compliant level by understanding the behavior of the model reference impedance control. The performance of fuzzy logic compliant control is tested in simulation for a robotic hand known as the RED Hand. The results show that the fuzzy logic is a feasible control approach, particularly to control position and to provide compliant control. In addition, the fuzzy logic control allows us to simplify the controller design process (i.e. avoid complex computation) when dealing with nonlinearities and uncertainties.

  6. Fuzzy logic control of steam generator water level in pressurized water reactors

    International Nuclear Information System (INIS)

    Kuan, C.C.; Lin, C.; Hsu, C.C.

    1992-01-01

    In this paper a fuzzy logic controller is applied to control the steam generator water level in a pressurized water reactor. The method does not require a detailed mathematical mode of the object to be controlled. The design is based on a set of linguistic rules that were adopted from the human operator's experience. After off-line fuzzy computation, the controller is a lookup table, and thus, real-time control is achieved. Shrink-and-swell phenomena are considered in the linguistic rules, and the simulation results show that their effect is dramatically reduced. The performance of the control system can also be improved by changing the input and output scaling factors, which is convenient for on-line tuning

  7. FUZZY LOGIC STATIC SYNCHRONOUS COMPENSATOR (FLSTATCOM

    Directory of Open Access Journals (Sweden)

    I Made Mataram

    2016-06-01

    Full Text Available Penerapan teknik fuzzy membawa perubahan yang signifikan khusus pada perhitungan dan analisis sistem konvensional. Peranan peralatan FACTS (Flexible AC Transmission System untuk memperbaiki kualitas tegangan dari pembangkit menuju beban sangat besar. STATCOM merupakan peralatan paling berpengaruh untuk memperbaiki tegangan pada jaringan transmisi tenaga listrik. Pembahasan pada penelitian ini dikhususkan pada FLSTATCOM. Model Fuzzy Logic dengan dua input digunakan sebagai pengontrol IGBT, sehingga mampu meningkatkan unjuk kerja STATCOM konvensional. Sistem Single Machine Infinite Bus menjadi sistem uji coba penggunaan FLSTATCOM.Hasil simulasi menggunakan simulink MATLAB, diperoleh nilai tegangan pada tiap sisi terima tanpa menggunakan STATCOM menghasilkan tegangan sebesar 217,3 kV, menggunakan STATCOM menghasilkan tegangan sebesar 220 kV, dan penggunaan FLSTATCOM mampu meningkatkan tegangan menjadi 228,9 kV (5,34%

  8. Fuzzy logic type 1 and type 2 based on LabVIEW FPGA

    CERN Document Server

    Ponce-Cruz, Pedro; MacCleery, Brian

    2016-01-01

    This book is a comprehensive introduction to LabVIEW FPGA™, a package allowing the programming of intelligent digital controllers in field programmable gate arrays (FPGAs) using graphical code. It shows how both potential difficulties with understanding and programming in VHDL and the consequent difficulty and slowness of implementation can be sidestepped. The text includes a clear theoretical explanation of fuzzy logic (type 1 and type 2) with case studies that implement the theory and systematically demonstrate the implementation process. It goes on to describe basic and advanced levels of programming LabVIEW FPGA and show how implementation of fuzzy-logic control in FPGAs improves system responses. A complete toolkit for implementing fuzzy controllers in LabVIEW FPGA has been developed with the book so that readers can generate new fuzzy controllers and deploy them immediately. Problems and their solutions allow readers to practice the techniques and to absorb the theoretical ideas as they arise. Fuzzy L...

  9. Fuzzy Logic Based Autonomous Traffic Control System

    Directory of Open Access Journals (Sweden)

    Muhammad ABBAS

    2012-01-01

    Full Text Available The aim of this paper is to design and implement fuzzy logic based traffic light Control system to solve the traffic congestion issues. In this system four input parameters: Arrival, Queue, Pedestrian and Emergency Vehicle and two output parameters: Extension in Green and Pedestrian Signals are used. Using Fuzzy Rule Base, the system extends or terminates the Green Signal according to the Traffic situation at the junction. On the presence of emergency vehicle, the system decides which signal(s should be red and how much an extension should be given to Green Signal for Emergency Vehicle. The system also monitors the density of people and makes decisions accordingly. In order to verify the proposed design algorithm MATLAB simulation is adopted and results obtained show concurrency to the calculated values according to the Mamdani Model of the Fuzzy Control System.

  10. A Fuzzy Logic Based Method for Analysing Test Results

    Directory of Open Access Journals (Sweden)

    Le Xuan Vinh

    2017-11-01

    Full Text Available Network operators must perform many tasks to ensure smooth operation of the network, such as planning, monitoring, etc. Among those tasks, regular testing of network performance, network errors and troubleshooting is very important. Meaningful test results will allow the operators to evaluate network performanceof any shortcomings and to better plan for network upgrade. Due to the diverse and mainly unquantifiable nature of network testing results, there is a needs to develop a method for systematically and rigorously analysing these results. In this paper, we present STAM (System Test-result Analysis Method which employs a bottom-up hierarchical processing approach using Fuzzy logic. STAM is capable of combining all test results into a quantitative description of the network performance in terms of network stability, the significance of various network erros, performance of each function blocks within the network. The validity of this method has been successfully demonstrated in assisting the testing of a VoIP system at the Research Instiute of Post and Telecoms in Vietnam. The paper is organized as follows. The first section gives an overview of fuzzy logic theory the concepts of which will be used in the development of STAM. The next section describes STAM. The last section, demonstrating STAM’s capability, presents a success story in which STAM is successfully applied.

  11. Applying Fuzzy Logic and Data Mining Techniques in Wireless Sensor Network for Determination Residential Fire Confidence

    Directory of Open Access Journals (Sweden)

    Mirjana Maksimović

    2014-09-01

    Full Text Available The main goal of soft computing technologies (fuzzy logic, neural networks, fuzzy rule-based systems, data mining techniques… is to find and describe the structural patterns in the data in order to try to explain connections between data and on their basis create predictive or descriptive models. Integration of these technologies in sensor nodes seems to be a good idea because it can significantly lead to network performances improvements, above all to reduce the energy consumption and enhance the lifetime of the network. The purpose of this paper is to analyze different algorithms in the case of fire confidence determination in order to see which of the methods and parameter values work best for the given problem. Hence, an analysis between different classification algorithms in a case of nominal and numerical d

  12. Fuzzy logic applied to the modeling of water dynamics in an Oxisol in northeastern Brazil

    Directory of Open Access Journals (Sweden)

    Antônio Cláudio Marques Afonso

    2014-04-01

    Full Text Available Modeling of water movement in non-saturated soil usually requires a large number of parameters and variables, such as initial soil water content, saturated water content and saturated hydraulic conductivity, which can be assessed relatively easily. Dimensional flow of water in the soil is usually modeled by a nonlinear partial differential equation, known as the Richards equation. Since this equation cannot be solved analytically in certain cases, one way to approach its solution is by numerical algorithms. The success of numerical models in describing the dynamics of water in the soil is closely related to the accuracy with which the water-physical parameters are determined. That has been a big challenge in the use of numerical models because these parameters are generally difficult to determine since they present great spatial variability in the soil. Therefore, it is necessary to develop and use methods that properly incorporate the uncertainties inherent to water displacement in soils. In this paper, a model based on fuzzy logic is used as an alternative to describe water flow in the vadose zone. This fuzzy model was developed to simulate the displacement of water in a non-vegetated crop soil during the period called the emergency phase. The principle of this model consists of a Mamdani fuzzy rule-based system in which the rules are based on the moisture content of adjacent soil layers. The performances of the results modeled by the fuzzy system were evaluated by the evolution of moisture profiles over time as compared to those obtained in the field. The results obtained through use of the fuzzy model provided satisfactory reproduction of soil moisture profiles.

  13. A fuzzy logic controller for feedwater regulation in pressurized water reactors

    International Nuclear Information System (INIS)

    Eryuerek, E.E.; Upadhyaya, B.R.; Alguindigue, I.E.

    1994-01-01

    Fuzzy control refers to the application of fuzzy logic theory to control systems. In this paper fuzzy controllers for steam generator water level control and pump speed control are presented, and their performance in the presence of perturbations is discussed. In order to test the robustness of the controllers, their performance is compared with the performance of model based adaptive controllers and traditional PID controllers. The control actions calculated by the fuzzy controllers is have the characteristic of quick and smooth control compared to the others

  14. Using fuzzy logic for automatic control: Case study of a problem of cereals samples classification

    Directory of Open Access Journals (Sweden)

    Lakhoua Najeh Mohamed

    2009-01-01

    Full Text Available The aim of this paper is to present the use of fuzzy logic for automatic control of industrial systems particularly the way to approach a problem of classification. We present a case study of a grading system of cereals that allows us to determine the price of transactions of cereals in Tunisia. Our contribution in this work consists in proposing not only an application of the fuzzy logic on the grading system of cereals but also a methodology enabling the proposing of a new grading system based on the concept of 'Grade' while using the fuzzy logic techniques. .

  15. A Modification of the Fuzzy Logic Based DASH Adaptation Scheme for Performance Improvement

    Directory of Open Access Journals (Sweden)

    Hyun Jun Kim

    2018-01-01

    Full Text Available We propose a modification of the fuzzy logic based DASH adaptation scheme (FDASH for seamless media service in time-varying network conditions. The proposed scheme (mFDASH selects a more appropriate bit-rate for the next segment by modification of the Fuzzy Logic Controller (FLC and estimates more accurate available bandwidth than FDASH scheme by using History-Based TCP Throughput Estimation. Moreover, mFDASH reduces the number of video bit-rate changes by applying Segment Bit-Rate Filtering Module (SBFM and employs Start Mechanism for clients to provide high-quality videos in the very beginning stage of the streaming service. Lastly, Sleeping Mechanism is applied to avoid any expected buffer overflow. We then use NS-3 Network Simulator to verify the performance of mFDASH. Upon the experimental results, mFDASH shows no buffer overflow within the limited buffer size, which is not guaranteed in FDASH. Also, we confirm that mFDASH provides the highest QoE to DASH clients among the three schemes (mFDASH, FDASH, and SVAA in Point-to-Point networks, Wi-Fi networks, and LTE networks, respectively.

  16. Fuzzy Logic Supervised Teleoperation Control for Mobile Robot

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    The supervised teleoperation control is presented for a mobile robot to implement the tasks by using fuzzy logic. The teleoperation control system includes joystick based user interaction mechanism, the high level instruction set and fuzzy logic behaviors integrated in a supervised autonomy teleoperation control system for indoor navigation. These behaviors include left wall following, right wall following, turn left, turn right, left obstacle avoidance, right obstacle avoidance and corridor following based on ultrasonic range finders data. The robot compares the instructive high level command from the operator and relays back a suggestive signal back to the operator in case of mismatch between environment and instructive command. This strategy relieves the operator's cognitive burden, handle unforeseen situations and uncertainties of environment autonomously. The effectiveness of the proposed method for navigation in an unstructured environment is verified by experiments conducted on a mobile robot equipped with only ultrasonic range finders for environment sensing.

  17. Expanding Basic Fuzzy Logic with Truth Constants for Component Delimiters

    Czech Academy of Sciences Publication Activity Database

    Haniková, Zuzana

    2012-01-01

    Roč. 197, 16 June (2012), s. 95-107 ISSN 0165-0114 R&D Projects: GA ČR GEICC/08/E018 Institutional research plan: CEZ:AV0Z10300504 Keywords : mathematics * non-classical logics * algebra * basic fuzzy logic BL * propositional constants Subject RIV: BA - General Mathematics Impact factor: 1.749, year: 2012

  18. Implementation of a fuzzy logic/neural network multivariable controller

    International Nuclear Information System (INIS)

    Cordes, G.A.; Clark, D.E.; Johnson, J.A.; Smartt, H.B.; Wickham, K.L.; Larson, T.K.

    1992-01-01

    This paper describes a multivariable controller developed at the Idaho National Engineering Laboratory (INEL) that incorporates both fuzzy logic rules and a neural network. The controller was implemented in a laboratory demonstration and was robust, producing smooth temperature and water level response curves with short time constants. In the future, intelligent control systems will be a necessity for optimal operation of autonomous reactor systems located on earth or in space. Even today, there is a need for control systems that adapt to the changing environment and process. Hybrid intelligent control systems promise to provide this adaptive capability. Fuzzy logic implements our imprecise, qualitative human reasoning. The values of system variables (controller inputs) and control variables (controller outputs) are described in linguistic terms and subdivided into fully overlapping value ranges. The fuzzy rule base describes how combinations of input parameter ranges determine the output control values. Neural networks implement our human learning. In this controller, neural networks were embedded in the software to explore their potential for adding adaptability

  19. Damage Identification of Bridge Based on Chebyshev Polynomial Fitting and Fuzzy Logic without Considering Baseline Model Parameters

    Directory of Open Access Journals (Sweden)

    Yu-Bo Jiao

    2015-01-01

    Full Text Available The paper presents an effective approach for damage identification of bridge based on Chebyshev polynomial fitting and fuzzy logic systems without considering baseline model data. The modal curvature of damaged bridge can be obtained through central difference approximation based on displacement modal shape. Depending on the modal curvature of damaged structure, Chebyshev polynomial fitting is applied to acquire the curvature of undamaged one without considering baseline parameters. Therefore, modal curvature difference can be derived and used for damage localizing. Subsequently, the normalized modal curvature difference is treated as input variable of fuzzy logic systems for damage condition assessment. Numerical simulation on a simply supported bridge was carried out to demonstrate the feasibility of the proposed method.

  20. Fuzzy Logic Based The Application of Multi-Microcontroller in Mobile Robot Model

    Directory of Open Access Journals (Sweden)

    Nuryono Satya Widodo

    2009-12-01

    Full Text Available This paper proposed a fuzzy logic based mobile robot as implemented in a multimicrocontroller system. Fuzzy logic controller was developed based on a behavior based approach. The Controller inputs were obtained from seven sonar sensor and three tactile switches. Behavior based approach was implemented in different level priority of behaviors. The behaviors were: obstacle avoidance, wall following and escaping as the emergency behavior. The results show that robot was able to navigate autonomously and avoid the entire obstacle.

  1. Fuzzy logic controller for crude oil levels at Escravos Tank Farm ...

    African Journals Online (AJOL)

    Fuzzy logic controller (FLC) for crude oil flow rates and tank levels was designed for monitoring flow and tank level management at Escravos Tank Farm in Nigeria. The fuzzy control system incorporated essence of expert knowledge required to handle the tasks. Proportional Integral Derivative (PID) control of crude flow ...

  2. Fuzzy logic controller architecture for water level control in nuclear power plant steam generator using ANFIS training method

    International Nuclear Information System (INIS)

    Vosoughi, Naser; Ekrami, AmirHasan; Naseri, Zahra

    2003-01-01

    Since suitable control of water level can greatly enhance the operation of a power station, a fuzzy logic controller is applied to control the steam generator water level in a pressurized water reactor. The method does not require a detailed mathematical model of the object to be controlled. It is shown that two inputs, a single output and the least number of rules (9 rules) are considered for a controller, and the ANFIS training method is employed to model functions in a controlled system. By using ANFIS training method, initial membership functions will be trained and appropriate functions are generated to control water level inside the steam generator while using the stated rules. The proposed architecture can construct an input-output mapping based on both human knowledge (in the from of fuzzy if - then rules) and stipulated input-output data. This fuzzy logic controller is applied to the steam generator level control by computer simulations. The simulation results confirm the excellent performance of this control architecture in compare with a well-turned PID controller. (author)

  3. Intelligent control a hybrid approach based on fuzzy logic, neural networks and genetic algorithms

    CERN Document Server

    Siddique, Nazmul

    2014-01-01

    Intelligent Control considers non-traditional modelling and control approaches to nonlinear systems. Fuzzy logic, neural networks and evolutionary computing techniques are the main tools used. The book presents a modular switching fuzzy logic controller where a PD-type fuzzy controller is executed first followed by a PI-type fuzzy controller thus improving the performance of the controller compared with a PID-type fuzzy controller.  The advantage of the switching-type fuzzy controller is that it uses one rule-base thus minimises the rule-base during execution. A single rule-base is developed by merging the membership functions for change of error of the PD-type controller and sum of error of the PI-type controller. Membership functions are then optimized using evolutionary algorithms. Since the two fuzzy controllers were executed in series, necessary further tuning of the differential and integral scaling factors of the controller is then performed. Neural-network-based tuning for the scaling parameters of t...

  4. Fuzzy Control Tutorial

    DEFF Research Database (Denmark)

    Dotoli, M.; Jantzen, Jan

    1999-01-01

    The tutorial concerns automatic control of an inverted pendulum, especially rule based control by means of fuzzy logic. A ball balancer, implemented in a software simulator in Matlab, is used as a practical case study. The objectives of the tutorial are to teach the basics of fuzzy control......, and to show how to apply fuzzy logic in automatic control. The tutorial is distance learning, where students interact one-to-one with the teacher using e-mail....

  5. Pemodelan Sistem Fuzzy Dengan Menggunakan Matlab

    Directory of Open Access Journals (Sweden)

    Afan Galih Salman

    2010-12-01

    Full Text Available Fuzzy logic is a method in soft computing category, a method that could process uncertain, inaccurate, and less cost implemented data. Some methods in soft computing category besides fuzzy logic are artificial network nerve, probabilistic reasoning, and evolutionary computing. Fuzzy logic has the ability to develop fuzzy system that is intelligent system in uncertain environment. Some stages in fuzzy system formation process is input and output analysis, determining input and output variable, defining each fuzzy set member function, determining rules based on experience or knowledge of an expert in his field, and implementing fuzzy system. Overall, fuzzy logic uses simple mathematical concept, understandable, detectable uncertain and accurate data. Fuzzy system could create and apply expert experiences directly without exercise process and effort to decode the knowledge into a computer until becoming a modeling system that could be relied on decision making.

  6. Digital Fuzzy logic and PI control of phase-shifted full-bridge current-doubler converter

    DEFF Research Database (Denmark)

    Török, Lajos; Munk-Nielsen, Stig

    2011-01-01

    Simple digital fuzzy logic voltage control of a phaseshifted full-bridge (PSFB) converter is proposed in this article. A comparison of the fuzzy controller and the classical PI voltage controller is presented and their effects on the converter dynamics are analyzed. Simulation model of the conver...... of the converter was built in Matlab/Simulink using PLECS. A 600W PSFB convert was designed and built and the control strategies were implemented in a 16 bit fixed point dsPIC microcontroller. The advantages and disadvantages of using Fuzzy logic control are highlighted....

  7. Analysis of Learning Development With Sugeno Fuzzy Logic And Clustering

    Directory of Open Access Journals (Sweden)

    Maulana Erwin Saputra

    2017-06-01

    Full Text Available In the first journal, I made this attempt to analyze things that affect the achievement of students in each school of course vary. Because students are one of the goals of achieving the goals of successful educational organizations. The mental influence of students’ emotions and behaviors themselves in relation to learning performance. Fuzzy logic can be used in various fields as well as Clustering for grouping, as in Learning Development analyzes. The process will be performed on students based on the symptoms that exist. In this research will use fuzzy logic and clustering. Fuzzy is an uncertain logic but its excess is capable in the process of language reasoning so that in its design is not required complicated mathematical equations. However Clustering method is K-Means method is method where data analysis is broken down by group k (k = 1,2,3, .. k. To know the optimal number of Performance group. The results of the research is with a questionnaire entered into matlab will produce a value that means in generating the graph. And simplify the school in seeing Student performance in the learning process by using certain criteria. So from the system that obtained the results for a decision-making required by the school.

  8. Controlling Smart Green House Using Fuzzy Logic Method

    Directory of Open Access Journals (Sweden)

    Rafiuddin Syam

    2017-03-01

    Full Text Available To increase agricultural output it is needed a system that can help the environmental conditions for optimum plant growth. Smart greenhouse allows for plants to grow optimally, because the temperature and humidity can be controlled so that no drastic changes. It is necessary for optimal smart greenhouse needed a system to manipulate the environment in accordance with the needs of the plant. In this case the setting temperature and humidity in the greenhouse according to the needs of the plant. So using an automated system for keeping such environmental condition is important. In this study, the authors use fuzzy logic to make the duration of watering the plants more dynamic in accordance with the input temperature and humidity so that the temperature and humidity in the green house plants maintained in accordance to the reference condition. Based on the experimental results using fuzzy logic method is effective to control the duration of watering and to maintain the optimum temperature and humidity inside the greenhouse

  9. Controlling Smart Green House Using Fuzzy Logic Method

    Directory of Open Access Journals (Sweden)

    Rafiuddin Syam

    2015-10-01

    Full Text Available To increase agricultural output it is needed a system that can help the environmental conditions for optimum plant growth. Smart greenhouse allows for plants to grow optimally, because the temperature and humidity can be controlled so that no drastic changes. It is necessary for optimal smart greenhouse needed a system to manipulate the environment in accordance with the needs of the plant. In this case the setting temperature and humidity in the greenhouse according to the needs of the plant. So using an automated system for keeping such environmental condition is important. In this study, the authors use fuzzy logic to make the duration of watering the plants more dynamic in accordance with the input temperature and humidity so that the temperature and humidity in the green house plants maintained in accordance to the reference condition. Based on the experimental results using fuzzy logic method is effective to control the duration of watering and to maintain the optimum temperature and humidity inside the greenhouse

  10. An Extension of the Fuzzy Possibilistic Clustering Algorithm Using Type-2 Fuzzy Logic Techniques

    Directory of Open Access Journals (Sweden)

    Elid Rubio

    2017-01-01

    Full Text Available In this work an extension of the Fuzzy Possibilistic C-Means (FPCM algorithm using Type-2 Fuzzy Logic Techniques is presented, and this is done in order to improve the efficiency of FPCM algorithm. With the purpose of observing the performance of the proposal against the Interval Type-2 Fuzzy C-Means algorithm, several experiments were made using both algorithms with well-known datasets, such as Wine, WDBC, Iris Flower, Ionosphere, Abalone, and Cover type. In addition some experiments were performed using another set of test images to observe the behavior of both of the above-mentioned algorithms in image preprocessing. Some comparisons are performed between the proposed algorithm and the Interval Type-2 Fuzzy C-Means (IT2FCM algorithm to observe if the proposed approach has better performance than this algorithm.

  11. Groundwater Prospecting in Luanda (Angola with the Application of Fuzzy Logics

    Directory of Open Access Journals (Sweden)

    Moises Catanha

    2016-10-01

    Full Text Available This study is aimed at obtaining a map for groundwater prospecting in the province of Luanda (Angola applying fuzzy logic. A favorability map was generated by integrating six variables (longitudinal conductance, delta H, digital elevation model, geological map, static elevation and apparent resistivity and using ArcSDM extension of Sig ArcView with gamma operator and index ϒ=0,7. This map made it possible to classify the province into three areas: less favorable, favorable and very favorable for prospecting for underground aquifers.

  12. Penggunaan Metode Fuzzy Logic untuk Pemantauan Sentimen Brand pada Media Sosial

    Directory of Open Access Journals (Sweden)

    Beki Subaeki, Fatkhan Gunawan, Aldy Rialdy Atmadja

    2017-10-01

    Full Text Available The purpose of this research is to monitor the sentiments of a brand and classify it into positive,  negative or neutral sentiments. The steps of research have started from collecting data, indexing, searching and weighting process. Data are collected by crawling data from social media, such as Facebook and Twitter. After collecting data, then weighting process is done with a fuzzy logic method, where the fuzzy set is determined based on the highest number of positive and negative words in a sentence. Weighting process is calculated from TF (Term Frequency which is the number of words that sought in the document. From the results, TF can be used to find the fuzzy set value and the number of positive or negative sentiments in a document. Mamdani method used to calculate the value of the final sentiment. From the calculation results, it can be shown that the average of sentiment analysis is 63.15%. Keywords:  Information, Sentiment analysis, brand, fuzzy logic, social media. 

  13. Detection of Stator Winding Fault in Induction Motor Using Fuzzy Logic with Optimal Rules

    Directory of Open Access Journals (Sweden)

    Hamid Fekri Azgomi

    2013-04-01

    Full Text Available Induction motors are critical components in many industrial processes. Therefore, swift, precise and reliable monitoring and fault detection systems are required to prevent any further damages. The online monitoring of induction motors has been becoming increasingly important. The main difficulty in this task is the lack of an accurate analytical model to describe a faulty motor. A fuzzy logic approach may help to diagnose traction motor faults. This paper presents a simple method for the detection of stator winding faults (which make up 38% of induction motor failures based on monitoring the line/terminal current amplitudes. In this method, fuzzy logic is used to make decisions about the stator motor condition. In fact, fuzzy logic is reminiscent of human thinking processes and natural language enabling decisions to be made based on vague information. The motor condition is described using linguistic variables. Fuzzy subsets and the corresponding membership functions describe stator current amplitudes. A knowledge base, comprising rule and data bases, is built to support the fuzzy inference. Simulation results are presented to verify the accuracy of motor’s fault detection and knowledge extraction feasibility. The preliminary results show that the proposed fuzzy approach can be used for accurate stator fault diagnosis.

  14. A Fuzzy Logic-Based Video Subtitle and Caption Coloring System

    Directory of Open Access Journals (Sweden)

    Mohsen Davoudi

    2012-01-01

    Full Text Available An approach has been proposed for automatic adaptive subtitle coloring using fuzzy logic-based algorithm. This system changes the color of the video subtitle/caption to “pleasant” color according to color harmony and the visual perception of the image background colors. In the fuzzy analyzer unit, using RGB histograms of background image, the R, G, and B values for the color of the subtitle/caption are computed using fixed fuzzy IF-THEN rules fully driven from the color harmony theories to satisfy complementary color and subtitle-background color harmony conditions. A real-time hardware structure has been proposed for implementation of the front-end processing unit as well as the fuzzy analyzer unit.

  15. Modelling for Temperature Non-Isothermal Continuous Stirred Tank Reactor Using Fuzzy Logic

    OpenAIRE

    Nasser Mohamed Ramli; Mohamad Syafiq Mohamad

    2017-01-01

    Many types of controllers were applied on the continuous stirred tank reactor (CSTR) unit to control the temperature. In this research paper, Proportional-Integral-Derivative (PID) controller are compared with Fuzzy Logic controller for temperature control of CSTR. The control system for temperature non-isothermal of a CSTR will produce a stable response curve to its set point temperature. A mathematical model of a CSTR using the most general operating condition was developed through a set of...

  16. Coordinated signal control for arterial intersections using fuzzy logic

    Science.gov (United States)

    Kermanian, Davood; Zare, Assef; Balochian, Saeed

    2013-09-01

    Every day growth of the vehicles has become one of the biggest problems of urbanism especially in major cities. This can waste people's time, increase the fuel consumption, air pollution, and increase the density of cars and vehicles. Fuzzy controllers have been widely used in many consumer products and industrial applications with success over the past two decades. This article proposes a comprehensive model of urban traffic network using state space equations and then using Fuzzy Logic Tool Box and SIMULINK Program MATLAB a fuzzy controller in order to optimize and coordinate signal control at two intersections at an arterial road. The fuzzy controller decides to extend, early cut or terminate a signal phase and phase sequence to ensure smooth flow of traffic with minimal waiting time and length of queue. Results show that the performance of the proposed traffic controller at novel fuzzy model is better that of conventional controllers under normal and abnormal traffic conditions.

  17. Fuel Saving Strategy in Spark Ignition Engine Using Fuzzy Logic Engine Torque Control

    OpenAIRE

    Aris Triwiyatno; Sumardi

    2012-01-01

    In the case of injection gasoline engine, or better known as spark ignition engines, an effort to improve engine performance as well as to reduce fuel consumption is a fairly complex problem. Generally, engine performance improvement efforts will lead to increase in fuel consumption. However, this problem can be solved by implementing engine torque control based on intelligent regulation such as the fuzzy logic inference system. In this study, fuzzy logic engine torque regulation is used to c...

  18. Fuzzy Logic System for Intermixed Biogas and Photovoltaics Measurement and Control

    Directory of Open Access Journals (Sweden)

    Liston Matindife

    2018-01-01

    Full Text Available This study develops a new integrated measurement and control system for intermixed biogas and photovoltaic systems to achieve safe and optimal energy usage. Literature and field studies show that existing control methods on small- to medium-scale systems fall short of comprehensive system optimization and fault diagnosis, hence the need to revisit these control methods. The control strategy developed in this study is intelligent as it is wholly based on fuzzy logic algorithms. Fuzzy logic controllers due to their superior nonlinear problem solving capabilities to classical controllers considerably simplify controller design. The mathematical models that define classical controllers are difficult or impossible to realize in biogas and photovoltaic generation process. A microcontroller centered fuzzy logic measurement and control embedded system is designed and developed on the existing hybrid biogas and photovoltaic installations. The designed system is able to accurately predict digester stability, quantify biogas output, and carry out biogas fault detection and control. Optimized battery charging and photovoltaic fault detection and control are also successfully implemented. The system is able to optimize the operation and performance of biogas and photovoltaic energy generation.

  19. Hardware simulation of automatic braking system based on fuzzy logic control

    Directory of Open Access Journals (Sweden)

    Noor Cholis Basjaruddin

    2016-07-01

    Full Text Available In certain situations, a moving or stationary object can be a barrier for a vehicle. People and vehicles crossing could potentially get hit by a vehicle. Objects around roads as sidewalks, road separator, power poles, and railroad gates are also a potential source of danger when the driver is inattentive in driving the vehicle. A device that can help the driver to brake automatically is known as Automatic Braking System (ABS. ABS is a part of the Advanced Driver Assistance Systems (ADAS, which is a device designed to assist the driver in driving the process. This device was developed to reduce human error that is a major cause of traffic accidents. This paper presents the design of ABS based on fuzzy logic which is simulated in hardware by using a remote control car. The inputs of fuzzy logic are the speed and distance of the object in front of the vehicle, while the output of fuzzy logic is the intensity of braking. The test results on the three variations of speed: slow-speed, medium-speed, and high-speed shows that the design of ABS can work according to design.

  20. A Temporal Fuzzy Logic Formalism for Knowledge Based Systems

    Directory of Open Access Journals (Sweden)

    Vasile MAZILESCU

    2012-11-01

    Full Text Available This paper shows that the influence of knowledge on new forms of work organisation can be described as mutual relationships. Different changes in work organisation also have a strong influence on the increasing importance of knowledge of different individual and collective actors in working situations. After that, we characterize a piece of basic formal system, an Extended Fuzzy Logic System (EFLS with temporal attributes, to conceptualize future DKMSs based on human imprecise for distributed just in time decisions. The approximate reasoning is perceived as a derivation of new formulas with the corresponding temporal attributes, within a fuzzy theory defined by the fuzzy set of special axioms. In a management application, the reasoning is evolutionary because of unexpected events which may change the state of the DKMS. In this kind of situations it is necessary to elaborate certain mechanisms in order to maintain the coherence of the obtained conclusions, to figure out their degree of reliability and the time domain for which these are true. These last aspects stand as possible further directions of development at a basic logic level for future technologies that must automate knowledge organizational processes.

  1. Analysis of atomic force microscopy data for surface characterization using fuzzy logic

    International Nuclear Information System (INIS)

    Al-Mousa, Amjed; Niemann, Darrell L.; Niemann, Devin J.; Gunther, Norman G.; Rahman, Mahmud

    2011-01-01

    In this paper we present a methodology to characterize surface nanostructures of thin films. The methodology identifies and isolates nanostructures using Atomic Force Microscopy (AFM) data and extracts quantitative information, such as their size and shape. The fuzzy logic based methodology relies on a Fuzzy Inference Engine (FIE) to classify the data points as being top, bottom, uphill, or downhill. The resulting data sets are then further processed to extract quantitative information about the nanostructures. In the present work we introduce a mechanism which can consistently distinguish crowded surfaces from those with sparsely distributed structures and present an omni-directional search technique to improve the structural recognition accuracy. In order to demonstrate the effectiveness of our approach we present a case study which uses our approach to quantitatively identify particle sizes of two specimens each with a unique gold nanoparticle size distribution. - Research Highlights: → A Fuzzy logic analysis technique capable of characterizing AFM images of thin films. → The technique is applicable to different surfaces regardless of their densities. → Fuzzy logic technique does not require manual adjustment of the algorithm parameters. → The technique can quantitatively capture differences between surfaces. → This technique yields more realistic structure boundaries compared to other methods.

  2. Self-learning fuzzy logic controllers based on reinforcement

    International Nuclear Information System (INIS)

    Wang, Z.; Shao, S.; Ding, J.

    1996-01-01

    This paper proposes a new method for learning and tuning Fuzzy Logic Controllers. The self-learning scheme in this paper is composed of Bucket-Brigade and Genetic Algorithm. The proposed method is tested on the cart-pole system. Simulation results show that our approach has good learning and control performance

  3. Use of UPFC device controlled by fuzzy logic controllers for decoupled power flow control

    Directory of Open Access Journals (Sweden)

    Ivković Sanja

    2014-01-01

    Full Text Available This paper investigates the possibility of decoupled active and reactive power flow control in a power system using a UPFC device controlled by fuzzy logic controllers. A Brief theoretical review of the operation principles and applications of UPFC devices and design principles of the fuzzy logic controller used are given. A Matlab/Simulink model of the system with UPFC, the fuzzy controller setup, and graphs of the results are presented. Conclusions are drawn regarding the possibility of using this system for decoupled control of the power flow in power systems based on analysis of these graphs.

  4. Development of Real Time Implementation of 5/5 Rule based Fuzzy Logic Controller Shunt Active Power Filter for Power Quality Improvement

    Science.gov (United States)

    Puhan, Pratap Sekhar; Ray, Pravat Kumar; Panda, Gayadhar

    2016-12-01

    This paper presents the effectiveness of 5/5 Fuzzy rule implementation in Fuzzy Logic Controller conjunction with indirect control technique to enhance the power quality in single phase system, An indirect current controller in conjunction with Fuzzy Logic Controller is applied to the proposed shunt active power filter to estimate the peak reference current and capacitor voltage. Current Controller based pulse width modulation (CCPWM) is used to generate the switching signals of voltage source inverter. Various simulation results are presented to verify the good behaviour of the Shunt active Power Filter (SAPF) with proposed two levels Hysteresis Current Controller (HCC). For verification of Shunt Active Power Filter in real time, the proposed control algorithm has been implemented in laboratory developed setup in dSPACE platform.

  5. Process optimization of citric acid production from aspergillus niger using fuzzy logic design

    International Nuclear Information System (INIS)

    Ali, S.; Haq, I.U.

    2014-01-01

    The inherent non-linearity of citric acid fermentation from Aspergillus niger renders its control difficult, so there is a need to fine-tune the bioreactor performance for maximum production of citric acid in batch culture. For this, fuzzy logic is becoming a popular tool to handle non-linearity of a batch process. The present manuscript deals with fuzzy logic control of citric acid accretion by A. niger in a stirred tank reactor using blackstrap sugarcane molasses as a basal fermentation medium. The customary batches were termed as 'control' while those under fuzzy logic were 'experimental'. The performance of fuzzy logic control of stirred tank reactor was found to be very encouraging for enhanced production of citric acid. The comparison of kinetic parameters showed improved citrate synthase ability of experimental culture (Yp/x = 7.042 g/g). When the culture grown on 150 g/l carbohydrates was monitored for Qp, Qs and Yp/s, there was significant enhancement in these variables over the control. Specific productivity of culture (qp = 0.070 g/g cells/h) was several fold increased. The enthalpy (HD = 70.5 kJ/mol) and entropy of activation (S = -144 J/mol/K) of enzyme for citric acid biosynthesis, free energies for transition state formation and substrate binding for sucrose hydrolysis of experimental were substantially improved. (author)

  6. Fuzzy-logic-based power control system for multifield electrostatic precipitators

    Energy Technology Data Exchange (ETDEWEB)

    Grass, N. [Siemens AG, Erlangen (Germany)

    2002-10-01

    The power consumption of large precipitators can be in the range of 1 MW and above. Depending on the dust load properties, the electrical power may be reduced by up to 50% by applying fuzzy logic, without significantly increasing the dust emissions. The new approach uses fuzzy logic for optimization of existing electrostatic precipitators. The software runs on a standard personal computer platform under the, Windows NT operating system. The controllers of the electrostatic precipitator power supplies are linked to the personal computer via an industrial network (e.g., PROFIBUS). The system determines online the differentials of emission versus electrical power of each field. This measurement is difficult because of overlaid events in the other zones, and process changes. The long response time of the resultant dust emission due to electrical power changes in the precipitator is an additional complication. Rules were defined for a coarse, but fast-response power adaptation of all zones. Fine tuning the running system after the coarse optimization increased the accuracy and reliability. When installed on a 4 x 5 zone precipitator in a power station, significant results were obtained. The power savings over three months of operation were in the range of 40%-60% depending on the load and fuel characteristics. Data were recorded over the test period of three months. The results are presented.

  7. Fuzzy logic and artificial neural networks for nuclear power plant applications

    International Nuclear Information System (INIS)

    Berkan, R.C.; Eryurek, E.; Upadhyaya, B.R.

    1992-01-01

    This paper discusses the feasibility of applying fuzzy logic and neural networks to plant-wide monitoring, diagnostics, and control problems. Different data sets are gathered from several sources including two commercial Pressurized Water Reactors (PWR), the Experimental Breeder Reactor-II (EBR-II), and the conceptual design of Modular Liquid-Metal Reactor (PRISM). These data sets are used to illustrate applications to operating processes, and to PRISM design. The results show that the artificial intelligence approach to a number of operational tasks can considerably improve the safety and availability of nuclear power generation

  8. Robust position control of induction motor using fuzzy logic control

    International Nuclear Information System (INIS)

    Kim, Sei Chan; Kim, Duk Hun; Yang, Seung Ho; Won, Chung Yuen

    1993-01-01

    In recent years, fuzzy logic or fuzzy set theory has reveived attention of a number of researchers in the area of power electronics and motion control. The paper describes a vector-controlled induction motor position servo drive where fuzzy control is used to get robustness against parameter variation and load torque disturbance effects. Both coarse and fine control with the help of look-up rule tables are used to improve transient response and system settling time. The performance characteristics are then compared with those of proportional-integral(PI) control. The simulation results clearly indicate the superiority of fuzzy control with larger number of rules. The fuzzy controller was implemented with a 16-bit microprocessor and tested in laboratory on a 3-hp IGBT inverter induction motor drive system. The test results verify the simulation performance. (Author)

  9. Turkey's short-term gross annual electricity demand forecast by fuzzy logic approach

    International Nuclear Information System (INIS)

    Kucukali, Serhat; Baris, Kemal

    2010-01-01

    This paper aims to forecast Turkey's short-term gross annual electricity demand by applying fuzzy logic methodology while general information on economical, political and electricity market conditions of the country is also given. Unlike most of the other forecast models about Turkey's electricity demand, which usually uses more than one parameter, gross domestic product (GDP) based on purchasing power parity was the only parameter used in the model. Proposed model made good predictions and captured the system dynamic behavior covering the years of 1970-2014. The model yielded average absolute relative errors of 3.9%. Furthermore, the model estimates a 4.5% decrease in electricity demand of Turkey in 2009 and the electricity demand growth rates are projected to be about 4% between 2010 and 2014. It is concluded that forecasting the Turkey's short-term gross electricity demand with the country's economic performance will provide more reliable projections. Forecasting the annual electricity consumption of a country could be made by any designer with the help of the fuzzy logic procedure described in this paper. The advantage of this model lies on the ability to mimic the human thinking and reasoning.

  10. Fuzzy logic control of stand-alone photovoltaic system with battery storage

    Science.gov (United States)

    Lalouni, S.; Rekioua, D.; Rekioua, T.; Matagne, E.

    Photovoltaic energy has nowadays an increased importance in electrical power applications, since it is considered as an essentially inexhaustible and broadly available energy resource. However, the output power provided via the photovoltaic conversion process depends on solar irradiation and temperature. Therefore, to maximize the efficiency of the photovoltaic energy system, it is necessary to track the maximum power point of the PV array. The present paper proposes a maximum power point tracker (MPPT) method, based on fuzzy logic controller (FLC), applied to a stand-alone photovoltaic system. It uses a sampling measure of the PV array power and voltage then determines an optimal increment required to have the optimal operating voltage which permits maximum power tracking. This method carries high accuracy around the optimum point when compared to the conventional one. The stand-alone photovoltaic system used in this paper includes two bi-directional DC/DC converters and a lead-acid battery bank to overcome the scare periods. One converter works as an MPP tracker, while the other regulates the batteries state of charge and compensates the power deficit to provide a continuous delivery of energy to the load. The Obtained simulation results show the effectiveness of the proposed fuzzy logic controller.

  11. Photovoltaic System Modeling with Fuzzy Logic Based Maximum Power Point Tracking Algorithm

    Directory of Open Access Journals (Sweden)

    Hasan Mahamudul

    2013-01-01

    Full Text Available This paper represents a novel modeling technique of PV module with a fuzzy logic based MPPT algorithm and boost converter in Simulink environment. The prime contributions of this work are simplification of PV modeling technique and implementation of fuzzy based MPPT system to track maximum power efficiently. The main highlighted points of this paper are to demonstrate the precise control of the duty cycle with respect to various atmospheric conditions, illustration of PV characteristic curves, and operation analysis of the converter. The proposed system has been applied for three different PV modules SOLKAR 36 W, BP MSX 60 W, and KC85T 87 W. Finally the resultant data has been compared with the theoretical prediction and company specified value to ensure the validity of the system.

  12. Development of erosion risk map using fuzzy logic approach

    Directory of Open Access Journals (Sweden)

    Fauzi Manyuk

    2017-01-01

    Full Text Available Erosion-hazard assessment is an important aspect in the management of a river basin such as Siak River Basin, Riau Province, Indonesia. This study presents an application of fuzzy logic approach to develop erosion risk map based on geographic information system. Fuzzy logic is a computing approach based on “degrees of truth” rather than the usual “true or false” (1 or 0 Boolean logic on which the modern computer is based. The results of the erosion risk map were verified by using field measurements. The verification result shows that the parameter of soil-erodibility (K indicates a good agreement with field measurement data. The classification of soil-erodibility (K as the result of validation were: very low (0.0–0.1, medium (0.21-0.32, high (0.44-0.55 and very high (0.56-0.64. The results obtained from this study show that the erosion risk map of Siak River Basin were dominantly classified as medium level which cover about 68.54%. The other classifications were high and very low erosion level which cover about 28.84% and 2.61% respectively.

  13. Self-tuning fuzzy logic nuclear reactor controller

    International Nuclear Information System (INIS)

    Alang-Rashid, N. K.; Heger, A.S.

    1994-01-01

    A method for self-timing of a fuzzy logic controller (FLC) based on the estimation of the optimum value of the centroids of the its output fuzzy sets is proposed. The method can be implemented on-line and does not modify the membership function and the control rules, thus preserving the description of control statements in their original forms. Results of simulation and actual tests show that the tuning method improves the FLCs performance in following desired reactor power level trajectories (simulation tests) and simple power up and power down experiments (simulation and actual tests). The FLC control rules were derived from control statements expressing the relations between error, rate of error change, and control rod duration and direction of movements

  14. Self-tuning fuzzy logic nuclear reactor controller

    Energy Technology Data Exchange (ETDEWEB)

    Alang-Rashid, N K; Heger, A S

    1994-12-31

    A method for self-timing of a fuzzy logic controller (FLC) based on the estimation of the optimum value of the centroids of the its output fuzzy sets is proposed. The method can be implemented on-line and does not modify the membership function and the control rules, thus preserving the description of control statements in their original forms. Results of simulation and actual tests show that the tuning method improves the FLCs performance in following desired reactor power level trajectories (simulation tests) and simple power up and power down experiments (simulation and actual tests). The FLC control rules were derived from control statements expressing the relations between error, rate of error change, and control rod duration and direction of movements.

  15. LANDSLIDE SUSCEPTIBILITY ASSESSMENT THROUGH FUZZY LOGIC INFERENCE SYSTEM (FLIS

    Directory of Open Access Journals (Sweden)

    T. Bibi

    2016-09-01

    Full Text Available Landslide is among one of the most important natural hazards that lead to modification of the environment. It is a regular feature of a rapidly growing district Mansehra, Pakistan. This caused extensive loss of life and property in the district located at the foothills of Himalaya. Keeping in view the situation it is concluded that besides structural approaches the non-structural approaches such as hazard and risk assessment maps are effective tools to reduce the intensity of damage. A landslide susceptibility map is base for engineering geologists and geomorphologists. However, it is not easy to produce a reliable susceptibility map due to complex nature of landslides. Since 1980s, several mathematical models have been developed to map landslide susceptibility and hazard. Among various models this paper is discussing the effectiveness of fuzzy logic approach for landslide susceptibility mapping in District Mansehra, Pakistan. The factor maps were modified as landslide susceptibility and fuzzy membership functions were assessed for each class. Likelihood ratios are obtained for each class of contributing factors by considering the expert opinion. The fuzzy operators are applied to generate landslide susceptibility maps. According to this map, 17% of the study area is classified as high susceptibility, 32% as moderate susceptibility, 51% as low susceptibility and areas. From the results it is found that the fuzzy model can integrate effectively with various spatial data for landslide hazard mapping, suggestions in this study are hope to be helpful to improve the applications including interpretation, and integration phases in order to obtain an accurate decision supporting layer.

  16. Fuzzy Logic Approach for the Prediction of Dross Formation in CO2 Laser Cutting of Mild Steel

    Directory of Open Access Journals (Sweden)

    Miloš Madić

    2015-11-01

    Full Text Available Dross free laser cutting is very important in the application of laser cutting technology. This paper focuses on the development of a fuzzy logic model to predict dross formation in CO2 laser oxygen cutting of mild steel. Laser cutting experiment, conducted according to Taguchi’s experimental design using L25 orthogonal array, provided a set of data for the development of a fuzzy rule base. The predicting fuzzy logic model is based on using Mamdani-type inference system. Developed fuzzy logic model considered the cutting speed, laser power and assist gas pressure as inputs. Using this model the effects of the selected laser cutting parameters on the dross formation were investigated. Additionally, 3-D surface plots were generated to study the interaction effects of the laser cutting parameters. The analysis revealed that the cutting speed has the most significant effect, followed by laser power and assist gas pressure. The results indicated that the fuzzy logic modeling approach can be effectively used for the dross formation prediction in CO2 laser cutting of mild steel.

  17. Realworld maximum power point tracking simulation of PV system based on Fuzzy Logic control

    Science.gov (United States)

    Othman, Ahmed M.; El-arini, Mahdi M. M.; Ghitas, Ahmed; Fathy, Ahmed

    2012-12-01

    In the recent years, the solar energy becomes one of the most important alternative sources of electric energy, so it is important to improve the efficiency and reliability of the photovoltaic (PV) systems. Maximum power point tracking (MPPT) plays an important role in photovoltaic power systems because it maximize the power output from a PV system for a given set of conditions, and therefore maximize their array efficiency. This paper presents a maximum power point tracker (MPPT) using Fuzzy Logic theory for a PV system. The work is focused on the well known Perturb and Observe (P&O) algorithm and is compared to a designed fuzzy logic controller (FLC). The simulation work dealing with MPPT controller; a DC/DC Ćuk converter feeding a load is achieved. The results showed that the proposed Fuzzy Logic MPPT in the PV system is valid.

  18. Fuzzy logic control of vehicle suspensions with dry friction nonlinearity

    Indian Academy of Sciences (India)

    Fuzzy logic control; active vehicle suspension; suspension space. 1. ... surface unevenness, stability and directional control during handling ..... Burton A W, Truscott A J, Wellstead P E 1995 Analysis, modeling and control of an advanced.

  19. Nonlinear Aerodynamic Modeling From Flight Data Using Advanced Piloted Maneuvers and Fuzzy Logic

    Science.gov (United States)

    Brandon, Jay M.; Morelli, Eugene A.

    2012-01-01

    Results of the Aeronautics Research Mission Directorate Seedling Project Phase I research project entitled "Nonlinear Aerodynamics Modeling using Fuzzy Logic" are presented. Efficient and rapid flight test capabilities were developed for estimating highly nonlinear models of airplane aerodynamics over a large flight envelope. Results showed that the flight maneuvers developed, used in conjunction with the fuzzy-logic system identification algorithms, produced very good model fits of the data, with no model structure inputs required, for flight conditions ranging from cruise to departure and spin conditions.

  20. A novel hybrid evidential belief function-based fuzzy logic model in spatial prediction of rainfall-induced shallow landslides in the Lang Son city area (Vietnam

    Directory of Open Access Journals (Sweden)

    Dieu Tien Bui

    2015-04-01

    Full Text Available The main objective of this study is to investigate potential application of an integrated evidential belief function (EBF-based fuzzy logic model for spatial prediction of rainfall-induced shallow landslides in the Lang Son city area (Vietnam. First, a landslide inventory map was constructed from various sources. Then the landslide inventory map was randomly partitioned as a ratio of 70/30 for training and validation of the models, respectively. Second, six landslide conditioning factors (slope angle, slope aspect, lithology, distance to faults, soil type, land use were prepared and fuzzy membership values for these factors classes were estimated using the EBF. Subsequently, fuzzy operators were used to generate landslide susceptibility maps. Finally, the susceptibility maps were validated and compared using the validation dataset. The results show that the lowest prediction capability is the fuzzy SUM (76.6%. The prediction capability is almost the same for the fuzzy PRODUCT and fuzzy GAMMA models (79.6%. Compared to the frequency-ratio based fuzzy logic models, the EBF-based fuzzy logic models showed better result in both the success rate and prediction rate. The results from this study may be useful for local planner in areas prone to landslides. The modelling approach can be applied for other areas.

  1. Reliability Analysis of Differential Relay as Main Protection Transformer Using Fuzzy Logic Algorithm

    Science.gov (United States)

    Mulyadi, Y.; Sucita, T.; Sumarto; Alpani, M.

    2018-02-01

    Electricity supply demand is increasing every year. It makes PT. PLN (Persero) is required to provide optimal customer service and satisfaction. Optimal service depends on the performance of the equipment of the power system owned, especially the transformer. Power transformer is an electrical equipment that transforms electricity from high voltage to low voltage or vice versa. However, in the electrical power system, is inseparable from interference included in the transformer. But, the disturbance can be minimized by the protection system. The main protection transformer is differential relays. Differential relays working system using Kirchoff law where inflows equal outflows. If there are excessive currents that interfere then the relays will work. But, the relay can also experience decreased performance. Therefore, this final project aims to analyze the reliability of the differential relay on the transformer in three different substations. Referring to the standard applied by the transmission line protection officer, the differential relay shall have slope characteristics of 30% in the first slope and 80% in the second slope when using two slopes and 80% when using one slope with an instant time and the corresponding ratio. So, the results obtained on the Siemens differential release have a reliable slope characteristic with a value of 30 on the fuzzy logic system. In a while, ABB a differential relay is only 80% reliable because two experiments are not reliable. For the time, all the differential relays are instant with a value of 0.06 on the fuzzy logic system. For ratios, the differential relays ABB have a better value than others brand with a value of 151 on the fuzzy logic system.

  2. Risk evaluation in Columbian electricity market using fuzzy logic

    International Nuclear Information System (INIS)

    Medina, S.; Moreno, J.

    2007-01-01

    This article proposes a model based on Fuzzy Logic to evaluate the market risk that a trading agent faces in the electric power negotiation in Colombia, as part of a general model of negotiation. The proposed model considers single external factors as regulatory changes, social and political issues, and the condition of the national transmission net. Variables of the market associated to these risk factors were selected and some graphic and statistical analyses were made in order to check their relationship with the electricity prices and to determine why the experts consider these factors in their analyses. According to the obtained results a Mamdani Fuzzy Inference System which contains the expert knowledge was developed and it is presented in a fuzzy cognitive map. (author)

  3. Noise-based logic: Binary, multi-valued, or fuzzy, with optional superposition of logic states

    Energy Technology Data Exchange (ETDEWEB)

    Kish, Laszlo B. [Texas A and M University, Department of Electrical and Computer Engineering, College Station, TX 77843-3128 (United States)], E-mail: laszlo.kish@ece.tamu.edu

    2009-03-02

    A new type of deterministic (non-probabilistic) computer logic system inspired by the stochasticity of brain signals is shown. The distinct values are represented by independent stochastic processes: independent voltage (or current) noises. The orthogonality of these processes provides a natural way to construct binary or multi-valued logic circuitry with arbitrary number N of logic values by using analog circuitry. Moreover, the logic values on a single wire can be made a (weighted) superposition of the N distinct logic values. Fuzzy logic is also naturally represented by a two-component superposition within the binary case (N=2). Error propagation and accumulation are suppressed. Other relevant advantages are reduced energy dissipation and leakage current problems, and robustness against circuit noise and background noises such as 1/f, Johnson, shot and crosstalk noise. Variability problems are also non-existent because the logic value is an AC signal. A similar logic system can be built with orthogonal sinusoidal signals (different frequency or orthogonal phase) however that has an extra 1/N type slowdown compared to the noise-based logic system with increasing number of N furthermore it is less robust against time delay effects than the noise-based counterpart.

  4. Noise-based logic: Binary, multi-valued, or fuzzy, with optional superposition of logic states

    International Nuclear Information System (INIS)

    Kish, Laszlo B.

    2009-01-01

    A new type of deterministic (non-probabilistic) computer logic system inspired by the stochasticity of brain signals is shown. The distinct values are represented by independent stochastic processes: independent voltage (or current) noises. The orthogonality of these processes provides a natural way to construct binary or multi-valued logic circuitry with arbitrary number N of logic values by using analog circuitry. Moreover, the logic values on a single wire can be made a (weighted) superposition of the N distinct logic values. Fuzzy logic is also naturally represented by a two-component superposition within the binary case (N=2). Error propagation and accumulation are suppressed. Other relevant advantages are reduced energy dissipation and leakage current problems, and robustness against circuit noise and background noises such as 1/f, Johnson, shot and crosstalk noise. Variability problems are also non-existent because the logic value is an AC signal. A similar logic system can be built with orthogonal sinusoidal signals (different frequency or orthogonal phase) however that has an extra 1/N type slowdown compared to the noise-based logic system with increasing number of N furthermore it is less robust against time delay effects than the noise-based counterpart

  5. Noise-based logic: Binary, multi-valued, or fuzzy, with optional superposition of logic states

    Science.gov (United States)

    Kish, Laszlo B.

    2009-03-01

    A new type of deterministic (non-probabilistic) computer logic system inspired by the stochasticity of brain signals is shown. The distinct values are represented by independent stochastic processes: independent voltage (or current) noises. The orthogonality of these processes provides a natural way to construct binary or multi-valued logic circuitry with arbitrary number N of logic values by using analog circuitry. Moreover, the logic values on a single wire can be made a (weighted) superposition of the N distinct logic values. Fuzzy logic is also naturally represented by a two-component superposition within the binary case ( N=2). Error propagation and accumulation are suppressed. Other relevant advantages are reduced energy dissipation and leakage current problems, and robustness against circuit noise and background noises such as 1/f, Johnson, shot and crosstalk noise. Variability problems are also non-existent because the logic value is an AC signal. A similar logic system can be built with orthogonal sinusoidal signals (different frequency or orthogonal phase) however that has an extra 1/N type slowdown compared to the noise-based logic system with increasing number of N furthermore it is less robust against time delay effects than the noise-based counterpart.

  6. Application of fuzzy logic approach for wind erosion hazard mapping in Laghouat region (Algeria) using remote sensing and GIS

    Science.gov (United States)

    Saadoud, Djouher; Hassani, Mohamed; Martin Peinado, Francisco José; Guettouche, Mohamed Saïd

    2018-06-01

    Wind erosion is one of the most serious environmental problems in Algeria that threatens human activities and socio-economic development. The main goal of this study is to apply a fuzzy logic approach to wind erosion sensitivity mapping in the Laghouat region, Algeria. Six causative factors, obtained by applying fuzzy membership functions to each used parameter, are considered: soil, vegetation cover, wind factor, soil dryness, land topography and land cover sensitivity. Different fuzzy operators (AND, OR, SUM, PRODUCT, and GAMMA) are applied to generate wind-erosion hazard map. Success rate curves reveal that the fuzzy gamma (γ) operator, with γ equal to 0.9, gives the best prediction accuracy with an area under curve of 85.2%. The resulting wind-erosion sensitivity map delineates the area into different zones of five relative sensitivity classes: very high, high, moderate, low and very low. The estimated result was verified by field measurements and the high statistically significant value of a chi-square test.

  7. Control of motion stability of the line tracer robot using fuzzy logic and kalman filter

    Science.gov (United States)

    Novelan, M. S.; Tulus; Zamzami, E. M.

    2018-03-01

    Setting of motion and balance line tracer robot two wheels is actually a combination of a two-wheeled robot balance concept and the concept of line follower robot. The main objective of this research is to maintain the robot in an upright and can move to follow the line of the Wizard while maintaining balance. In this study the motion balance system on line tracer robot by considering the presence of a noise, so that it takes the estimator is used to mengestimasi the line tracer robot motion. The estimation is done by the method of Kalman Filter and the combination of Fuzzy logic-Fuzzy Kalman Filter called Kalman Filter, as well as optimal smooting. Based on the results of the study, the value of the output of the fuzzy results obtained from the sensor input value has been filtered before entering the calculation of the fuzzy. The results of the output of the fuzzy logic hasn’t been able to control dc motors are well balanced at the moment to be able to run. The results of the fuzzy logic by using membership function of triangular membership function or yet can control with good dc motor movement in order to be balanced

  8. evaluation of a multi-variable self-learning fuzzy logic controller

    African Journals Online (AJOL)

    Dr Obe

    2003-03-01

    Mar 1, 2003 ... The most challenging aspect of the design of a fuzzy logic controller is ... inaccuracy (or structured uncertainty) and unmodelled ... mathematical analysis on paper is impossible ... output (SISO) system that can self-construct ...

  9. Operational Investigation of Overhead Crane with Fuzzy Logic Anti-Swing Controller Using 3-D Simulation

    Directory of Open Access Journals (Sweden)

    Y. N. Petrenko

    2011-01-01

    Full Text Available The purpose of a crane control system is to provide load transfer with minimum swinging. The paper presents a developed three-dimensional simulation model of a bridge crane with fuzzy logic controller designed with application of genetic algorithms. Comparative indices of oscillation while load transferring are given in the paper. The indices have been obtained at various parameters of the fuzzy logic controller. 

  10. A Fuzzy Logic Approach to Marine Spatial Management

    Science.gov (United States)

    Teh, Lydia C. L.; Teh, Louise S. L.

    2011-04-01

    Marine spatial planning tends to prioritise biological conservation targets over socio-economic considerations, which may incur lower user compliance and ultimately compromise management success. We argue for more inclusion of human dimensions in spatial management, so that outcomes not only fulfill biodiversity and conservation objectives, but are also acceptable to resource users. We propose a fuzzy logic framework that will facilitate this task- The protected area suitability index (PASI) combines fishers' spatial preferences with biological criteria to assess site suitability for protection from fishing. We apply the PASI in a spatial evaluation of a small-scale reef fishery in Sabah, Malaysia. While our results pertain to fishers specifically, the PASI can also be customized to include the interests of other stakeholders and resource users, as well as incorporate varying levels of protection.

  11. Fuzzy logic controller using different inference methods

    International Nuclear Information System (INIS)

    Liu, Z.; De Keyser, R.

    1994-01-01

    In this paper the design of fuzzy controllers by using different inference methods is introduced. Configuration of the fuzzy controllers includes a general rule-base which is a collection of fuzzy PI or PD rules, the triangular fuzzy data model and a centre of gravity defuzzification algorithm. The generalized modus ponens (GMP) is used with the minimum operator of the triangular norm. Under the sup-min inference rule, six fuzzy implication operators are employed to calculate the fuzzy look-up tables for each rule base. The performance is tested in simulated systems with MATLAB/SIMULINK. Results show the effects of using the fuzzy controllers with different inference methods and applied to different test processes

  12. Mapping Shape Geometry And Emotions Using Fuzzy Logic

    DEFF Research Database (Denmark)

    Achiche, Sofiane; Ahmed, Saeema

    2008-01-01

    An important aspect of artifact/product design is defining the aesthetic and emotional value. The success of a product is not only dependent on its functionality but also on the emotional value that it creates to its user. However, if several designers are faced with a task to create an object...... that would evoke a certain emotion (aggressive, soft, heavy, friendly, etc.), each would most likely interpret the emotion with a different set of geometric features and shapes. In this paper the authors propose an approach to formalize the relationship between geometric information of a 3D object...... and the intended emotion using fuzzy logic. To achieve this; 3D objects (shapes) created by design engineering students to match a set of words/emotions were analyzed. The authors identified geometric information as inputs of the fuzzy model and developed a set of fuzzy if/then rules to map the relationships...

  13. Fuzzy Logic Based Control of Power of PEM Fuel Cell System for Residential Application

    Directory of Open Access Journals (Sweden)

    Khaled MAMMAR

    2009-07-01

    Full Text Available This paper presents a dynamic model of Fuel cell system for residential power generation. The models proposed include a fuel cell stack model, reformer model and DC/AC inverter model. Furthermore a fuzzy logic (FLC controller is used to control active power of PEM fuel cell system. The controller modifies the hydrogen flow feedback from the terminal load. Simulation results confirmed the high performance capability of the fuzzy logic controller to control power generation.

  14. Implementation Of Automatic Wiper Speed Control And Headlight Modes Control Systems Using Fuzzy Logic

    OpenAIRE

    ThetKoKo; ZawMyoTun; Hla Myo Tun

    2015-01-01

    Abstract This research paper describes the design and simulation of the automatic wiper speed and headlight modes controllers using fuzzy logic. This proposed system consists of a fuzzy logic controller to control a cars wiper speed and headlight modes. The automatic wiper system detects the rain and its intensity. And according to the rain intensity the wiper speed is automatically controlled. Headlight modes automatically changes either from low beam mode to high beam mode or form high beam...

  15. A Grey Fuzzy Logic Approach for Cotton Fibre Selection

    Science.gov (United States)

    Chakraborty, Shankar; Das, Partha Protim; Kumar, Vidyapati

    2017-06-01

    It is a well known fact that the quality of ring spun yarn predominantly depends on various physical properties of cotton fibre. Any variation in these fibre properties may affect the strength and unevenness of the final yarn. Thus, so as to achieve the desired yarn quality and characteristics, it becomes imperative for the spinning industry personnel to identify the most suitable cotton fibre from a set of feasible alternatives in presence of several conflicting properties/attributes. This cotton fibre selection process can be modelled as a Multi-Criteria Decision Making (MCDM) problem. In this paper, a grey fuzzy logic-based approach is proposed for selection of the most apposite cotton fibre from 17 alternatives evaluated based on six important fibre properties. It is observed that the preference order of the top-ranked cotton fibres derived using the grey fuzzy logic approach closely matches with that attained by the past researchers which proves the application potentiality of this method in solving varying MCDM problems in textile industries.

  16. Gas Turbine Engine Control Design Using Fuzzy Logic and Neural Networks

    Directory of Open Access Journals (Sweden)

    M. Bazazzadeh

    2011-01-01

    Full Text Available This paper presents a successful approach in designing a Fuzzy Logic Controller (FLC for a specific Jet Engine. At first, a suitable mathematical model for the jet engine is presented by the aid of SIMULINK. Then by applying different reasonable fuel flow functions via the engine model, some important engine-transient operation parameters (such as thrust, compressor surge margin, turbine inlet temperature, etc. are obtained. These parameters provide a precious database, which train a neural network. At the second step, by designing and training a feedforward multilayer perceptron neural network according to this available database; a number of different reasonable fuel flow functions for various engine acceleration operations are determined. These functions are used to define the desired fuzzy fuel functions. Indeed, the neural networks are used as an effective method to define the optimum fuzzy fuel functions. At the next step, we propose a FLC by using the engine simulation model and the neural network results. The proposed control scheme is proved by computer simulation using the designed engine model. The simulation results of engine model with FLC illustrate that the proposed controller achieves the desired performance and stability.

  17. Realworld maximum power point tracking simulation of PV system based on Fuzzy Logic control

    Directory of Open Access Journals (Sweden)

    Ahmed M. Othman

    2012-12-01

    Full Text Available In the recent years, the solar energy becomes one of the most important alternative sources of electric energy, so it is important to improve the efficiency and reliability of the photovoltaic (PV systems. Maximum power point tracking (MPPT plays an important role in photovoltaic power systems because it maximize the power output from a PV system for a given set of conditions, and therefore maximize their array efficiency. This paper presents a maximum power point tracker (MPPT using Fuzzy Logic theory for a PV system. The work is focused on the well known Perturb and Observe (P&O algorithm and is compared to a designed fuzzy logic controller (FLC. The simulation work dealing with MPPT controller; a DC/DC Ćuk converter feeding a load is achieved. The results showed that the proposed Fuzzy Logic MPPT in the PV system is valid.

  18. control of a dc motor using fuzzy logic control algorithm

    African Journals Online (AJOL)

    user

    controller in the control performance of an industrial type DC motor using MATLAB. The fuzzy logic .... controlled separately excited permanent magnet DC motor (PMDC). ... When the field current is constant, the flux induced by the field ...

  19. Different control applications on a vehicle using fuzzy logic control

    Indian Academy of Sciences (India)

    Vehicle vibrations; active suspensions; fuzzy logic control; vehicle model. 1. .... The general expression of the mathematical model is shown below: .... Figure 5a presents the time history of the control force when the controller exists only under.

  20. Optimal fuzzy logic-based PID controller for load-frequency control including superconducting magnetic energy storage units

    International Nuclear Information System (INIS)

    Pothiya, Saravuth; Ngamroo, Issarachai

    2008-01-01

    This paper proposes a new optimal fuzzy logic-based-proportional-integral-derivative (FLPID) controller for load frequency control (LFC) including superconducting magnetic energy storage (SMES) units. Conventionally, the membership functions and control rules of fuzzy logic control are obtained by trial and error method or experiences of designers. To overcome this problem, the multiple tabu search (MTS) algorithm is applied to simultaneously tune PID gains, membership functions and control rules of FLPID controller to minimize frequency deviations of the system against load disturbances. The MTS algorithm introduces additional techniques for improvement of search process such as initialization, adaptive search, multiple searches, crossover and restarting process. Simulation results explicitly show that the performance of the optimum FLPID controller is superior to the conventional PID controller and the non-optimum FLPID controller in terms of the overshoot, settling time and robustness against variations of system parameters

  1. A critical study of fuzzy logic as a scientific method in social sciences ...

    African Journals Online (AJOL)

    The logic of the social sciences, from its inception, has been certain and classic. By advent of Fuzzy logic, gradually making use of it was common because of frequent capabilities and applications that in resolving problems of this science was been attributed to it. Changing of logic in a science or epistemic system has many ...

  2. Use of Fuzzy Logic Systems for Assessment of Primary Faults

    Science.gov (United States)

    Petrović, Ivica; Jozsa, Lajos; Baus, Zoran

    2015-09-01

    In electric power systems, grid elements are often subjected to very complex and demanding disturbances or dangerous operating conditions. Determining initial fault or cause of those states is a difficult task. When fault occurs, often it is an imperative to disconnect affected grid element from the grid. This paper contains an overview of possibilities for using fuzzy logic in an assessment of primary faults in the transmission grid. The tool for this task is SCADA system, which is based on information of currents, voltages, events of protection devices and status of circuit breakers in the grid. The function model described with the membership function and fuzzy logic systems will be presented in the paper. For input data, diagnostics system uses information of protection devices tripping, states of circuit breakers and measurements of currents and voltages before and after faults.

  3. Neutral network and fuzzy logic based grate control; Roststyrning med neutrala naetverk och fuzzy logic

    Energy Technology Data Exchange (ETDEWEB)

    Ramstroem, Erik [TPS Termiska Processer AB, Nykoeping (Sweden)

    2002-04-01

    Grate-control is a complex task in many ways. The relations between controlled variables and the values they depend on are mostly unknown. Research projects are going on to create grate models based on physical laws. Those models are too complex for control implementation. The evaluation time is to long for control use. Another fundamental difficulty is that the relationships are none linear. That is, for a specific change in control value, the change in controlled value depends on the original size of control value, process disturbances and controlled values. There are extensive theories for linear process control. Non-linear control theory is used in robotic applications, but not in process and combustion control. The aim of grate control is to use as much of the grate area as possible, without having unburned material in ash. The outlined strategy is: To keep the position of the final bum out zone constant and its extension controlled. The control variables should be primary airflow, distribution of primary air, and fuel flow. Disturbances that should be measured are the fuel moisture content, the temperature of primary air and the grate temperature under the fuel bed. Technologies used are, fuzzy-logic and neural networks. A combination of booth could be used as well as any of them separately. A Fuzzy-logic controller acts as a computerised operator. Rules are specified with 'if - then' thesis. An example of that is: - if temperature is low, then close the valve The boundaries between the rules are made fuzzy. That makes it possible for the temperature to be just a bit low, which makes the valve open a bit. A lot of rules are created so that the controller knows what to do in every situation. Neural networks are sort of multi dimensional curves, with arbitrary degrees of freedom. The nets are used to predict future process values from measured ones. The model is evaluated from collected data. Parameters are adjusted for best correspondence between

  4. Active control of flexible structures using a fuzzy logic algorithm

    Science.gov (United States)

    Cohen, Kelly; Weller, Tanchum; Ben-Asher, Joseph Z.

    2002-08-01

    This study deals with the development and application of an active control law for the vibration suppression of beam-like flexible structures experiencing transient disturbances. Collocated pairs of sensors/actuators provide active control of the structure. A design methodology for the closed-loop control algorithm based on fuzzy logic is proposed. First, the behavior of the open-loop system is observed. Then, the number and locations of collocated actuator/sensor pairs are selected. The proposed control law, which is based on the principles of passivity, commands the actuator to emulate the behavior of a dynamic vibration absorber. The absorber is tuned to a targeted frequency, whereas the damping coefficient of the dashpot is varied in a closed loop using a fuzzy logic based algorithm. This approach not only ensures inherent stability associated with passive absorbers, but also circumvents the phenomenon of modal spillover. The developed controller is applied to the AFWAL/FIB 10 bar truss. Simulated results using MATLAB© show that the closed-loop system exhibits fairly quick settling times and desirable performance, as well as robustness characteristics. To demonstrate the robustness of the control system to changes in the temporal dynamics of the flexible structure, the transient response to a considerably perturbed plant is simulated. The modal frequencies of the 10 bar truss were raised as well as lowered substantially, thereby significantly perturbing the natural frequencies of vibration. For these cases, too, the developed control law provides adequate settling times and rates of vibrational energy dissipation.

  5. Optimizing biological waste water cleaning by means of modern control systems (fuzzy logic); Optimierung der biologischen Abwasserreinigung durch moderne Regelsysteme (Fuzzy-Logik)

    Energy Technology Data Exchange (ETDEWEB)

    Lohse, M.; Boening, T.; Hegemann, G. [Fachhochschule Muenster (Germany). Inst. fuer Abfall- und Abwasserwirtschaft e.V.

    1999-07-01

    Within the framework of a project sponsored by EUREGIO, test series with the biological activation stages of a German and a Dutch sewage treatment plant each are carried out using different process concepts for the control of oxygen supply by fuzzy logic. As the currently available results demonstrate, the developed fuzzy-logic fields of characteristic curves permit establishing a stable and, thus, little energy-consuming process with optimum oxygen supply in comparison with conventional control. (orig.) [German] Im Rahmen eines von der EUREGIO gefoerderten Forschungsprojektes werden Versuchsreihen im Bereich der biologischen Belebungsstufen einer deutschen und einer niederlaendischen Abwasserreinigungsanlage (ARA) mit unterschiedlichen Verfahrenskonzepten hinsichtlich der Regelung der Sauerstoffzufuhr mit Hilfe der Fuzzy-Logik Technik durchgefuehrt. Die bisherigen Versuchsergebnisse zeigen, dass - im Vergleich zur konventionellen Regelung - durch die entwickelten Fuzzy-Logik Kennfelder ein stabiler und damit energiearmer Prozess mit optimaler Sauerstoffzufuhr erzeugt wird. (orig.)

  6. Artificial intelligence/fuzzy logic method for analysis of combined signals from heavy metal chemical sensors

    International Nuclear Information System (INIS)

    Turek, M.; Heiden, W.; Riesen, A.; Chhabda, T.A.; Schubert, J.; Zander, W.; Krueger, P.; Keusgen, M.; Schoening, M.J.

    2009-01-01

    The cross-sensitivity of chemical sensors for several metal ions resembles in a way the overlapping sensitivity of some biological sensors, like the optical colour receptors of human retinal cone cells. While it is difficult to assign crisp classification values to measurands based on complex overlapping sensory signals, fuzzy logic offers a possibility to mathematically model such systems. Current work goes into the direction of mixed heavy metal solutions and the combination of fuzzy logic with heavy metal-sensitive, silicon-based chemical sensors for training scenarios of arbitrary sensor/probe combinations in terms of an electronic tongue. Heavy metals play an important role in environmental analysis. As trace elements as well as water impurities released from industrial processes they occur in the environment. In this work, the development of a new fuzzy logic method based on potentiometric measurements performed with three different miniaturised chalcogenide glass sensors in different heavy metal solutions will be presented. The critical validation of the developed fuzzy logic program will be demonstrated by means of measurements in unknown single- and multi-component heavy metal solutions. Limitations of this program and a comparison between calculated and expected values in terms of analyte composition and heavy metal ion concentration will be shown and discussed.

  7. Artificial intelligence/fuzzy logic method for analysis of combined signals from heavy metal chemical sensors

    Energy Technology Data Exchange (ETDEWEB)

    Turek, M. [Institute of Nano- and Biotechnologies (INB), Aachen University of Applied Sciences, Campus Juelich, Juelich (Germany); Institute of Bio- and Nanosystems (IBN), Research Centre Juelich GmbH, Juelich (Germany); Heiden, W.; Riesen, A. [Bonn-Rhein-Sieg University of Applied Sciences, Sankt Augustin (Germany); Chhabda, T.A. [Institute of Nano- and Biotechnologies (INB), Aachen University of Applied Sciences, Campus Juelich, Juelich (Germany); Schubert, J.; Zander, W. [Institute of Bio- and Nanosystems (IBN), Research Centre Juelich GmbH, Juelich (Germany); Krueger, P. [Institute of Biochemistry and Molecular Biology, RWTH Aachen, Aachen (Germany); Keusgen, M. [Institute for Pharmaceutical Chemistry, Philipps-University Marburg, Marburg (Germany); Schoening, M.J. [Institute of Nano- and Biotechnologies (INB), Aachen University of Applied Sciences, Campus Juelich, Juelich (Germany); Institute of Bio- and Nanosystems (IBN), Research Centre Juelich GmbH, Juelich (Germany)], E-mail: m.j.schoening@fz-juelich.de

    2009-10-30

    The cross-sensitivity of chemical sensors for several metal ions resembles in a way the overlapping sensitivity of some biological sensors, like the optical colour receptors of human retinal cone cells. While it is difficult to assign crisp classification values to measurands based on complex overlapping sensory signals, fuzzy logic offers a possibility to mathematically model such systems. Current work goes into the direction of mixed heavy metal solutions and the combination of fuzzy logic with heavy metal-sensitive, silicon-based chemical sensors for training scenarios of arbitrary sensor/probe combinations in terms of an electronic tongue. Heavy metals play an important role in environmental analysis. As trace elements as well as water impurities released from industrial processes they occur in the environment. In this work, the development of a new fuzzy logic method based on potentiometric measurements performed with three different miniaturised chalcogenide glass sensors in different heavy metal solutions will be presented. The critical validation of the developed fuzzy logic program will be demonstrated by means of measurements in unknown single- and multi-component heavy metal solutions. Limitations of this program and a comparison between calculated and expected values in terms of analyte composition and heavy metal ion concentration will be shown and discussed.

  8. Normal Forms for Fuzzy Logics: A Proof-Theoretic Approach

    Czech Academy of Sciences Publication Activity Database

    Cintula, Petr; Metcalfe, G.

    2007-01-01

    Roč. 46, č. 5-6 (2007), s. 347-363 ISSN 1432-0665 R&D Projects: GA MŠk(CZ) 1M0545 Institutional research plan: CEZ:AV0Z10300504 Keywords : fuzzy logic * normal form * proof theory * hypersequents Subject RIV: BA - General Mathematics Impact factor: 0.620, year: 2007

  9. Application of ANN and fuzzy logic algorithms for streamflow ...

    Indian Academy of Sciences (India)

    The present study focusses on development of models using ANN and fuzzy logic (FL) algorithm for predicting the streamflow for catchment of Savitri River Basin. The input vector to these models were daily rainfall, mean daily evaporation, mean daily temperature and lag streamflow used. In the present study, 20 years ...

  10. A Fuzzy Logic Framework for Integrating Multiple Learned Models

    Energy Technology Data Exchange (ETDEWEB)

    Hartog, Bobi Kai Den [Univ. of Nebraska, Lincoln, NE (United States)

    1999-03-01

    The Artificial Intelligence field of Integrating Multiple Learned Models (IMLM) explores ways to combine results from sets of trained programs. Aroclor Interpretation is an ill-conditioned problem in which trained programs must operate in scenarios outside their training ranges because it is intractable to train them completely. Consequently, they fail in ways related to the scenarios. We developed a general-purpose IMLM solution, the Combiner, and applied it to Aroclor Interpretation. The Combiner's first step, Scenario Identification (M), learns rules from very sparse, synthetic training data consisting of results from a suite of trained programs called Methods. S1 produces fuzzy belief weights for each scenario by approximately matching the rules. The Combiner's second step, Aroclor Presence Detection (AP), classifies each of three Aroclors as present or absent in a sample. The third step, Aroclor Quantification (AQ), produces quantitative values for the concentration of each Aroclor in a sample. AP and AQ use automatically learned empirical biases for each of the Methods in each scenario. Through fuzzy logic, AP and AQ combine scenario weights, automatically learned biases for each of the Methods in each scenario, and Methods' results to determine results for a sample.

  11. Fuzzy set classifier for waste classification tracking

    International Nuclear Information System (INIS)

    Gavel, D.T.

    1992-01-01

    We have developed an expert system based on fuzzy logic theory to fuse the data from multiple sensors and make classification decisions for objects in a waste reprocessing stream. Fuzzy set theory has been applied in decision and control applications with some success, particularly by the Japanese. We have found that the fuzzy logic system is rather easy to design and train, a feature that can cut development costs considerably. With proper training, the classification accuracy is quite high. We performed several tests sorting radioactive test samples using a gamma spectrometer to compare fuzzy logic to more conventional sorting schemes

  12. Fuzzy logic and its possibility using in automation of small-scale hydroelectric power plants regulation

    International Nuclear Information System (INIS)

    Puskajler, J.

    2004-01-01

    The paper explains how can computer understand and process inaccurate (indefinite) information. It is processing of terms like e.g. 'around in the middle of month' or 'not too big'. Fuzzy logic, fuzzy sets, operations with them, fuzzy rules and using of linguistics variables are explained. The possibilities of application of fuzzy systems in automation of regulation of small-scale hydro power plants are discussed. (author)

  13. Conditioning of high voltage radio frequency cavities by using fuzzy logic in connection with rule based programming

    CERN Document Server

    Perréard, S

    1993-01-01

    Many processes are controlled by experts using some kind of mental model to decide actions and make conclusions. This model, based on heuristic knowledge, can often be conveniently represented in rules and has not to be particularly accurate. This is the case for the problem of conditioning high voltage radio-frequency cavities: the expert has to decide, by observing some criteria, if he can increase or if he has to decrease the voltage and by how much. A program has been implemented which can be applied to a class of similar problems. The kernel of the program is a small rule base, which is independent of the kind of cavity. To model a specific cavity, we use fuzzy logic which is implemented as a separate routine called by the rule base. We use fuzzy logic to translate from numeric to symbolic information. The example we chose for applying this kind of technique can be implemented by sequential programming. The two versions exist for comparison. However, we believe that this kind of programming can be powerf...

  14. Looking for Oriental fundamentals Fuzzy Logic

    Directory of Open Access Journals (Sweden)

    Angel Garrido

    2013-10-01

    Full Text Available For quite some time we have been trying to trace the river of Non-ClassicalLogics, and especially, Fuzzy Logic, trying to find the sources of this today flowing quite mighty river. Following from Lotfi A. Zadeh, we have traced his inspiring, the Polish logician Jan Lukasiewicz, who in turn was inspired by Aristotle's Peri Hermeneias (De Interpretatione. Also, Lukasiewicz occupies a central position in the Lvov-Warsaw School, who founded Kazimierz Twardowski, a student of Franz Brentano, and this in turn disciple of Bernard Bolzano. The connection with Leibniz and Bolzano come through medieval scholastic thinkers, especially John Duns Scotus and William of Ockham and the problem of future contingents, they had collected from the Aristotelian tradition. But there was to trace the “eastern (oriental track, which leads to the ancient Chinese and Indian philosophy. Here we will treat it as a first and necessary approach.

  15. Fuzzy logic controller to improve powerline communication

    Science.gov (United States)

    Tirrito, Salvatore

    2015-12-01

    The Power Line Communications (PLC) technology allows the use of the power grid in order to ensure the exchange of data information among devices. This work proposes an approach, based on Fuzzy Logic, that dynamically manages the amplitude of the signal, with which each node transmits, by processing the master-slave link quality measured and the master-slave distance. The main objective of this is to reduce both the impact of communication interferences induced and power consumption.

  16. Modelling of the automatic stabilization system of the aircraft course by a fuzzy logic method

    Science.gov (United States)

    Mamonova, T.; Syryamkin, V.; Vasilyeva, T.

    2016-04-01

    The problem of the present paper concerns the development of a fuzzy model of the system of an aircraft course stabilization. In this work modelling of the aircraft course stabilization system with the application of fuzzy logic is specified. Thus the authors have used the data taken for an ordinary passenger plane. As a result of the study the stabilization system models were realised in the environment of Matlab package Simulink on the basis of the PID-regulator and fuzzy logic. The authors of the paper have shown that the use of the method of artificial intelligence allows reducing the time of regulation to 1, which is 50 times faster than the time when standard receptions of the management theory are used. This fact demonstrates a positive influence of the use of fuzzy regulation.

  17. Logic-based hierarchies for modeling behavior of complex dynamic systems with applications

    International Nuclear Information System (INIS)

    Hu, Y.S.; Modarres, M.

    2000-01-01

    Most complex systems are best represented in the form of a hierarchy. The Goal Tree Success Tree and Master Logic Diagram (GTST-MLD) are proven powerful hierarchic methods to represent complex snap-shot of plant knowledge. To represent dynamic behaviors of complex systems, fuzzy logic is applied to replace binary logic to extend the power of GTST-MLD. Such a fuzzy-logic-based hierarchy is called Dynamic Master Logic Diagram (DMLD). This chapter discusses comparison of the use of GTST-DMLD when applied as a modeling tool for systems whose relationships are modeled by either physical, binary logical or fuzzy logical relationships. This is shown by applying GTST-DMLD to the Direct Containment Heating (DCH) phenomenon at pressurized water reactors which is an important safety issue being addressed by the nuclear industry. (orig.)

  18. Environmental impact assessment procedure: A new approach based on fuzzy logic

    International Nuclear Information System (INIS)

    Peche, Roberto; Rodriguez, Esther

    2009-01-01

    The information related to the different environmental impacts produced by the execution of activities and projects is often limited, described by semantic variables and, affected by a high degree of inaccuracy and uncertainty, thereby making fuzzy logic a suitable tool with which to express and treat this information. The present study proposes a new approach based on fuzzy logic to carry out the environmental impact assessment (EIA) of these activities and projects. Firstly, a set of impact properties is stated and two nondimensional parameters - ranging from 0 to 100 -are assigned, (p i ) to assess the value of the property and (v i ) to assess its contribution to each environmental impact. Next, the impact properties are described by means of fuzzy numbers p i - using generalised confidence intervals. Then, a procedure based on fuzzy arithmetic is developed to define the assessment functions v-bar = f(p-bar) - conventional mathematical functions, which incorporate the knowledge of these impact properties and give the fuzzy values v i - corresponding to each p i - . Subsequently, the fuzzy value of each environmental impact V-bar is estimated by aggregation of the values v i - , in order to obtain the total positive and negative environmental impacts V +- and V -- and, later - from them - the total environmental impact of the activity or project TV - . Finally, the defuzzyfication of TV - leads to a punctual impact estimator TV (1) - a conventional EI estimation - and its corresponding uncertainty interval estimator {(δ l (TV - ),δ r (TV - )}, which represent the total value of the environmental impact caused by the execution of the considered activity or project.

  19. Comparison of Sliding Mode Control and Fuzzy Logic control applied to Variable Speed Wind Energy Conversion Systems

    Directory of Open Access Journals (Sweden)

    Souhila Rached Zine

    2015-08-01

    Full Text Available wind energy features prominently as a supplementary energy booster. It does not pollute and is inexhaustible. However, its high cost is a major constraint, especially on the less windy sites. The purpose of wind energy systems is to maximize energy efficiency, and extract maximum power from the wind speed. In This case, the MPPT control becomes important. To realize this control, strategy conventional Proportional and Integral (PI controller is usually used. However, this strategy cannot achieve better performance. This paper proposes other control methods of a turbine which optimizes its production such as fuzzy logic, sliding mode control. These methods improve the quality and energy efficiency. The proposed Sliding Mode Control (SMC strategy and the fuzzy controllers have presented attractive features such as robustness to parametric uncertainties of the turbine, simplicity of its design and good performances. The simulation result under Matlab\\Simulink has validated the performance of the proposed MPPT strategies.

  20. Application of fuzzy logic in nuclear reactor control Part I: An assessment of state-of-the-art

    International Nuclear Information System (INIS)

    Herger, A.S.; Jamshidl, M.; Alang-Rashid, N.K.

    1995-01-01

    This article discusses the application of fuzzy logic to nuclear reactor control. The method has been suggested by many investigators in many control applications. Reviews of the application of fuzzy logic in process control are given by Tong and Sugeno. Because fuzzy logic control (FLC) provides a pathway for transforming human abstractions into the numerical domain, it has the potential to assist nuclear reactor operators in the control room. With this transformation, linguistically expressed control principles can be coded into the fuzzy controller rule base. Having acquired the skill of the operators, the FLC can assist an operator in controlling the complex system. The thrust of FLC is to derive a conceptual model of the control operation, without expressing the process as mathematical equations, to assist the human operator in interpreting incoming plant variables and arriving at a proper control action. To introduce the concept of FLC in nuclear reactor operation, an overview of the mythology and a review of its application in both nuclear and nonnuclear control application domains are presented along with subsequent discussion of fuzzy logic controllers, their structures, and their method of information processing. The article concludes with the application of a tunable FLC to a typical reactor control problem

  1. Application of fuzzy logic in nuclear reactor control: Part 1: An assessment of state-of-the-art

    International Nuclear Information System (INIS)

    Heger, A.S.; Alang-Rashid, N.K.; Jamshidi, M.

    1995-01-01

    This article discusses the application of fuzzy logic of nuclear reactor control. The method has been suggested by many investigators in many control applications. Reviews of the application of fuzzy logic in process control are given by Tong and Sugeno. Because fuzzy logic control (FLC) provides a pathway for transforming human abstractions into the numerical domain, it has the potential to assist nuclear reactor operators in the control room. With this transformation, linguistically expressed control principles can be coded into the fuzzy controller rule base. Having acquired the skill of he operators, the FLC can assist an operator in controlling the complex system. The thrust of FLC is to derive a conceptual model of the control operation, without expressing the process as mathematical equations, to assist the human operator in interpreting incoming plant variables and arriving at a proper control action. To introduce the concept of FLC in nuclear reactor operation, an overview of the mythology and a review of its application in both nuclear and nonnuclear control application domains are presented along with subsequent discussion of fuzzy logic controllers, their structures, and their method of information processing. The article concludes with the application of a tunable FLC to a typical reactor control problem. 49 refs., 9 figs., 3 tabs

  2. Geo-Spatial Tactical Decision Aid Systems: Fuzzy Logic for Supporting Decision Making

    National Research Council Canada - National Science Library

    Grasso, Raffaele; Giannecchini, Simone

    2006-01-01

    .... This paper describes a tactical decision aid system based on fuzzy logic reasoning for data fusion and on current Open Geospatial Consortium specifications for interoperability, data dissemination...

  3. Depth Control of Sevofluorane Anesthesia with Microcontroller Based Fuzzy Logic System

    National Research Council Canada - National Science Library

    Yardimci, A

    2001-01-01

    ... at the end of the anesthesia. In this study, sevofluorane depth of anesthesia was examined through a microcontroller-based fuzzy logic control system according to the blood pressure and heart rate taken from the patient...

  4. MRI definition of target volumes using fuzzy logic method for three-dimensional conformal radiation therapy

    International Nuclear Information System (INIS)

    Caudrelier, Jean-Michel; Vial, Stephane; Gibon, David; Kulik, Carine; Fournier, Charles; Castelain, Bernard; Coche-Dequeant, Bernard; Rousseau, Jean

    2003-01-01

    Purpose: Three-dimensional (3D) volume determination is one of the most important problems in conformal radiation therapy. Techniques of volume determination from tomographic medical imaging are usually based on two-dimensional (2D) contour definition with the result dependent on the segmentation method used, as well as on the user's manual procedure. The goal of this work is to describe and evaluate a new method that reduces the inaccuracies generally observed in the 2D contour definition and 3D volume reconstruction process. Methods and Materials: This new method has been developed by integrating the fuzziness in the 3D volume definition. It first defines semiautomatically a minimal 2D contour on each slice that definitely contains the volume and a maximal 2D contour that definitely does not contain the volume. The fuzziness region in between is processed using possibility functions in possibility theory. A volume of voxels, including the membership degree to the target volume, is then created on each slice axis, taking into account the slice position and slice profile. A resulting fuzzy volume is obtained after data fusion between multiorientation slices. Different studies have been designed to evaluate and compare this new method of target volume reconstruction and a classical reconstruction method. First, target definition accuracy and robustness were studied on phantom targets. Second, intra- and interobserver variations were studied on radiosurgery clinical cases. Results: The absolute volume errors are less than or equal to 1.5% for phantom volumes calculated by the fuzzy logic method, whereas the values obtained with the classical method are much larger than the actual volumes (absolute volume errors up to 72%). With increasing MRI slice thickness (1 mm to 8 mm), the phantom volumes calculated by the classical method are increasing exponentially with a maximum absolute error up to 300%. In contrast, the absolute volume errors are less than 12% for phantom

  5. Spatial analysis of Ardabil plain aquifer potable groundwater using fuzzy logic

    Directory of Open Access Journals (Sweden)

    Mehdi Kord

    2014-04-01

    Full Text Available The purpose of this study is to evaluate the quality of drinking water and qualitative classification of potable water in Ardabil plain aquifer. To determine the chemical properties 58 water samples were collected from wells and analyzed. Distribution of each quality parameter was estimated using data driven techniques of kriging and fuzzy logic modeling. According to the obtained results, the fuzzy model provides better results compared to kriging. Different water quality standards are used for assessment of drinking water. The quantitative limits specified in these standards and also water quality data are associated with uncertainty. To reduce the uncertainty a fuzzy based decision making approach was applied for interpretation of groundwater quality. Final output was presented in the form of a zoning map with three categories as ‘Desirable’, ‘Acceptable’ and ‘Not acceptable’. This map indicates that most parts of the aquifer have acceptable and desirable water quality for drinking; but the groundwater in the Southwest and North of the plain, being in conformity with Miocene formations, is undesirable (Not acceptable. This spatial distribution map can help a lot for groundwater supply and offers a good insight of groundwater qualitative trend in this study area.

  6. Fuzzy logic for business, finance, and management

    CERN Document Server

    Bojadziev, George

    1997-01-01

    This is an interdisciplinary book for knowledge workers in business, finance, management, and socio-economic sciences. It provides a guide to and techniques for forecasting, decision making, conclusions, and evaluations in an environment involving uncertainty, vagueness, and impression. Traditional modeling techniques do not capture the nature of complex systems especially when humans are involved. Fuzzy logic provides effective tools for dealing with such systems. Emphasis is on applications presented in case studies including Time Forecasting for Project Management, New Product Pricing, Clie

  7. a fuzzy logic approach to non-linearity problem of load frequency

    African Journals Online (AJOL)

    user

    2016-07-03

    Jul 3, 2016 ... reduction in settling time, percent overshoot and steady state error. Keywords: fuzzy logic ... power system to regain a state of operating equilibrium given ... power system depends basically on the active (real) power balance ...

  8. Pneumatic motor speed control by trajectory tracking fuzzy logic

    Indian Academy of Sciences (India)

    In this study, trajectory tracking fuzzy logic controller (TTFLC) is proposed for the speed control of a pneumatic motor (PM). A third order trajectory is defined to determine the trajectory function that has to be tracked by the PM speed. Genetic algorithm (GA) is used to find the TTFLC boundary values of membership functions ...

  9. A Fuzzy Logic Prompting Mechanism Based on Pattern Recognition and Accumulated Activity Effective Index Using a Smartphone Embedded Sensor

    Directory of Open Access Journals (Sweden)

    Chung-Tse Liu

    2016-08-01

    Full Text Available Sufficient physical activity can reduce many adverse conditions and contribute to a healthy life. Nevertheless, inactivity is prevalent on an international scale. Improving physical activity is an essential concern for public health. Reminders that help people change their health behaviors are widely applied in health care services. However, timed-based reminders deliver periodic prompts suffer from flexibility and dependency issues which may decrease prompt effectiveness. We propose a fuzzy logic prompting mechanism, Accumulated Activity Effective Index Reminder (AAEIReminder, based on pattern recognition and activity effective analysis to manage physical activity. AAEIReminder recognizes activity levels using a smartphone-embedded sensor for pattern recognition and analyzing the amount of physical activity in activity effective analysis. AAEIReminder can infer activity situations such as the amount of physical activity and days spent exercising through fuzzy logic, and decides whether a prompt should be delivered to a user. This prompting system was implemented in smartphones and was used in a short-term real-world trial by seventeenth participants for validation. The results demonstrated that the AAEIReminder is feasible. The fuzzy logic prompting mechanism can deliver prompts automatically based on pattern recognition and activity effective analysis. AAEIReminder provides flexibility which may increase the prompts’ efficiency.

  10. Fuzzy logic control of vehicle suspensions with dry friction nonlinearity

    Indian Academy of Sciences (India)

    We design and investigate the performance of fuzzy logic-controlled (FLC) active suspensions on a nonlinear vehicle model with four degrees of freedom, without causing any degeneration in suspension working limits. Force actuators were mounted parallel to the suspensions. In this new approach, linear combinations of ...

  11. Simulating Shopper Behavior using Fuzzy Logic in Shopping Center Simulation

    Directory of Open Access Journals (Sweden)

    Jason Christian

    2016-12-01

    Full Text Available To simulate real-world phenomena, a computer tool can be used to run a simulation and provide a detailed report. By using a computer-aided simulation tool, we can retrieve information relevant to the simulated subject in a relatively short time. This study is an extended and complete version of an initial research done by Christian and Hansun and presents a prototype of a multi-agent shopping center simulation tool along with a fuzzy logic algorithm implemented in the system. Shopping centers and all their components are represented in a simulated 3D environment. The simulation tool was created using the Unity3D engine to build the 3D environment and to run the simulation. To model and simulate the behavior of agents inside the simulation, a fuzzy logic algorithm that uses the agents’ basic knowledge as input was built to determine the agents’ behavior inside the system and to simulate human behaviors as realistically as possible.

  12. Risk Assessment in Underground Coalmines Using Fuzzy Logic in the Presence of Uncertainty

    Science.gov (United States)

    Tripathy, Debi Prasad; Ala, Charan Kumar

    2018-04-01

    Fatal accidents are occurring every year as regular events in Indian coal mining industry. To increase the safety conditions, it has become a prerequisite to performing a risk assessment of various operations in mines. However, due to uncertain accident data, it is hard to conduct a risk assessment in mines. The object of this study is to present a method to assess safety risks in underground coalmines. The assessment of safety risks is based on the fuzzy reasoning approach. Mamdani fuzzy logic model is developed in the fuzzy logic toolbox of MATLAB. A case study is used to demonstrate the applicability of the developed model. The summary of risk evaluation in case study mine indicated that mine fire has the highest risk level among all the hazard factors. This study could help the mine management to prepare safety measures based on the risk rankings obtained.

  13. Improved Fuzzy Logic based DTC of Induction machine for wide range of speed control using AI based controllers

    Directory of Open Access Journals (Sweden)

    H. Sudheer

    2016-06-01

    Full Text Available This paper presents improvements in Direct Torque control of induction motor using Fuzzy logic switching controller (FDTC. The conventional DTC (CDTC and FDTC drive performance is compared using Conventional PI, Fuzzy controller and Neural Network controllers. The major disadvantages of CDTC are high torque and flux ripples in steady state operation of the drive, inferior performance at low speed operation and variable switching frequency. The presence of hysteresis bands is the major reason for high torque and flux ripples in CDTC. In FDTC the hysteresis band and switching table are replaced by Fuzzy logic switching controller. Using fuzzy logic torque, stator flux space are divided into smaller subsections which results in precise and optimal selection of switching state to meet load torque. In high performance drives accurate tuning of PI speed controller is required. The conventional PI controller cannot adapt to the variation in model parameters. Artificial intelligence based fuzzy controller and neural network controller are compared with PI controller for both CDTC and FDTC of Induction machine. The proposed schemes are developed in Matlab/Simulink environment. Simulation results shows reduction in torque and flux ripples in FDTC and dynamic performance of the drive at low speeds and sudden change in load torque can be improved using Fuzzy logic controller compared to PI and neural network controller.

  14. Multi input-output fuzzy logic smart controller for a residential hybrid solar-wind-storage energy system

    International Nuclear Information System (INIS)

    Derrouazin, A.; Aillerie, M.; Mekkakia-Maaza, N.; Charles, J.-P.

    2017-01-01

    Highlights: • We present a fuzzy smart controller for hybrid renewable and conventional energy system. • The rules are based on human intelligence and implemented in the smart controller. • Efficient tracking capability of the proposed controller is proofed in this paper by an example. • Excess produced renewable energy is converted to hydrogen for household use . • Considerable electric grid energy saving is highlighted in the proposed controller system. - Abstract: This study concerns the conception and development of an efficient multi input-output fuzzy logic smart controller, to manage the energy flux of a sustainable hybrid power system, based on renewable power sources, integrating solar panels and a wind turbine associated with storage, applied to a typical residential habitat. In the suggested topology, the energy surplus is redirected to an electrolysis system to produce hydrogen suitable for household utilities. To assume a constant access to electricity in case of consumption peak, connection to the grid is also considered as an exceptional rescue resource. The objective of the presented controller is to exploit instantaneously the produced renewable electric energy and insure savings of electric grid energy. The proposed multi input-output fuzzy logic smart controller has been achieved and verified, outcome switches command signals are discussed and the renewable energy system integration ratio is highlighted.

  15. A fuzzy logic intelligent diagnostic system for spacecraft integrated vehicle health management

    Science.gov (United States)

    Wu, G. Gordon

    1995-01-01

    Due to the complexity of future space missions and the large amount of data involved, greater autonomy in data processing is demanded for mission operations, training, and vehicle health management. In this paper, we develop a fuzzy logic intelligent diagnostic system to perform data reduction, data analysis, and fault diagnosis for spacecraft vehicle health management applications. The diagnostic system contains a data filter and an inference engine. The data filter is designed to intelligently select only the necessary data for analysis, while the inference engine is designed for failure detection, warning, and decision on corrective actions using fuzzy logic synthesis. Due to its adaptive nature and on-line learning ability, the diagnostic system is capable of dealing with environmental noise, uncertainties, conflict information, and sensor faults.

  16. Human action quality evaluation based on fuzzy logic with application in underground coal mining.

    Science.gov (United States)

    Ionica, Andreea; Leba, Monica

    2015-01-01

    The work system is defined by its components, their roles and the relationships between them. Any work system gravitates around the human resource and the interdependencies between human factor and the other components of it. Researches in this field agreed that the human factor and its actions are difficult to quantify and predict. The objective of this paper is to apply a method of human actions evaluation in order to estimate possible risks and prevent possible system faults, both at human factor level and at equipment level. In order to point out the importance of the human factor influence on all the elements of the working systems we propose a fuzzy logic based methodology for quality evaluation of human actions. This methodology has a multidisciplinary character, as it gathers ideas and methods from: quality management, ergonomics, work safety and artificial intelligence. The results presented refer to a work system with a high degree of specificity, namely, underground coal mining and are valuable for human resources risk evaluation pattern. The fuzzy logic evaluation of the human actions leads to early detection of possible dangerous evolutions of the work system and alarm the persons in charge.

  17. Turkey's short-term gross annual electricity demand forecast by fuzzy logic approach

    Energy Technology Data Exchange (ETDEWEB)

    Kucukali, Serhat [Civil Engineering Department, Zonguldak Karaelmas University, Incivez 67100, Zonguldak (Turkey); Baris, Kemal [Mining Engineering Department, Zonguldak Karaelmas University, Incivez 67100, Zonguldak (Turkey)

    2010-05-15

    This paper aims to forecast Turkey's short-term gross annual electricity demand by applying fuzzy logic methodology while general information on economical, political and electricity market conditions of the country is also given. Unlike most of the other forecast models about Turkey's electricity demand, which usually uses more than one parameter, gross domestic product (GDP) based on purchasing power parity was the only parameter used in the model. Proposed model made good predictions and captured the system dynamic behavior covering the years of 1970-2014. The model yielded average absolute relative errors of 3.9%. Furthermore, the model estimates a 4.5% decrease in electricity demand of Turkey in 2009 and the electricity demand growth rates are projected to be about 4% between 2010 and 2014. It is concluded that forecasting the Turkey's short-term gross electricity demand with the country's economic performance will provide more reliable projections. Forecasting the annual electricity consumption of a country could be made by any designer with the help of the fuzzy logic procedure described in this paper. The advantage of this model lies on the ability to mimic the human thinking and reasoning. (author)

  18. Water quality index development using fuzzy logic: A case study of ...

    African Journals Online (AJOL)

    Water quality index development using fuzzy logic: A case study of the Karoon River of Iran. ... PROMOTING ACCESS TO AFRICAN RESEARCH ... Determination of the status of water quality of a river or any other water source is highly ...

  19. Construction of a fuzzy and all Boolean logic gates based on DNA

    DEFF Research Database (Denmark)

    M. Zadegan, Reza; Jepsen, Mette D E; Hildebrandt, Lasse

    2015-01-01

    to the operation of the six Boolean logic gates AND, NAND, OR, NOR, XOR, and XNOR. The logic gate complex is shown to work also when implemented in a three-dimensional DNA origami box structure, where it controlled the position of the lid in a closed or open position. Implementation of multiple microRNA sensitive...... DNA locks on one DNA origami box structure enabled fuzzy logical operation that allows biosensing of complex molecular signals. Integrating logic gates with DNA origami systems opens a vast avenue to applications in the fields of nanomedicine for diagnostics and therapeutics....

  20. A New Control Strategy Based Multi Converter UPQC Using Fuzzy Logic Controller to Improve the Power Quality Issues

    Directory of Open Access Journals (Sweden)

    Chandra Babu Paduchuri

    2014-01-01

    Full Text Available A design of multiconverter unified power quality conditioner to improve the power quality issues is presents in this paper. Modified SRF theory and fuzzy logic controller technique are incorporated in this modelling. This newly designed controller is connected to a source in order to compensate voltage and current in the two feeders. The expanded concept of UPQC is multi converter-UPQC; this system has two series voltage source converter (VSC and one shunt VSC connected back to back. In the proposed system, the power can be conveyed from one feeder to another in order to mitigate the voltage sag, swell, interruption and transient response of the system. The control strategies of multi converter-UPQC are designed based on the modified synchronous reference frame theory with fuzzy logic controller. The transient response of the fuzzy logic controller in dc-link voltage controller will be very fast. The relevant simulation and compensation performance analysis of multi converter-UPQC with fuzzy logic controller is performed using MATLAB/Simulink software.

  1. Rule-bases construction through self-learning for a table-based Sugeno-Takagi fuzzy logic control system

    Directory of Open Access Journals (Sweden)

    C. Boldisor

    2009-12-01

    Full Text Available A self-learning based methodology for building the rule-base of a fuzzy logic controller (FLC is presented and verified, aiming to engage intelligent characteristics to a fuzzy logic control systems. The methodology is a simplified version of those presented in today literature. Some aspects are intentionally ignored since it rarely appears in control system engineering and a SISO process is considered here. The fuzzy inference system obtained is a table-based Sugeno-Takagi type. System’s desired performance is defined by a reference model and rules are extracted from recorded data, after the correct control actions are learned. The presented algorithm is tested in constructing the rule-base of a fuzzy controller for a DC drive application. System’s performances and method’s viability are analyzed.

  2. Fuzzy logic controller versus classical logic controller for residential hybrid solar-wind-storage energy system

    Energy Technology Data Exchange (ETDEWEB)

    Derrouazin, A., E-mail: derrsid@gmail.com [University Hassiba BenBouali of Chlef, LGEER,Chlef (Algeria); Université de Lorraine, LMOPS, EA 4423, 57070 Metz (France); CentraleSupélec, LMOPS, 57070 Metz (France); Aillerie, M., E-mail: aillerie@metz.supelec.fr; Charles, J. P. [Université de Lorraine, LMOPS, EA 4423, 57070 Metz (France); CentraleSupélec, LMOPS, 57070 Metz (France); Mekkakia-Maaza, N. [Université des sciences et de la Technologie d’Oran, Mohamed Boudiaf-USTO MB,LMSE, Oran Algérie (Algeria)

    2016-07-25

    Several researches for management of diverse hybrid energy systems and many techniques have been proposed for robustness, savings and environmental purpose. In this work we aim to make a comparative study between two supervision and control techniques: fuzzy and classic logics to manage the hybrid energy system applied for typical housing fed by solar and wind power, with rack of batteries for storage. The system is assisted by the electric grid during energy drop moments. A hydrogen production device is integrated into the system to retrieve surplus energy production from renewable sources for the household purposes, intending the maximum exploitation of these sources over years. The models have been achieved and generated signals for electronic switches command of proposed both techniques are presented and discussed in this paper.

  3. Fuzzy logic controller versus classical logic controller for residential hybrid solar-wind-storage energy system

    International Nuclear Information System (INIS)

    Derrouazin, A.; Aillerie, M.; Charles, J. P.; Mekkakia-Maaza, N.

    2016-01-01

    Several researches for management of diverse hybrid energy systems and many techniques have been proposed for robustness, savings and environmental purpose. In this work we aim to make a comparative study between two supervision and control techniques: fuzzy and classic logics to manage the hybrid energy system applied for typical housing fed by solar and wind power, with rack of batteries for storage. The system is assisted by the electric grid during energy drop moments. A hydrogen production device is integrated into the system to retrieve surplus energy production from renewable sources for the household purposes, intending the maximum exploitation of these sources over years. The models have been achieved and generated signals for electronic switches command of proposed both techniques are presented and discussed in this paper.

  4. Expert system for fault diagnosis in process control valves using fuzzy-logic

    Energy Technology Data Exchange (ETDEWEB)

    Carneiro, Alvaro L.G., E-mail: carneiro@ipen.br [Instituto de Pesquisas Energeticas e Nucleares (IPEN/CNEN-SP), Sao Paulo, SP (Brazil); Porto Junior, Almir C.S., E-mail: almir@ctmsp.mar.mil.br [Centro Tecnologico da Marinha em Sao Paulo (CIANA/CTMSP), Ipero, SP (Brazil). Centro de Instrucao e Adestramento Nuclear de ARAMAR

    2013-07-01

    The models of asset maintenance of a process plant basically are classified in corrective maintenance, preventive, predictive and proactive (online). The corrective maintenance is the elementary and most obvious way of the maintenance models. The preventive maintenance consists in a fault prevention work, based on statistical studies that can lead to low efficiency or even an unexpected shutdown of the plant. Predictive maintenance aims to prevent equipment or systems failures through monitoring and tracking of parameters, allowing continuous operation as long as possible. The proactive maintenance usually includes predictive maintenance, emphasizing the root cause analysis of the failure. The maintenance predictive/proactive planning frequently uses software that integrates data from different systems, which facilitates a quick and effective decision- making. In nuclear plants this model has an important role regarding the reliability of equipment and systems. The main focus of this work is to study the development of a model of non-intrusive monitoring and diagnosis applied to process control valves using artificial intelligence by fuzzy logic technique, contributing in the development of predictive methodologies identifying faults in incipient state. The control valve analyzed belongs to a steam plant which simulates the secondary circuit of a PWR nuclear reactor - Pressurized Water Reactor. This study makes use of MATLAB language through the fuzzy logic toolbox which uses the method of inference Mamdani, acting by fuzzy conjunction, through Triangular Norms (t-norm) and Triangular Conorms (t-conorm). As input variables are used air pressure and displacement of the valve stem. Input data coming into the fuzzy system by graph of the automation system Delta V ® available in the plant, which receives a signal of electric current from an 'intelligent' positioned installed on the valve. The output variable is the 'status' of the valve. Through a

  5. Expert system for fault diagnosis in process control valves using fuzzy-logic

    International Nuclear Information System (INIS)

    Carneiro, Alvaro L.G.; Porto Junior, Almir C.S.

    2013-01-01

    The models of asset maintenance of a process plant basically are classified in corrective maintenance, preventive, predictive and proactive (online). The corrective maintenance is the elementary and most obvious way of the maintenance models. The preventive maintenance consists in a fault prevention work, based on statistical studies that can lead to low efficiency or even an unexpected shutdown of the plant. Predictive maintenance aims to prevent equipment or systems failures through monitoring and tracking of parameters, allowing continuous operation as long as possible. The proactive maintenance usually includes predictive maintenance, emphasizing the root cause analysis of the failure. The maintenance predictive/proactive planning frequently uses software that integrates data from different systems, which facilitates a quick and effective decision- making. In nuclear plants this model has an important role regarding the reliability of equipment and systems. The main focus of this work is to study the development of a model of non-intrusive monitoring and diagnosis applied to process control valves using artificial intelligence by fuzzy logic technique, contributing in the development of predictive methodologies identifying faults in incipient state. The control valve analyzed belongs to a steam plant which simulates the secondary circuit of a PWR nuclear reactor - Pressurized Water Reactor. This study makes use of MATLAB language through the fuzzy logic toolbox which uses the method of inference Mamdani, acting by fuzzy conjunction, through Triangular Norms (t-norm) and Triangular Conorms (t-conorm). As input variables are used air pressure and displacement of the valve stem. Input data coming into the fuzzy system by graph of the automation system Delta V ® available in the plant, which receives a signal of electric current from an 'intelligent' positioned installed on the valve. The output variable is the 'status' of the valve. Through a rule base

  6. Implement Fuzzy Logic to Optimize Electronic Business Success

    OpenAIRE

    Fahim Akhter

    2016-01-01

    Customers are realizing the importance and benefits of shopping online such as convenience, comparison, product research, larger selection, and lower prices. The dynamic nature of e-commerce evokes online businesses to make alterations in their business processes and decisions making to satisfy customers’ needs. Online businesses are adopting Business Intelligence (BI) tools and systems with the collaboration of fuzzy logic system to forecast the future of the e-commerce. With the aid of BI, ...

  7. A Comparison of Fuzzy and Annotated Logic Programming

    Czech Academy of Sciences Publication Activity Database

    Krajči, S.; Lencses, R.; Vojtáš, Peter

    2004-01-01

    Roč. 144, - (2004), s. 173-192 ISSN 0165-0114 R&D Projects: GA ČR GA201/00/1489 Grant - others:VEGA(SK) 1/7557/20; VEGA(SK) 1/7555/20; VEGA(SK) 1/0385/03 Institutional research plan: CEZ:AV0Z1030915 Keywords : fuzzy logic programming * generalized annotated programs * declarative and procedural semantics * continuous semantics and computable fixpoint * soundness and completeness Subject RIV: BA - General Mathematics Impact factor: 0.734, year: 2004

  8. CAC Algorithm Based on Fuzzy Logic

    Directory of Open Access Journals (Sweden)

    Ľubomír DOBOŠ

    2009-05-01

    Full Text Available Quality of Service (QoS represent one ofmajor parameters that describe mobile wirelesscommunication systems. Thanks growing popularity ofmobile communication in last years, there is anincreasing expansion of connection admission controlschemes (CAC that plays important role in QoSdelivering in terms of connection blocking probability,connection dropping probability, data loss rate andsignal quality.With expansion of services provided by the mobilenetworks growing the requirements to QoS andtogether growing requirements to CAC schemes.Therefore, still more sophisticated CAC schemes arerequired to guarantee the QoS. This paper containsshort introduction into division of connectionadmission control schemes and presents thresholdoriented CAC scheme with fuzzy logic used foradaptation of the threshold value.

  9. Fuzzy Logic-Based Histogram Equalization for Image Contrast Enhancement

    Directory of Open Access Journals (Sweden)

    V. Magudeeswaran

    2013-01-01

    Full Text Available Fuzzy logic-based histogram equalization (FHE is proposed for image contrast enhancement. The FHE consists of two stages. First, fuzzy histogram is computed based on fuzzy set theory to handle the inexactness of gray level values in a better way compared to classical crisp histograms. In the second stage, the fuzzy histogram is divided into two subhistograms based on the median value of the original image and then equalizes them independently to preserve image brightness. The qualitative and quantitative analyses of proposed FHE algorithm are evaluated using two well-known parameters like average information contents (AIC and natural image quality evaluator (NIQE index for various images. From the qualitative and quantitative measures, it is interesting to see that this proposed method provides optimum results by giving better contrast enhancement and preserving the local information of the original image. Experimental result shows that the proposed method can effectively and significantly eliminate washed-out appearance and adverse artifacts induced by several existing methods. The proposed method has been tested using several images and gives better visual quality as compared to the conventional methods.

  10. Performance of Globally Linearized Controller and Two Region Fuzzy Logic Controller on a Nonlinear Process

    Directory of Open Access Journals (Sweden)

    N. Jaya

    2008-10-01

    Full Text Available In this work, a design and implementation of a Conventional PI controller, single region fuzzy logic controller, two region fuzzy logic controller and Globally Linearized Controller (GLC for a two capacity interacting nonlinear process is carried out. The performance of this process using single region FLC, two region FLC and GLC are compared with the performance of conventional PI controller about an operating point of 50 %. It has been observed that GLC and two region FLC provides better performance. Further, this procedure is also validated by real time experimentation using dSPACE.

  11. Navigasi Berbasis Behavior dan Fuzzy Logic pada Simulasi Robot Bergerak Otonom

    Directory of Open Access Journals (Sweden)

    Rendyansyah

    2016-03-01

    Full Text Available Mobile robot is the robotic mechanism that is able to moved automatically. The movement of the robot automatically require a navigation system. Navigation is a method for determining the robot motion. In this study, using a method developed robot navigation behavior with fuzzy logic. The behavior of the robot is divided into several modules, such as walking, avoid obstacles, to follow walls, corridors and conditions of u-shape. In this research designed mobile robot simulation in a visual programming. Robot is equipped with seven distance sensor and divided into several groups to test the behavior that is designed, so that the behavior of the robot generate speed and steering control. Based on experiments that have been conducted shows that mobile robot simulation can run smooth on many conditions. This proves that the implementation of the formation of behavior and fuzzy logic techniques on the robot working well

  12. Challenges And Results of the Applications of Fuzzy Logic in the Classification of Rich Galaxy Clusters

    Science.gov (United States)

    Girola Schneider, R.

    2017-07-01

    The fuzzy logic is a branch of the artificial intelligence founded on the concept that everything is a matter of degree. It intends to create mathematical approximations on the resolution of certain types of problems. In addition, it aims to produce exact results obtained from imprecise data, for which it is particularly useful for electronic and computer applications. This enables it to handle vague or unspecific information when certain parts of a system are unknown or ambiguous and, therefore, they cannot be measured in a reliable manner. Also, when the variation of a variable can produce an alteration on the others The main focus of this paper is to prove the importance of these techniques formulated from a theoretical analysis on its application on ambiguous situations in the field of the rich clusters of galaxies. The purpose is to show its applicability in the several classification systems proposed for the rich clusters, which are based on criteria such as the level of richness of the cluster, the distribution of the brightest galaxies, whether there are signs of type-cD galaxies or not or the existence of sub-clusters. Fuzzy logic enables the researcher to work with "imprecise" information implementing fuzzy sets and combining rules to define actions. The control systems based on fuzzy logic join input variables that are defined in terms of fuzzy sets through rule groups that produce one or several output values of the system under study. From this context, the application of the fuzzy logic's techniques approximates the solution of the mathematical models in abstractions about the rich galaxy cluster classification of physical properties in order to solve the obscurities that must be confronted by an investigation group in order to make a decision.

  13. Hybrid Multi-objective Forecasting of Solar Photovoltaic Output Using Kalman Filter based Interval Type-2 Fuzzy Logic System

    DEFF Research Database (Denmark)

    Hassan, Saima; Ahmadieh Khanesar, Mojtaba; Hajizadeh, Amin

    2017-01-01

    Learning of fuzzy parameters for system modeling using evolutionary algorithms is an interesting topic. In this paper, two optimal design and tuning of Interval type-2 fuzzy logic system are proposed using hybrid learning algorithms. The consequent parameters of the interval type-2 fuzzy logic...... system in both the hybrid algorithms are tuned using Kalman filter. Whereas the antecedent parameters of the system in the first hybrid algorithm is optimized using the multi-objective particle swarm optimization (MOPSO) and using the multi-objective evolutionary algorithm Based on Decomposition (MOEA...

  14. ARBO-VLV: beoordeling met fuzzy logic van arbeidsomstandigheden in een vleesvarkensstal

    NARCIS (Netherlands)

    Drost, H.; Satter, I.H.G.

    2000-01-01

    Until now, assessment of working conditions occurs mainly in a qualitative way or quantitative but in different variables. Because of this, interpretation results of similar data differ between researchers. The aim of this study is to develop a fuzzy logic model for quantitative assessment of

  15. A fuzzy logic approach to control anaerobic digestion.

    Science.gov (United States)

    Domnanovich, A M; Strik, D P; Zani, L; Pfeiffer, B; Karlovits, M; Braun, R; Holubar, P

    2003-01-01

    One of the goals of the EU-Project AMONCO (Advanced Prediction, Monitoring and Controlling of Anaerobic Digestion Process Behaviour towards Biogas Usage in Fuel Cells) is to create a control tool for the anaerobic digestion process, which predicts the volumetric organic loading rate (Bv) for the next day, to obtain a high biogas quality and production. The biogas should contain a high methane concentration (over 50%) and a low concentration of components toxic for fuel cells, e.g. hydrogen sulphide, siloxanes, ammonia and mercaptanes. For producing data to test the control tool, four 20 l anaerobic Continuously Stirred Tank Reactors (CSTR) are operated. For controlling two systems were investigated: a pure fuzzy logic system and a hybrid-system which contains a fuzzy based reactor condition calculation and a hierachial neural net in a cascade of optimisation algorithms.

  16. A fuzzy logic based navigation for mobile robot

    International Nuclear Information System (INIS)

    Adel Ali S Al-Jumaily; Shamsudin M Amin; Mohamed Khalil

    1998-01-01

    The main issue of intelligent robot is how to reach its goal safely in real time when it moves in unknown environment. The navigational planning is becoming the central issue in development of real-time autonomous mobile robots. Behaviour based robots have been successful in reacting with dynamic environment but still there are some complexity and challenging problems. Fuzzy based behaviours present as powerful method to solve the real time reactive navigation problems in unknown environment. We shall classify the navigation generation methods, five some characteristics of these methods, explain why fuzzy logic is suitable for the navigation of mobile robot and automated guided vehicle, and describe a reactive navigation that is flexible to react through their behaviours to the change of the environment. Some simulation results will be presented to show the navigation of the robot. (Author)

  17. Switch Reluctance Motor Control Based on Fuzzy Logic System

    Directory of Open Access Journals (Sweden)

    S. V. Aleksandrovsky

    2012-01-01

    Full Text Available Due to its intrinsic simplicity and reliability, the switched reluctance motor (SRM has now become a promising candidate for variable-speed drive applications as an alternative induction motor in various industrial application. However, the SRM has the disadvantage of nonlinear characteristic and control. It is suggested to use controller based on fuzzy logic system. Design of FLS controller and simulation model presented.

  18. A fuzzy logic decision support system for assessing clinical nutritional risk

    Directory of Open Access Journals (Sweden)

    Ali Mohammad Hadianfard

    2015-04-01

    Full Text Available Introduction: Studies have indicated a global high prevalence of hospital malnutrition on admission and during hospitalization. Clinical Nutritional Risk Screen (CNRS is a way to identify malnutrition and manage nutritional interventions. Several traditional and non-computer based tools have been suggested for screening nutritional risk levels. The present study was an attempt to employ a computer based fuzzy model decision support system as a nutrition-screening tool for inpatients. Method: This is an applied modeling study. The system architecture was designed based on the fuzzy logic model including input data, inference engine, and output. A clinical nutritionist entered nineteen input variables using a windows-based graphical user interface. The inference engine was involved with knowledge obtained from literature and the construction of ‘IF-THEN’ rules. The output of the system was stratification of patients into four risk levels from ‘No’ to ‘High’ where a number was also allocated to them as a nutritional risk grade. All patients (121 people admitted during implementing the system participated in testing the model. The classification tests were used to measure the CNRS fuzzy model performance. IBM SPSS version 21 was utilized as a tool for data analysis with α = 0.05 as a significance level. Results: Results showed that sensitivity, specificity, accuracy, and precision of the fuzzy model performance were 91.67% (±4.92, 76% (±7.6, 88.43% (±5.7, and 93.62% (±4.32, respectively. Instant performance on admission and very low probability of mistake in predicting malnutrition risk level may justify using the model in hospitals. Conclusion: To conclude, the fuzzy model-screening tool is based on multiple nutritional risk factors, having the capability of classifying inpatients into several nutritional risk levels and identifying the level of required nutritional intervention.

  19. Using Fuzzy Logic to Increase the Accuracy of E-Commerce Risk Assessment Based on an Expert System

    Directory of Open Access Journals (Sweden)

    H. Beheshti

    2017-12-01

    Full Text Available Strong adaptive control can be exercised even without access to accurate data inputs. Such control is possible through fuzzy mathematics, which is a meta-collection of Boolean logic principles that imply relative accuracy. Fuzzy mathematics find applications in e-commerce, where different risk analysis methods are available for risk assessment and estimation. Such approaches can be quantitative or qualitative, depending on the type of examined data. Quantitative methods are grounded in statistics, whereas qualitative methods are based on expert judgments and fuzzy set theory. Given that qualitative methods are very subjective and deal with vague or inaccurate data, fuzzy logic can be used to extract useful information from data inaccuracies. In this study, a model based on the opinions of e-commerce security experts was designed and implemented by using fuzzy expert systems and MATLAB. A case study was conducted to validate the effectiveness of the Model.

  20. Simulation comparison of proportional integral derivative and fuzzy logic in controlling AC-DC buck boost converter

    Science.gov (United States)

    Faisal, A.; Hasan, S.; Suherman

    2018-03-01

    AC-DC converter is widely used in the commercial industry even for daily purposes. The AC-DC converter is used to convert AC voltage into DC. In order to obtain the desired output voltage, the converter usually has a controllable regulator. This paper discusses buck boost regulator with a power MOSFET as switching component which is adjusted based on the duty cycle of pulse width modulation (PWM). The main problems of the buck boost converter at start up are the high overshoot, the long peak time and rise time. This paper compares the effectiveness of two control techniques: proportional integral derivative (PID) and fuzzy logic control in controlling the buck boost converter through simulations. The results show that the PID is more sensitive to voltage change than fuzzy logic. However, PID generates higher overshoot, long peak time and rise time. On the other hand, fuzzy logic generates no overshoot and shorter rise time.

  1. Automatic generation control of TCPS based hydrothermal system under open market scenario: A fuzzy logic approach

    Energy Technology Data Exchange (ETDEWEB)

    Rao, C. Srinivasa [EEE Department, G. Pulla Reddy Engineering College, Kurnool, Andhra Pradesh (India); Nagaraju, S. Siva [EEE Department, J.N.T.U College of Engg., Kakinada, Andhra Pradesh (India); Raju, P. Sangameswara [EEE Department, S.V. University, Tirupati, Andhra Pradesh (India)

    2009-09-15

    This paper presents the analysis of automatic generation control of a two-area interconnected thyristor controlled phase shifter based hydrothermal system in the continuous mode using fuzzy logic controller under open market scenario. Open transmission access and the evolving of more socialized companies for generation, transmission and distribution affects the formulation of AGC problem. So the traditional AGC two-area system is modified to take into account the effect of bilateral contracts on the dynamics. It is possible to stabilize the system frequency and tie-power oscillations by controlling the phase angle of TCPS which is expected to provide a new ancillary service for the future power systems. A control strategy using TCPS is proposed to provide active control of system frequency. Further dynamic responses for small perturbation considering fuzzy logic controller and PI controller (dual mode controller) have been observed and the superior performance of fuzzy logic controller has been reported analytically and also through simulation. (author)

  2. Fuzzy logic modeling of EIS measurements on lithium-ion batteries

    International Nuclear Information System (INIS)

    Singh, Pritpal; Vinjamuri, Ramana; Wang, Xiquan; Reisner, David

    2006-01-01

    A fuzzy logic-based state of health (SOH) meter is being developed for lithium-ion (Li-ion) batteries for potential use in portable defibrillators. Electrochemical impedance spectroscopy (EIS) measurements have been made from which input parameters for a fuzzy logic model to estimate the state of charge (SOC) and SOH are derived. The batteries are discharged continuously at a 1.4 A load current to simulate the constant current draw during the monitoring and recording of a patient's EKG, and periodically interrupted by 10 A pulses to simulate the battery discharge to charge up the capacitor that is in turn discharged to supply high voltage to the electrodes for the defibrillation of the patient. The test procedures included both voltage recovery and EIS measurements, and were made as the batteries were being discharged and over 30 charge/discharge cycles. Accurate models have been developed to estimate the number of pulses that the battery pack can deliver at various stages of its cycle life (SOC measure) and the number of charge/discharge cycles (SOH measure) that it had undergone

  3. Fuzzy logic estimator of rotor time constant in induction motors

    Energy Technology Data Exchange (ETDEWEB)

    Alminoja, J. [Tampere University of Technology (Finland). Control Engineering Laboratory; Koivo, H. [Helsinki University of Technology, Otaniemi (Finland). Control Engineering Laboratory

    1997-12-31

    Vector control of AC machines is a well-known and widely used technique in induction machine control. It offers an exact method for speed control of induction motors, but it is also sensitive to the changes in machine parameters. E.g. rotor time constant has a strong dependence on temperature. In this paper a fuzzy logic estimator is developed, with which the rotor time constant can be estimated when the machine has a load. It is more simple than the estimators proposed in the literature. The fuzzy estimator is tested by simulation when step-wise abrupt changes and slow drifting occurs. (orig.) 7 refs.

  4. Extraction of Fuzzy Logic Rules from Data by Means of Artificial Neural Networks

    Czech Academy of Sciences Publication Activity Database

    Holeňa, Martin

    2005-01-01

    Roč. 41, č. 3 (2005), s. 297-314 ISSN 0023-5954 R&D Projects: GA AV ČR IAA1030004 Institutional research plan: CEZ:AV0Z10300504 Keywords : knowledge extraction from data * artificial neural networks * fuzzy logic * Lukasiewicz logic * disjunctive normal form Subject RIV: BA - General Mathematics Impact factor: 0.343, year: 2005 http://dml.cz/handle/10338.dmlcz/135657

  5. Implementasi Fuzzy Logic Controller untuk Mengatur Ph Nutrisi pada Sistem Hidroponik Nutrient Film Technique (NFT

    Directory of Open Access Journals (Sweden)

    Dian Pancawati

    2016-07-01

    Full Text Available One solution to solve limited agricultural land is applying hydroponics Nutrient Film Technique (NFT. The advantage of NFT is using water circulated as a growing medium in order to obtain water, nutrients and oxygen to accelerate the growth of plants with good results. The most important parameter is the pH of nutrients. This article discusses how to design an automatic nutritional pH control system by implementing the method of Fuzzy Logic Controller. The control system use Arduino Mega2560, Analog pH Meter Kit as input, and the solenoid valve as actuators. The best response of the implementation of Fuzzy Logic Controller with the system which has 25 rules. The response shows that the system has in 1200 millisecond rise time and the steady state in 5530 milliseconds to increase the pH. While to decrease the pH system has response of rise time at 2000 milliseconds and steady state at the time of 3000 milliseconds. The system is able to maintain the pH at 5.5, with the result of the growth of lettuce as high as 20 cm and seven leaves for 54 days.

  6. Fuzzy logic for structural system control

    Directory of Open Access Journals (Sweden)

    Herbert Martins Gomes

    Full Text Available This paper provides some information and numerical tests that aims to investigate the use of a Fuzzy Controller applied to control systems. Some advantages are reported regarding the use of this controller, such as the characteristic ease of implementation due to its semantic feature in the statement of the control rules. On the other hand, it is also hypothesized that these systems have a lower performance loss when the system to be controlled is nonlinear or has time varying parameters. Numerical tests are performed using modal LQR optimal control and Fuzzy control of non-collocated systems with full state feedback in a two-dimensional structure. The paper proposes a way of designing a controller that may be a supervisory Fuzzy controller for a traditional controller or even a fuzzy controller independent from the traditional control, consisting on individual mode controllers. Some comments are drawn regarding the performance of these proposals in a number of arrangements.

  7. Technical application of Fuzzy logic in the construction of an energy sustainability index; Aplicacao das tecnicas de logica fuzzi na construcao de um indice de sustentabilidade energetica

    Energy Technology Data Exchange (ETDEWEB)

    Santos, Francisco Carlos B. dos; Carneiro, Alvaro Luiz Guimaraes [Instituto de Pesquisas Energeticas e Nucleares (IPEN-CNEN/SP), Sao Paulo - SP (Brazil)], E-mails: fcarlos@usp.br, carneiro@ipen.br

    2010-11-15

    Aggregation tools database and subsequent interpretation are the most challenge in the area of sustainability This task becomes very complex due to correlation of topics that comprise the dimensions that form the basis of the concept of sustainable development. The technique known as Fuzzy Logic or Fuzzy Logic is a powerful tool to capture information on vacancies, which is often the only information available in the area of sustainability. (author)

  8. Expert System for Competences Evaluation 360° Feedback Using Fuzzy Logic

    Directory of Open Access Journals (Sweden)

    Alberto Alfonso Aguilar Lasserre

    2014-01-01

    Full Text Available Performance evaluation (PE is a process that estimates the employee overall performance during a given period, and it is a common function carried out inside modern companies. PE is important because it is an instrument that encourages employees, organizational areas, and the whole company to have an appropriate behavior and continuous improvement. In addition, PE is useful in decision making about personnel allocation, productivity bonuses, incentives, promotions, disciplinary measures, and dismissals. There are many performance evaluation methods; however, none is universal and common to all companies. This paper proposes an expert performance evaluation system based on a fuzzy logic model, with competences 360° feedback oriented to human behavior. This model uses linguistic labels and adjustable numerical values to represent ambiguous concepts, such as imprecision and subjectivity. The model was validated in the administrative department of a real Mexican manufacturing company, where final results and conclusions show the fuzzy logic method advantages in comparison with traditional 360° performance evaluation methodologies.

  9. Design and FPGA-implementation of an improved adaptive fuzzy logic controller for DC motor speed control

    Directory of Open Access Journals (Sweden)

    E.A. Ramadan

    2014-09-01

    Full Text Available This paper presents an improved adaptive fuzzy logic speed controller for a DC motor, based on field programmable gate array (FPGA hardware implementation. The developed controller includes an adaptive fuzzy logic control (AFLC algorithm, which is designed and verified with a nonlinear model of DC motor. Then, it has been synthesised, functionally verified and implemented using Xilinx Integrated Software Environment (ISE and Spartan-3E FPGA. The performance of this controller has been successfully validated with good tracking results under different operating conditions.

  10. Fuzzy Logic Control of Adaptive ARQ for Video Distribution over a Bluetooth Wireless Link

    Directory of Open Access Journals (Sweden)

    R. Razavi

    2007-01-01

    Full Text Available Bluetooth's default automatic repeat request (ARQ scheme is not suited to video distribution resulting in missed display and decoded deadlines. Adaptive ARQ with active discard of expired packets from the send buffer is an alternative approach. However, even with the addition of cross-layer adaptation to picture-type packet importance, ARQ is not ideal in conditions of a deteriorating RF channel. The paper presents fuzzy logic control of ARQ, based on send buffer fullness and the head-of-line packet's deadline. The advantage of the fuzzy logic approach, which also scales its output according to picture type importance, is that the impact of delay can be directly introduced to the model, causing retransmissions to be reduced compared to all other schemes. The scheme considers both the delay constraints of the video stream and at the same time avoids send buffer overflow. Tests explore a variety of Bluetooth send buffer sizes and channel conditions. For adverse channel conditions and buffer size, the tests show an improvement of at least 4 dB in video quality compared to nonfuzzy schemes. The scheme can be applied to any codec with I-, P-, and (possibly B-slices by inspection of packet headers without the need for encoder intervention.

  11. Design of stability-guaranteed fuzzy logic controller for nuclear steam generators

    International Nuclear Information System (INIS)

    Cho, Byung Hak

    1996-02-01

    A fuzzy logic controller(FLC) and a fuzzy logic filter(FLF), which have a special type of fuzzifier, inference engine, and defuzzifier, are applied to the water level control of a nuclear steam generator (S/G). It is shown that arbitrary two-input, single-output linear state feedback controllers can be adequately expressed by this FLC. A procedure to construct stability-guaranteed FLC rules is proposed. It contains the following steps: (1) The stable sector of linear feedback gains is obtained from the suboptimal concept based on LQR theory and the Lyapunov's stability criteria: (2) The stable sector of linear gains is mapped into two linear rule tables that are used as limits for the FLC rules: (3) The construction of an FLC rule table is done by choosing certain rules that lie between these limits. This type of FLC guarantees asymptotic stability of the control system. The FLF generates a feedforward signal of S/G feedwater from the steam flow measurement using a fuzzy concept. Through computer simulation, it is found that the FLC with the FLF works better than well-tuned PID controller with variable gains to reduce swell/shrink phenomena especially for the water level deviation and abrupt steam flow disturbances that are typical in the existing power plants. A neurofuzzy logic controller (NFLC), that is implemented by using multi-layered neural network to have the same function as the FLC discussed above, is designed. The automatic generation of NFLC rule table is accomplished by using back-error-propagation (BEP) algorithm. There are two separated paths at the error back-propagation in the S/G. One is to consider the level dynamics depending on the tank capacity, and the other is to take into account the reverse dynamics of S/G. The amounts of error back-propagated through these paths show opposite effects to the BEP algorithm each other at the swell/shrink phenomena. Through the computer simulation, it is found that the BEP algorithm adequately generates NFLC

  12. Controlling the power output of a nuclear reactor with fuzzy logic

    NARCIS (Netherlands)

    Ruan, D.; Wal, A.J. van der

    1998-01-01

    The application of fuzzy logic control (FLC) in the domain of nuclear industry presents a tremendous challenge. The main reason for this is the public awareness of the risks of nuclear reactors and the very strict safety regulations in force for nuclear power plants. The very same regulations

  13. Controlling the Power Output of a Nuclear Reactor with Fuzzy Logic

    NARCIS (Netherlands)

    Ruan, D.; Wal, A.J. van der

    1997-01-01

    The application of fuzzy logic control (FLC) in the domain of nuclear industry presents a tremendous challenge. The main reason for this is the public awareness of the risks of nuclear reactors and the very strict safety regulations in force for nuclear power plants. The very same regulations

  14. Fuzzy associative memories for instrument fault detection

    International Nuclear Information System (INIS)

    Heger, A.S.

    1996-01-01

    A fuzzy logic instrument fault detection scheme is developed for systems having two or three redundant sensors. In the fuzzy logic approach the deviation between each signal pairing is computed and classified into three fuzzy sets. A rule base is created allowing the human perception of the situation to be represented mathematically. Fuzzy associative memories are then applied. Finally, a defuzzification scheme is used to find the centroid location, and hence the signal status. Real-time analyses are carried out to evaluate the instantaneous signal status as well as the long-term results for the sensor set. Instantaneous signal validation results are used to compute a best estimate for the measured state variable. The long-term sensor validation method uses a frequency fuzzy variable to determine the signal condition over a specific period. To corroborate the methodology synthetic data representing various anomalies are analyzed with both the fuzzy logic technique and the parity space approach. (Author)

  15. Fuzzy logic algorithm for quantitative tissue characterization of diffuse liver diseases from ultrasound images.

    Science.gov (United States)

    Badawi, A M; Derbala, A S; Youssef, A M

    1999-08-01

    Computerized ultrasound tissue characterization has become an objective means for diagnosis of liver diseases. It is difficult to differentiate diffuse liver diseases, namely cirrhotic and fatty liver by visual inspection from the ultrasound images. The visual criteria for differentiating diffused diseases are rather confusing and highly dependent upon the sonographer's experience. This often causes a bias effects in the diagnostic procedure and limits its objectivity and reproducibility. Computerized tissue characterization to assist quantitatively the sonographer for the accurate differentiation and to minimize the degree of risk is thus justified. Fuzzy logic has emerged as one of the most active area in classification. In this paper, we present an approach that employs Fuzzy reasoning techniques to automatically differentiate diffuse liver diseases using numerical quantitative features measured from the ultrasound images. Fuzzy rules were generated from over 140 cases consisting of normal, fatty, and cirrhotic livers. The input to the fuzzy system is an eight dimensional vector of feature values: the mean gray level (MGL), the percentile 10%, the contrast (CON), the angular second moment (ASM), the entropy (ENT), the correlation (COR), the attenuation (ATTEN) and the speckle separation. The output of the fuzzy system is one of the three categories: cirrhosis, fatty or normal. The steps done for differentiating the pathologies are data acquisition and feature extraction, dividing the input spaces of the measured quantitative data into fuzzy sets. Based on the expert knowledge, the fuzzy rules are generated and applied using the fuzzy inference procedures to determine the pathology. Different membership functions are developed for the input spaces. This approach has resulted in very good sensitivities and specificity for classifying diffused liver pathologies. This classification technique can be used in the diagnostic process, together with the history

  16. Dynamic Fuzzy Logic Parameter Tuning for ACO and Its Application in the Fuzzy Logic Control of an Autonomous Mobile Robot

    Directory of Open Access Journals (Sweden)

    Oscar Castillo

    2013-01-01

    Full Text Available Ant Colony Optimization (ACO is a population-based constructive meta-heuristic that exploits a form of past performance memory inspired by the foraging behaviour of real ants. The behaviour of the ACO algorithm is highly dependent on the values defined for its parameters. Adaptation and parameter control are recurring themes in the field of bio-inspired algorithms. The present paper explores a new approach to diversity control in ACO. The central idea is to avoid or slow down full convergence through the dynamic variation of certain parameters. The performance of different variants of the ACO algorithm was observed to choose one as the basis for the proposed approach. A convergence fuzzy logic controller with the objective of maintaining diversity at some level to avoid premature convergence was created. Encouraging results have been obtained on its application to the design of fuzzy controllers. In particular, the optimization of membership functions for a unicycle mobile robot trajectory control is presented with the proposed method.

  17. Use of an Electronic Tongue System and Fuzzy Logic to Analyze Water Samples

    Science.gov (United States)

    Braga, Guilherme S.; Paterno, Leonardo G.; Fonseca, Fernando J.

    2009-05-01

    An electronic tongue (ET) system incorporating 8 chemical sensors was used in combination with two pattern recognition tools, namely principal component analysis (PCA) and Fuzzy logic for discriminating/classification of water samples from different sources (tap, distilled and three brands of mineral water). The Fuzzy program exhibited a higher accuracy than the PCA and allowed the ET to classify correctly 4 in 5 types of water. Exception was made for one brand of mineral water which was sometimes misclassified as tap water. On the other hand, the PCA grouped water samples in three clusters, one with the distilled water; a second with tap water and one brand of mineral water, and the third with the other two other brands of mineral water. Samples in the second and third clusters could not be distinguished. Nevertheless, close grouping between repeated tests indicated that the ET system response is reproducible. The potential use of the Fuzzy logic as the data processing tool in combination with an electronic tongue system is discussed.

  18. Adaptive Fuzzy Logic based MPPT Control for PV System Under Partial Shading Condition

    OpenAIRE

    Choudhury, Subhashree; Rout, Pravat Kumar

    2016-01-01

    Partial shading causes power loss, hotspots and threatens the reliability of the Photovoltaic generation system. Moreover characteristic curves exhibit multiple peaks. Conventional MPPT techniques under this condition often fail to give optimum MPP. Focusing on the afore mentioned problem an attempt has been made to design an Adaptive Takagi-Sugeno Fuzzy Inference System based Fuzzy Logic Control MPPT.The mathematical model of PV array is simulated using in MATLAB/Simulink environment.Various...

  19. Intelligent tuning of vibration mitigation process for single link manipulator using fuzzy logic

    Directory of Open Access Journals (Sweden)

    Ahmed A. Ali

    2017-08-01

    Full Text Available In this work, active vibration mitigation for smart single link manipulator is presented. Two piezoelectric transducers were utilized to act as actuator and sensor respectively. Classical Proportional (P controller was tested numerically and experimentally. The comparison between measured results showed good agreement. The proposed work includes the introducing of fuzzy logic for tuning controller's gain within finite element method. Classical Proportional-Integral (PI, Fuzzy-P and Fuzzy-PI controllers were totally integrated as a series of [IF-Then] states and solved numerically by using Finite Element (FE solver (ANSYS. Proposed method will pave the way on solving the tuning process totally within single FE solver with high efficiency. Proposed method satisfied mitigation in the overall free response with about 52% and 74% of the manipulator settling time when Fuzzy-P and Fuzzy-PI controllers were activated respectively. This contribution can be utilized for many other applications related to fuzzy topics.

  20. A Fuzzy Logic-Based Approach for Estimation of Dwelling Times of Panama Metro Stations

    Directory of Open Access Journals (Sweden)

    Aranzazu Berbey Alvarez

    2015-04-01

    Full Text Available Passenger flow modeling and station dwelling time estimation are significant elements for railway mass transit planning, but system operators usually have limited information to model the passenger flow. In this paper, an artificial-intelligence technique known as fuzzy logic is applied for the estimation of the elements of the origin-destination matrix and the dwelling time of stations in a railway transport system. The fuzzy inference engine used in the algorithm is based in the principle of maximum entropy. The approach considers passengers’ preferences to assign a level of congestion in each car of the train in function of the properties of the station platforms. This approach is implemented to estimate the passenger flow and dwelling times of the recently opened Line 1 of the Panama Metro. The dwelling times obtained from the simulation are compared to real measurements to validate the approach.

  1. Fuzzy Logic-based expert system for evaluating cake quality of freeze-dried formulations.

    Science.gov (United States)

    Trnka, Hjalte; Wu, Jian X; Van De Weert, Marco; Grohganz, Holger; Rantanen, Jukka

    2013-12-01

    Freeze-drying of peptide and protein-based pharmaceuticals is an increasingly important field of research. The diverse nature of these compounds, limited understanding of excipient functionality, and difficult-to-analyze quality attributes together with the increasing importance of the biosimilarity concept complicate the development phase of safe and cost-effective drug products. To streamline the development phase and to make high-throughput formulation screening possible, efficient solutions for analyzing critical quality attributes such as cake quality with minimal material consumption are needed. The aim of this study was to develop a fuzzy logic system based on image analysis (IA) for analyzing cake quality. Freeze-dried samples with different visual quality attributes were prepared in well plates. Imaging solutions together with image analytical routines were developed for extracting critical visual features such as the degree of cake collapse, glassiness, and color uniformity. On the basis of the IA outputs, a fuzzy logic system for analysis of these freeze-dried cakes was constructed. After this development phase, the system was tested with a new screening well plate. The developed fuzzy logic-based system was found to give comparable quality scores with visual evaluation, making high-throughput classification of cake quality possible. © 2013 Wiley Periodicals, Inc. and the American Pharmacists Association.

  2. An Integrated Risk Index Model Based on Hierarchical Fuzzy Logic for Underground Risk Assessment

    Directory of Open Access Journals (Sweden)

    Muhammad Fayaz

    2017-10-01

    Full Text Available Available space in congested cities is getting scarce due to growing urbanization in the recent past. The utilization of underground space is considered as a solution to the limited space in smart cities. The numbers of underground facilities are growing day by day in the developing world. Typical underground facilities include the transit subway, parking lots, electric lines, water supply and sewer lines. The likelihood of the occurrence of accidents due to underground facilities is a random phenomenon. To avoid any accidental loss, a risk assessment method is required to conduct the continuous risk assessment and report any abnormality before it happens. In this paper, we have proposed a hierarchical fuzzy inference based model for under-ground risk assessment. The proposed hierarchical fuzzy inference architecture reduces the total number of rules from the rule base. Rule reduction is important because the curse of dimensionality damages the transparency and interpretation as it is very tough to understand and justify hundreds or thousands of fuzzy rules. The computation time also increases as rules increase. The proposed model takes 175 rules having eight input parameters to compute the risk index, and the conventional fuzzy logic requires 390,625 rules, having the same number of input parameters to compute risk index. Hence, the proposed model significantly reduces the curse of dimensionality. Rule design for fuzzy logic is also a tedious task. In this paper, we have also introduced new rule schemes, namely maximum rule-based and average rule-based; both schemes can be used interchangeably according to the logic needed for rule design. The experimental results show that the proposed method is a virtuous choice for risk index calculation where the numbers of variables are greater.

  3. A Fuzzy Logic System to Analyze a Student's Lifestyle

    OpenAIRE

    Ghosh, Sourish; Boob, Aaditya Sanjay; Nikhil, Nishant; Vysyaraju, Nayan Raju; Kumar, Ankit

    2016-01-01

    A college student's life can be primarily categorized into domains such as education, health, social and other activities which may include daily chores and travelling time. Time management is crucial for every student. A self realisation of one's daily time expenditure in various domains is therefore essential to maximize one's effective output. This paper presents how a mobile application using Fuzzy Logic and Global Positioning System (GPS) analyzes a student's lifestyle and provides recom...

  4. Interdisciplinarity, logic of uncertainty and fuzzy logic in primary school

    Directory of Open Access Journals (Sweden)

    Luciana Delli Rocili

    2015-12-01

    Full Text Available On the occasion of the 120th anniversary of Mathesis, this work wants to be a memory, a tribute to two great presidents of Mathesis: Bruno de Finetti and Angelo Fadini. Both have pursued the idea of interdisciplinary teaching and research. Bruno de Finetti, with his books on The invention of truth, (1934, and on Logic and Intuitive Mathematics, (1959, and his very famous "Theory of probability", (1970, shows a rejection of formal education, comfortable, monodisciplinary, made of certainties, and chooses the impervious way of addressing the problems that are to the base of science. Angelo Fadini, with his papers and books on Theory of Fuzzy Sets, shows first in Italy several logical questions which puts as the basis for practical applications in Architecture. This paper is an attempt to experiment, in an interdisciplinary framework, the basic ideas of Bruno de Finetti and Angelo Fadini in primary school, in the belief that in the Primary School are formed ideas and intuitions, while in the secondary school the attention is focused mainly on specific issues of Mathematics. We shows some results of a still ongoing experimentation.   Interdisciplinarietà, logica dell'incerto e logica sfumata nella scuola primaria In occasione dei 120 anni della Mathesis, questo lavoro vuole essere un ricordo, un omaggio a due grandi Presidenti della Mathesis: Bruno de Finetti e Angelo Fadini. Entrambi hanno portato avanti l’idea della interdisciplinarietà nell’insegnamento e nella ricerca. Bruno de Finetti, con la sua “Matematica Logico Intuitiva” del 1959, e la sua “Teoria delle probabilità”, del 1970, e ancora prima, con “L’invenzione della verità”, del 1934, mostra un rifiuto dell’insegnamento formale, comodo, monodisciplinare, fatto di certezze, e sceglie la strada impervia dell’affrontare i problemi che sono alla base della scienza. Angelo Fadini, con la sua Teoria degli Insiemi Sfocati, mostra per primo in Italia varie questioni

  5. Robust nonlinear PID-like fuzzy logic control of a planar parallel (2PRP-PPR) manipulator.

    Science.gov (United States)

    Londhe, P S; Singh, Yogesh; Santhakumar, M; Patre, B M; Waghmare, L M

    2016-07-01

    In this paper, a robust nonlinear proportional-integral-derivative (PID)-like fuzzy control scheme is presented and applied to complex trajectory tracking control of a 2PRP-PPR (P-prismatic, R-revolute) planar parallel manipulator (motion platform) with three degrees-of-freedom (DOF) in the presence of parameter uncertainties and external disturbances. The proposed control law consists of mainly two parts: first part uses a feed forward term to enhance the control activity and estimated perturbed term to compensate for the unknown effects namely external disturbances and unmodeled dynamics, and the second part uses a PID-like fuzzy logic control as a feedback portion to enhance the overall closed-loop stability of the system. Experimental results are presented to show the effectiveness of the proposed control scheme. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

  6. Genetic algorithms optimized fuzzy logic control for the maximum power point tracking in photovoltaic system

    Energy Technology Data Exchange (ETDEWEB)

    Larbes, C.; Ait Cheikh, S.M.; Obeidi, T.; Zerguerras, A. [Laboratoire des Dispositifs de Communication et de Conversion Photovoltaique, Departement d' Electronique, Ecole Nationale Polytechnique, 10, Avenue Hassen Badi, El Harrach, Alger 16200 (Algeria)

    2009-10-15

    This paper presents an intelligent control method for the maximum power point tracking (MPPT) of a photovoltaic system under variable temperature and irradiance conditions. First, for the purpose of comparison and because of its proven and good performances, the perturbation and observation (P and O) technique is briefly introduced. A fuzzy logic controller based MPPT (FLC) is then proposed which has shown better performances compared to the P and O MPPT based approach. The proposed FLC has been also improved using genetic algorithms (GA) for optimisation. Different development stages are presented and the optimized fuzzy logic MPPT controller (OFLC) is then simulated and evaluated, which has shown better performances. (author)

  7. Using LDR as Sensing Element for an External Fuzzy Controller Applied in Photovoltaic Pumping Systems with Variable-Speed Drives.

    Science.gov (United States)

    Maranhão, Geraldo Neves De A; Brito, Alaan Ubaiara; Leal, Anderson Marques; Fonseca, Jéssica Kelly Silva; Macêdo, Wilson Negrão

    2015-09-22

    In the present paper, a fuzzy controller applied to a Variable-Speed Drive (VSD) for use in Photovoltaic Pumping Systems (PVPS) is proposed. The fuzzy logic system (FLS) used is embedded in a microcontroller and corresponds to a proportional-derivative controller. A Light-Dependent Resistor (LDR) is used to measure, approximately, the irradiance incident on the PV array. Experimental tests are executed using an Arduino board. The experimental results show that the fuzzy controller is capable of operating the system continuously throughout the day and controlling the direct current (DC) voltage level in the VSD with a good performance.

  8. Using LDR as Sensing Element for an External Fuzzy Controller Applied in Photovoltaic Pumping Systems with Variable-Speed Drives

    Directory of Open Access Journals (Sweden)

    Geraldo Neves De A. Maranhão

    2015-09-01

    Full Text Available In the present paper, a fuzzy controller applied to a Variable-Speed Drive (VSD for use in Photovoltaic Pumping Systems (PVPS is proposed. The fuzzy logic system (FLS used is embedded in a microcontroller and corresponds to a proportional-derivative controller. A Light-Dependent Resistor (LDR is used to measure, approximately, the irradiance incident on the PV array. Experimental tests are executed using an Arduino board. The experimental results show that the fuzzy controller is capable of operating the system continuously throughout the day and controlling the direct current (DC voltage level in the VSD with a good performance.

  9. Structural modeling and fuzzy-logic based diagnosis of a ship propulsion benchmark

    DEFF Research Database (Denmark)

    Izadi-Zamanabadi, Roozbeh; Blanke, M.; Katebi, S.D.

    2000-01-01

    An analysis of structural model of a ship propulsion benchmark leads to identifying the subsystems with inherent redundant information. For a nonlinear part of the system, a Fuzzy logic based FD algorithm with adaptive threshold is employed. The results illustrate the applicability of structural...

  10. A Fuzzy Logic Model to Classify Design Efficiency of Nursing Unit Floors

    Directory of Open Access Journals (Sweden)

    Tuğçe KAZANASMAZ

    2010-01-01

    Full Text Available This study was conducted to determine classifications for the planimetric design efficiency of certain public hospitals by developing a fuzzy logic algorithm. Utilizing primary areas and circulation areas from nursing unit floor plans, the study employed triangular membership functions for the fuzzy subsets. The input variables of primary areas per bed and circulation areas per bed were fuzzified in this model. The relationship between input variables and output variable of design efficiency were displayed as a result of fuzzy rules. To test existing nursing unit floors, efficiency output values were obtained and efficiency classes were constructed by this model in accordance with general norms, guidelines and previous studies. The classification of efficiency resulted from the comparison of hospitals.

  11. Analysis of selected structures for model-based measuring methods using fuzzy logic

    Energy Technology Data Exchange (ETDEWEB)

    Hampel, R.; Kaestner, W.; Fenske, A.; Vandreier, B.; Schefter, S. [Hochschule fuer Technik, Wirtschaft und Sozialwesen Zittau/Goerlitz (FH), Zittau (DE). Inst. fuer Prozesstechnik, Prozessautomatisierung und Messtechnik e.V. (IPM)

    2000-07-01

    Monitoring and diagnosis of safety-related technical processes in nuclear enginering can be improved with the help of intelligent methods of signal processing such as analytical redundancies. This chapter gives an overview about combined methods in form of hybrid models using model based measuring methods (observer) and knowledge-based methods (fuzzy logic). Three variants of hybrid observers (fuzzy-supported observer, hybrid observer with variable gain and hybrid non-linear operating point observer) are explained. As a result of the combination of analytical and fuzzy-based algorithms a new quality of monitoring and diagnosis is achieved. The results will be demonstrated in summary for the example water level estimation within pressure vessels (pressurizer, steam generator, and Boiling Water Reactor) with water-steam mixture during the accidental depressurization. (orig.)

  12. Analysis of selected structures for model-based measuring methods using fuzzy logic

    International Nuclear Information System (INIS)

    Hampel, R.; Kaestner, W.; Fenske, A.; Vandreier, B.; Schefter, S.

    2000-01-01

    Monitoring and diagnosis of safety-related technical processes in nuclear engineering can be improved with the help of intelligent methods of signal processing such as analytical redundancies. This chapter gives an overview about combined methods in form of hybrid models using model based measuring methods (observer) and knowledge-based methods (fuzzy logic). Three variants of hybrid observers (fuzzy-supported observer, hybrid observer with variable gain and hybrid non-linear operating point observer) are explained. As a result of the combination of analytical and fuzzy-based algorithms a new quality of monitoring and diagnosis is achieved. The results will be demonstrated in summary for the example water level estimation within pressure vessels (pressurizer, steam generator, and Boiling Water Reactor) with water-steam mixture during the accidental depressurization. (orig.)

  13. SPEED CONTROL OF DC MOTOR ON LOAD USING FUZZY LOGIC ...

    African Journals Online (AJOL)

    This paper presents the development of a fuzzy logic controller for the driver DC motor in the lube oil system of the H25 Hitachi gas turbine generator. The turbine generator is required to run at an operating pressure of 1.5bar with the low and the high pressure trip points being 0.78 bar and 1.9 bar respectively. However, the ...

  14. FUZZY LOGIC CONTROLLER IMPLEMENTATION FOR PHOTOVOLTAIC STATION

    Directory of Open Access Journals (Sweden)

    Imad Zein

    2014-01-01

    Full Text Available Solar panels have a nonlinear voltage-current characteristic, with a distinct maximum power point (MPP, which depends on the environmental factors, such as temperature and irradiation. In order to continuously harvest maximum power from the solar panels, they have to operate at their MPP despite the inevitable changes in the environment. This is why the controllers of all solar power electronic converters employ some method for maximum power point tracking (MPPT . Over the past years many MPPT techniques have been published and based on that the main paper’s objective is to analyze one of the most promising MPPT control algorithms: fuzzy logic controller. 

  15. Optimum selection of an energy resource using fuzzy logic

    International Nuclear Information System (INIS)

    Abouelnaga, Ayah E.; Metwally, Abdelmohsen; Nagy, Mohammad E.; Agamy, Saeed

    2009-01-01

    Optimum selection of an energy resource is a vital issue in developed countries. Considering energy resources as alternatives (nuclear, hydroelectric, gas/oil, and solar) and factors upon which the proper decision will be taken as attributes (economics, availability, environmental impact, and proliferation), one can use the multi-attribute utility theory (MAUT) to optimize the selection process. Recently, fuzzy logic is extensively applied to the MAUT as it expresses the linguistic appraisal for all attributes in wide and reliable manners. The rise in oil prices and the increased concern about environmental protection from CO 2 emissions have promoted the attention to the use of nuclear power as a viable energy source for power generation. For Egypt, as a case study, the nuclear option is found to be an appropriate choice. Following the introduction of innovative designs of nuclear power plants, improvements in the proliferation resistance, environmental impacts, and economics will enhance the selection of the nuclear option.

  16. The use of fuzzy logic for data analysis and modelling of European ...

    African Journals Online (AJOL)

    The use of fuzzy logic for data analysis and modelling of European harmful algal blooms: results of the HABES project. ... African Journal of Marine Science ... Alexandrium minutum, Karenia mikimotoi and Phaeocystis globosa at various European sites as part of the Harmful Algal Blooms Expert System (HABES) project.

  17. Recent Advances in Interval Type-2 Fuzzy Systems

    CERN Document Server

    Castillo, Oscar

    2012-01-01

    This book reviews current state of the art methods for building intelligent systems using type-2 fuzzy logic and bio-inspired optimization techniques. Combining type-2 fuzzy logic with optimization algorithms, powerful hy-brid intelligent systems have been built using the advantages that each technique offers. This book is intended to be a reference for scientists and engineers interested in applying type-2 fuzzy logic for solving problems in pattern recognition, intelligent control, intelligent manufacturing, robotics and automation. This book can also be used as a reference for graduate courses like the following: soft computing, intelligent pattern recognition, computer vision, applied artificial intelligence, and similar ones. We con-sider that this book can also be used to get novel ideas for new lines of re-search, or to continue the lines of research proposed by the authors.

  18. Bio indication of water quality in the Bogota Sabane using fuzzy logic sagging and aquatic micro invertebrates

    International Nuclear Information System (INIS)

    Gutierrez, Juan David; Riss Wolfgang; Ospina Rodolfo

    2002-01-01

    An application of the Sagging-type fuzzy logic to calculate biological water quality in Bogota, Colombia is presented 28 sites corresponding to 9 watersheds in the Bogota area were used. The organisms selected were: Leptoceridae and Hidrobiosidae as indicators of clean waters, Planariidae and Amphipoda as indicators of polluted waters and Psychodida and Syrphidae as indicators of highly polluted waters Chironomids were also included. In order to prove the degree of reliability of Sugeno-type fuzzy logic, the results obtained were compared with values for the Cfq index, and a highly significant correlation was obtained

  19. A new systematic and quantitative approach to characterization of surface nanostructures using fuzzy logic

    Science.gov (United States)

    Al-Mousa, Amjed A.

    Thin films are essential constituents of modern electronic devices and have a multitude of applications in such devices. The impact of the surface morphology of thin films on the device characteristics where these films are used has generated substantial attention to advanced film characterization techniques. In this work, we present a new approach to characterize surface nanostructures of thin films by focusing on isolating nanostructures and extracting quantitative information, such as the shape and size of the structures. This methodology is applicable to any Scanning Probe Microscopy (SPM) data, such as Atomic Force Microscopy (AFM) data which we are presenting here. The methodology starts by compensating the AFM data for some specific classes of measurement artifacts. After that, the methodology employs two distinct techniques. The first, which we call the overlay technique, proceeds by systematically processing the raster data that constitute the scanning probe image in both vertical and horizontal directions. It then proceeds by classifying points in each direction separately. Finally, the results from both the horizontal and the vertical subsets are overlaid, where a final decision on each surface point is made. The second technique, based on fuzzy logic, relies on a Fuzzy Inference Engine (FIE) to classify the surface points. Once classified, these points are clustered into surface structures. The latter technique also includes a mechanism which can consistently distinguish crowded surfaces from those with sparsely distributed structures and then tune the fuzzy technique system uniquely for that surface. Both techniques have been applied to characterize organic semiconductor thin films of pentacene on different substrates. Also, we present a case study to demonstrate the effectiveness of our methodology to identify quantitatively particle sizes of two specimens of gold nanoparticles of different nominal dimensions dispersed on a mica surface. A comparison

  20. Process Monitoring by combining several signal-analysis results using fuzzy logic

    International Nuclear Information System (INIS)

    Schoonwelle, H.; Van der Hagen, T.H.J.J.; Hoogenboom, J.E.

    1996-01-01

    In order to improve reliability in detecting anomalies in nuclear power plant performance, a method is presented which is based on acquiring various characteristics of signal data using autoregressive, wavelet and fractal-analysis techniques. These characteristics are combined using a decision making approach based on fuzzy logic. This approach is able to detect and distinguish several system states

  1. Expert systems with fuzzy logic for intelligent diagnosis and control of nuclear power plants

    International Nuclear Information System (INIS)

    Abdelhai, M.I.; Upadhyaya, B.R.

    1990-01-01

    A model-based production-rule analysis system was developed for the tracking and diagnosis of the condition of a reactor coolant system (RCS) using a fuzzy logic algorithm. Since nuclear power plants are large and complex systems, it is natural that vagueness, uncertainty, and imprecision are introduced to such systems. Even in fully automated power plants, the critical diagnostic and control changes must be made by operators who usually express their diagnostic and control strategies linguistically as sets of heuristic decision rules. Therefore, additional imprecisions are introduced into the systems because of the imprecise nature of such qualitative strategies when they are converted into quantitative rules. Such problems, in which the source of imprecision is the absence of sharply defined criteria of class membership, could be dealt with using fuzzy set theory. Hence, a fuzzy logic algorithm could be initiated to implement a known heuristic whenever the given information is vague and qualitative, and it will allow operators to introduce certain linguistic assertions and commands to diagnose and control the system

  2. Methodology of analysis sustainable development of Ukraine by using the theory fuzzy logic

    Directory of Open Access Journals (Sweden)

    Methodology of analysis sustainable development of Ukraine by using the theory fuzzy logic

    2016-02-01

    Full Text Available Article objective is analysis of the theoretical and methodological aspects for the assessment of sustainable development in times of crisis. The methodical approach to the analysis of sustainable development territory taking into account the assessment of the level of economic security has been proposed. A necessity of development of the complex methodical approach to the accounting of the indeterminacy properties and multicriterial in the tasks to provide economic safety on the basis of using the fuzzy logic theory (or the fuzzy sets theory was proved. The results of using the method of fuzzy sets of during the 2002-2012 years the dynamics of changes dynamics of sustainable development in Ukraine were presented.

  3. FUZZY-LOGIC-BASED CONTROLLERS FOR EFFICIENCY OPTIMIZATION OF INVERTER-FED INDUCTION MOTOR DRIVES

    Science.gov (United States)

    This paper describes a fuzzy-logic-based energy optimizing controller to improve the efficiency of induction motor/drives operating at various load (torque) and speed conditions. Improvement of induction motor efficiency is important not only from the considerations of energy sav...

  4. Performance analysis of PM synchronous motor using fuzzy logic and self tuning fuzzy PI speed controls

    International Nuclear Information System (INIS)

    Karakaya, A.; Karakas, E.

    2008-01-01

    Permanent Magnet Synchronous Motors have nonlinear characteristics whose dynamics changes with time. In spite of this structure the permanent magnet synchronous motor has answered engineering problems in industry such as motion control which need high torque values. This paper obtains a nonlinear mathematical model for Permanent Magnet Synchronous Motor and realizes stimulation of the obtained model in the Matlab/Simulink program. Motor parameters are determined by an experimental set-up and they are used in the motor model. Speed control of motor model is made with Fuzzy Logic and Self Tuning logic PI controllers. Using the speed graphs obtained, rise time, overshoot, steady-state error and settling time are analyzed and controller performances are compared. (author)

  5. Taguchi based fuzzy logic optimization of multiple quality characteristics in laser cutting of Duralumin sheet

    Science.gov (United States)

    Pandey, Arun Kumar; Dubey, Avanish Kumar

    2012-03-01

    Capability of laser cutting mainly depends on optical and thermal properties of work material. Highly reflective and thermally conductive Duralumin sheets are difficult-to-laser-cut. Application of Duralumin sheets in aeronautic and automotive industries due to its high strength to weight ratio demand narrow and complex cuts with high geometrical accuracy. The present paper experimentally investigates the laser cutting of Duralumin sheet with the aim to improve geometrical accuracy by simultaneously minimizing the kerf width and kerf deviations at top and bottom sides. A hybrid approach, obtained by combining robust parameter design methodology and Fuzzy logic theory has been applied to compute the fuzzy multi-response performance index. This performance index is further used for multi-objective optimization. The predicted optimum results have been verified by performing the confirmation tests. The confirmation tests show considerable reduction in kerf deviations at top and bottom sides.

  6. Determination of Biological Treatability Processes of Textile Wastewater and Implementation of a Fuzzy Logic Model

    Directory of Open Access Journals (Sweden)

    Harun Akif Kabuk

    2015-01-01

    Full Text Available This study investigated the biological treatability of textile wastewater. For this purpose, a membrane bioreactor (MBR was utilized for biological treatment after the ozonation process. Due to the refractory organic contents of textile wastewater that has a low biodegradability capacity, ozonation was implemented as an advanced oxidation process prior to the MBR system to increase the biodegradability of the wastewater. Textile wastewater, oxidized by ozonation, was fed to the MBR at different hydraulic retention times (HRT. During the process, color, chemical oxygen demand (COD, and biochemical oxygen demand (BOD removal efficiencies were monitored for 24-hour, 12-hour, 6-hour, and 3-hour retention times. Under these conditions, 94% color, 65% COD, and 55% BOD removal efficiencies were obtained in the MBR system. The experimental outputs were modeled with multiple linear regressions (MLR and fuzzy logic. MLR results suggested that color removal is more related to COD removal relative to BOD removal. A surface map of this issue was prepared with a fuzzy logic model. Furthermore, fuzzy logic was employed to the whole modeling of the biological system treatment. Determination coefficients for COD, BOD, and color removal efficiencies were 0.96, 0.97, and 0.92, respectively.

  7. A first course in fuzzy logic, fuzzy dynamical systems, and biomathematics theory and applications

    CERN Document Server

    de Barros, Laécio Carvalho; Lodwick, Weldon Alexander

    2017-01-01

    This book provides an essential introduction to the field of dynamical models. Starting from classical theories such as set theory and probability, it allows readers to draw near to the fuzzy case. On one hand, the book equips readers with a fundamental understanding of the theoretical underpinnings of fuzzy sets and fuzzy dynamical systems. On the other, it demonstrates how these theories are used to solve modeling problems in biomathematics, and presents existing derivatives and integrals applied to the context of fuzzy functions. Each of the major topics is accompanied by examples, worked-out exercises, and exercises to be completed. Moreover, many applications to real problems are presented. The book has been developed on the basis of the authors’ lectures to university students and is accordingly primarily intended as a textbook for both upper-level undergraduates and graduates in applied mathematics, statistics, and engineering. It also offers a valuable resource for practitioners such as mathematical...

  8. Short-term prediction of solar energy in Saudi Arabia using automated-design fuzzy logic systems.

    Science.gov (United States)

    Almaraashi, Majid

    2017-01-01

    Solar energy is considered as one of the main sources for renewable energy in the near future. However, solar energy and other renewable energy sources have a drawback related to the difficulty in predicting their availability in the near future. This problem affects optimal exploitation of solar energy, especially in connection with other resources. Therefore, reliable solar energy prediction models are essential to solar energy management and economics. This paper presents work aimed at designing reliable models to predict the global horizontal irradiance (GHI) for the next day in 8 stations in Saudi Arabia. The designed models are based on computational intelligence methods of automated-design fuzzy logic systems. The fuzzy logic systems are designed and optimized with two models using fuzzy c-means clustering (FCM) and simulated annealing (SA) algorithms. The first model uses FCM based on the subtractive clustering algorithm to automatically design the predictor fuzzy rules from data. The second model is using FCM followed by simulated annealing algorithm to enhance the prediction accuracy of the fuzzy logic system. The objective of the predictor is to accurately predict next-day global horizontal irradiance (GHI) using previous-day meteorological and solar radiation observations. The proposed models use observations of 10 variables of measured meteorological and solar radiation data to build the model. The experimentation and results of the prediction are detailed where the root mean square error of the prediction was approximately 88% for the second model tuned by simulated annealing compared to 79.75% accuracy using the first model. This results demonstrate a good modeling accuracy of the second model despite that the training and testing of the proposed models were carried out using spatially and temporally independent data.

  9. Power control of SAFE reactor using fuzzy logic

    International Nuclear Information System (INIS)

    Irvine, Claude

    2002-01-01

    Controlling the 100 kW SAFE (Safe Affordable Fission Engine) reactor consists of design and implementation of a fuzzy logic process control system to regulate dynamic variables related to nuclear system power. The first phase of development concentrates primarily on system power startup and regulation, maintaining core temperature equilibrium, and power profile matching. This paper discusses the experimental work performed in those areas. Nuclear core power from the fuel elements is simulated using resistive heating elements while heat rejection is processed by a series of heat pipes. Both axial and radial nuclear power distributions are determined from neuronic modeling codes. The axial temperature profile of the simulated core is matched to the nuclear power profile by varying the resistance of the heating elements. The SAFE model establishes radial temperature profile equivalence by establishing 32 control zones as the nodal coordinates. Control features also allow for slow warm up, since complete shutoff can occur in the heat pipes if heat-source temperatures drop/rise below a certain minimum value, depending on the specific fluid and gas combination in the heat pipe. The entire system is expected to be self-adaptive, i.e., capable of responding to long-range changes in the space environment. Particular attention in the development of the fuzzy logic algorithm shall ensure that the system process remains at set point, virtually eliminating overshoot on start-up and during in-process disturbances. The controller design will withstand harsh environments and applications where it might come in contact with water, corrosive chemicals, radiation fields, etc

  10. Creating Clinical Fuzzy Automata with Fuzzy Arden Syntax.

    Science.gov (United States)

    de Bruin, Jeroen S; Steltzer, Heinz; Rappelsberger, Andrea; Adlassnig, Klaus-Peter

    2017-01-01

    Formal constructs for fuzzy sets and fuzzy logic are incorporated into Arden Syntax version 2.9 (Fuzzy Arden Syntax). With fuzzy sets, the relationships between measured or observed data and linguistic terms are expressed as degrees of compatibility that model the unsharpness of the boundaries of linguistic terms. Propositional uncertainty due to incomplete knowledge of relationships between clinical linguistic concepts is modeled with fuzzy logic. Fuzzy Arden Syntax also supports the construction of fuzzy state monitors. The latter are defined as monitors that employ fuzzy automata to observe gradual transitions between different stages of disease. As a use case, we re-implemented FuzzyARDS, a previously published clinical monitoring system for patients suffering from acute respiratory distress syndrome (ARDS). Using the re-implementation as an example, we show how key concepts of fuzzy automata, i.e., fuzzy states and parallel fuzzy state transitions, can be implemented in Fuzzy Arden Syntax. The results showed that fuzzy state monitors can be implemented in a straightforward manner.

  11. Fuzzy Logic Based Autonomous Parallel Parking System with Kalman Filtering

    Science.gov (United States)

    Panomruttanarug, Benjamas; Higuchi, Kohji

    This paper presents an emulation of fuzzy logic control schemes for an autonomous parallel parking system in a backward maneuver. There are four infrared sensors sending the distance data to a microcontroller for generating an obstacle-free parking path. Two of them mounted on the front and rear wheels on the parking side are used as the inputs to the fuzzy rules to calculate a proper steering angle while backing. The other two attached to the front and rear ends serve for avoiding collision with other cars along the parking space. At the end of parking processes, the vehicle will be in line with other parked cars and positioned in the middle of the free space. Fuzzy rules are designed based upon a wall following process. Performance of the infrared sensors is improved using Kalman filtering. The design method needs extra information from ultrasonic sensors. Starting from modeling the ultrasonic sensor in 1-D state space forms, one makes use of the infrared sensor as a measurement to update the predicted values. Experimental results demonstrate the effectiveness of sensor improvement.

  12. Application of a PID controller based on fuzzy logic to reduce variations in the control parameters in PWR reactors

    International Nuclear Information System (INIS)

    Vasconcelos, Wagner Eustaquio de; Lira, Carlos Alberto Brayner de Oliveira; Brito, Thiago Souza Pereira de; Afonso, Antonio Claudio Marques; Cruz Filho, Antonio Jose da; Marques, Jose Antonio; Teixeira, Marcello Goulart

    2013-01-01

    Nuclear reactors are in nature nonlinear systems and their parameters vary with time as a function of power level. These characteristics must be considered if large power variations occur in power plant operational regimes, such as in load-following conditions. A PWR reactor has a component called pressurizer, whose function is to supply the necessary high pressure for its operation and to contain pressure variations in the primary cooling system. The use of control systems capable of reducing fast variations of the operation variables and to maintain the stability of this system is of fundamental importance. The best-known controllers used in industrial control processes are proportional-integral-derivative (PID) controllers due to their simple structure and robust performance in a wide range of operating conditions. However, designing a fuzzy controller is seen to be a much less difficult task. Once a Fuzzy Logic controller is designed for a particular set of parameters of the nonlinear element, it yields satisfactory performance for a range of these parameters. The objective of this work is to develop fuzzy proportional-integral-derivative (fuzzy-PID) control strategies to control the level of water in the reactor. In the study of the pressurizer, several computer codes are used to simulate its dynamic behavior. At the fuzzy-PID control strategy, the fuzzy logic controller is exploited to extend the finite sets of PID gains to the possible combinations of PID gains in stable region. Thus the fuzzy logic controller tunes the gain of PID controller to adapt the model with changes in the water level of reactor. The simulation results showed a favorable performance with the use to fuzzy-PID controllers. (author)

  13. Fuzzy logic approach to SWOT analysis for economics tasks and example of its computer realization

    Directory of Open Access Journals (Sweden)

    Vladimir CHERNOV

    2016-07-01

    Full Text Available The article discusses the widely used classic method of analysis, forecasting and decision-making in the various economic problems, called SWOT analysis. As known, it is a qualitative comparison of multicriteria degree of Strength, Weakness, Opportunity, Threat for different kinds of risks, forecasting the development in the markets, status and prospects of development of enterprises, regions and economic sectors, territorials etc. It can also be successfully applied to the evaluation and analysis of different project management tasks - investment, innovation, marketing, development, design and bring products to market and so on. However, in practical competitive market and economic conditions, there are various uncertainties, ambiguities, vagueness. Its making usage of SWOT analysis in the classical sense not enough reasonable and ineffective. In this case, the authors propose to use fuzzy logic approach and the theory of fuzzy sets for a more adequate representation and posttreatment assessments in the SWOT analysis. In particular, has been short showed the mathematical formulation of respective task and the main approaches to its solution. Also are given examples of suitable computer calculations in specialized software Fuzicalc for processing and operations with fuzzy input data. Finally, are presented considerations for interpretation of the results.

  14. Fuzzy Logic Based Edge Detection in Smooth and Noisy Clinical Images.

    Directory of Open Access Journals (Sweden)

    Izhar Haq

    Full Text Available Edge detection has beneficial applications in the fields such as machine vision, pattern recognition and biomedical imaging etc. Edge detection highlights high frequency components in the image. Edge detection is a challenging task. It becomes more arduous when it comes to noisy images. This study focuses on fuzzy logic based edge detection in smooth and noisy clinical images. The proposed method (in noisy images employs a 3 × 3 mask guided by fuzzy rule set. Moreover, in case of smooth clinical images, an extra mask of contrast adjustment is integrated with edge detection mask to intensify the smooth images. The developed method was tested on noise-free, smooth and noisy images. The results were compared with other established edge detection techniques like Sobel, Prewitt, Laplacian of Gaussian (LOG, Roberts and Canny. When the developed edge detection technique was applied to a smooth clinical image of size 270 × 290 pixels having 24 dB 'salt and pepper' noise, it detected very few (22 false edge pixels, compared to Sobel (1931, Prewitt (2741, LOG (3102, Roberts (1451 and Canny (1045 false edge pixels. Therefore it is evident that the developed method offers improved solution to the edge detection problem in smooth and noisy clinical images.

  15. Enhancement of micro-grid performance during islanding mode using storage batteries and new fuzzy logic pitch angle controller

    International Nuclear Information System (INIS)

    Kamel, Rashad M.; Chaouachi, A.; Nagasaka, Ken

    2011-01-01

    Research highlights: → Novel fuzzy pitch angle controller is proposed for smoothing wind fluctuation. → Storage batteries are used for performance improve of MG in islanding mode. → Those new techniques are compared with conventional PI pitch angle controller. -- Abstract: Power system deregulation, shortage of transmission capacities and needing to reduce green house gas have led to increase interesting in distributed generations (DGs) especially renewable sources. This study developed a complete model able to analysis and simulates in details the transient dynamic performance of the Micro-Grid (MG) during and subsequent islanding process. Wind speed fluctuations cause high fluctuations in output power of wind turbine which lead to fluctuations of frequency and voltages of the MG during the islanding mode. In this paper a new fuzzy logic pitch angle controller is proposed to smooth the output power of wind turbine to reduce MG frequency and voltage fluctuations during the islanding mode. The proposed fuzzy logic pitch controller is compared with the conventional PI pitch angle controller which usually used for wind turbine power control. Results proved the effectiveness of the proposed fuzzy controller in improvement of the MG performance. Also, this paper proposed using storage batteries technique to reduce the frequency deviation and fluctuations originated from wind power solar power fluctuations. Results indicate that the storage batteries technique is superior than fuzzy logic pitch controller in reducing frequency deviation, but with more expensive than the fuzzy controller. All models and controllers are built using Matlab (registered) Simulink (registered) environment.

  16. Construction of Fuzzy Sets and Applying Aggregation Operators for Fuzzy Queries

    DEFF Research Database (Denmark)

    Hudec, Miroslav; Sudzina, Frantisek

    Flexible query conditions could use linguistic terms described by fuzzy sets. The question is how to properly construct fuzzy sets for each linguistic term and apply an adequate aggregation function. For construction of fuzzy sets, the lowest value, the highest value of attribute...... and the distribution of data inside its domain are used. The logarithmic transformation of domains appears to be suitable. This way leads to a balanced distribution of tuples over fuzzy sets. In addition, users’ opinions about linguistic terms as well as current content in database are merged. The second investigated...

  17. Toward Determination of Venous Thrombosis Ages by Using Fuzzy Logic and Supervised Bayes Classification

    National Research Council Canada - National Science Library

    Lim, P

    2001-01-01

    .... Thus, the proposed learning base is constructed in a 3-tuple: observation, label, membership value in term of fuzzy logic for each class and not a 2-tuple as in the usual supervised Bayes classification application...

  18. Force control of a tri-layer conducting polymer actuator using optimized fuzzy logic control

    International Nuclear Information System (INIS)

    Itik, Mehmet; Sabetghadam, Mohammadreza; Alici, Gursel

    2014-01-01

    Conducting polymers actuators (CPAs) are potential candidates for replacing conventional actuators in various fields, such as robotics and biomedical engineering, due to their advantageous properties, which includes their low cost, light weight, low actuation voltage and biocompatibility. As these actuators are very suitable for use in micro-nano manipulation and in injection devices in which the magnitude of the force applied to the target is of crucial importance, the force generated by CPAs needs to be accurately controlled. In this paper, a fuzzy logic (FL) controller with a Mamdani inference system is designed to control the blocking force of a trilayer CPA with polypyrrole electrodes, which operates in air. The particle swarm optimization (PSO) method is employed to optimize the controller’s membership function parameters and therefore enhance the performance of the FL controller. An adaptive neuro-fuzzy inference system model, which can capture the nonlinear dynamics of the actuator, is utilized in the optimization process. The optimized Mamdani FL controller is then implemented on the CPA experimentally, and its performance is compared with a non-optimized fuzzy controller as well as with those obtained from a conventional PID controller. The results presented indicate that the blocking force at the tip of the CPA can be effectively controlled by the optimized FL controller, which shows excellent transient and steady state characteristics but increases the control voltage compared to the non-optimized fuzzy controllers. (paper)

  19. Logika Fuzzy untuk Audit Sistem Informasi

    Directory of Open Access Journals (Sweden)

    Hari Setiabudi Husni

    2013-06-01

    Full Text Available The aim of this research is to study and introduce fuzzy logic into audit information system. Fuzzy logic is already adopted in other field of study. It helps decision process that incorporates subjective information and transforms it to scientific objective information which is more accepted. This research implements simulation scenario to see how fuzzy logic concept should be used in audit information process. The result shows that there is a possible concept of fuzzy logic that can be used for helping auditor in making objective decision in audit information system process. More researches needed to further explore the fuzzy logic concept such as creating the system of fuzzy logic and build application that can be used for daily information system audit process. 

  20. Multi-region fuzzy logic controller with local PID controllers for U-tube steam generator in nuclear power plant

    Directory of Open Access Journals (Sweden)

    Puchalski Bartosz

    2015-12-01

    Full Text Available In the paper, analysis of multi-region fuzzy logic controller with local PID controllers for steam generator of pressurized water reactor (PWR working in wide range of thermal power changes is presented. The U-tube steam generator has a nonlinear dynamics depending on thermal power transferred from coolant of the primary loop of the PWR plant. Control of water level in the steam generator conducted by a traditional PID controller which is designed for nominal power level of the nuclear reactor operates insufficiently well in wide range of operational conditions, especially at the low thermal power level. Thus the steam generator is often controlled manually by operators. Incorrect water level in the steam generator may lead to accidental shutdown of the nuclear reactor and consequently financial losses. In the paper a comparison of proposed multi region fuzzy logic controller and traditional PID controllers designed only for nominal condition is presented. The gains of the local PID controllers have been derived by solving appropriate optimization tasks with the cost function in a form of integrated squared error (ISE criterion. In both cases, a model of steam generator which is readily available in literature was used for control algorithms synthesis purposes. The proposed multi-region fuzzy logic controller and traditional PID controller were subjected to broad-based simulation tests in rapid prototyping software - Matlab/Simulink. These tests proved the advantage of multi-region fuzzy logic controller with local PID controllers over its traditional counterpart.

  1. Expert evaluation of innovation projects of mining enterprises on the basis of methods of system analysis and fuzzy logics

    Directory of Open Access Journals (Sweden)

    Pimonov Alexander

    2017-01-01

    Full Text Available This paper presents the multipurpose approach to evaluation of research and innovation projects based on the method of analysis of hierarchies and fuzzy logics for the mining industry. The approach, implemented as part of a decision support system, can reduce the degree of subjectivity during examinations by taking into account both quantitative and qualitative characteristics of the compared innovative alternatives; it does not depend on specific conditions of examination and allows engagement of experts of various fields of knowledge. The system includes the mechanism of coordination of several experts’ views. Using of fuzzy logics allows evaluating the qualitative characteristics of innovations in the form of formalized logical conclusions.

  2. Sparking-out optimization while surface grinding aluminum alloy 1933T2 parts using fuzzy logic

    Science.gov (United States)

    Soler, Ya I.; Salov, V. M.; Kien Nguyen, Chi

    2018-03-01

    The article presents the results of a search for optimal sparing-out strokes when surface grinding aluminum parts by high-porous wheels Norton of black silicon carbide 37C80K12VP using fuzzy logic. The topography of grinded surface is evaluated according to the following parameters: roughness – Ra, Rmax, Sm; indicators of flatness deviation – EFEmax, EFEa, EFEq; microhardness HV, each of these parameters is represented by two measures of position and dispersion. The simulation results of fuzzy logic in the Matlab medium establish that during the grinding of alloy 1933T2, the best integral performance evaluation of sparking-out was given to two double-strokes (d=0.827) and the worst – to three ones (d=0.405).

  3. Fuzzy Logic Controller Stability Analysis Using a Satisfiability Modulo Theories Approach

    Science.gov (United States)

    Arnett, Timothy; Cook, Brandon; Clark, Matthew A.; Rattan, Kuldip

    2017-01-01

    While many widely accepted methods and techniques exist for validation and verification of traditional controllers, at this time no solutions have been accepted for Fuzzy Logic Controllers (FLCs). Due to the highly nonlinear nature of such systems, and the fact that developing a valid FLC does not require a mathematical model of the system, it is quite difficult to use conventional techniques to prove controller stability. Since safety-critical systems must be tested and verified to work as expected for all possible circumstances, the fact that FLC controllers cannot be tested to achieve such requirements poses limitations on the applications for such technology. Therefore, alternative methods for verification and validation of FLCs needs to be explored. In this study, a novel approach using formal verification methods to ensure the stability of a FLC is proposed. Main research challenges include specification of requirements for a complex system, conversion of a traditional FLC to a piecewise polynomial representation, and using a formal verification tool in a nonlinear solution space. Using the proposed architecture, the Fuzzy Logic Controller was found to always generate negative feedback, but inconclusive for Lyapunov stability.

  4. Fuzzy Logic-Based Model That Incorporates Personality Traits for Heterogeneous Pedestrians

    Directory of Open Access Journals (Sweden)

    Zhuxin Xue

    2017-10-01

    Full Text Available Most models designed to simulate pedestrian dynamical behavior are based on the assumption that human decision-making can be described using precise values. This study proposes a new pedestrian model that incorporates fuzzy logic theory into a multi-agent system to address cognitive behavior that introduces uncertainty and imprecision during decision-making. We present a concept of decision preferences to represent the intrinsic control factors of decision-making. To realize the different decision preferences of heterogeneous pedestrians, the Five-Factor (OCEAN personality model is introduced to model the psychological characteristics of individuals. Then, a fuzzy logic-based approach is adopted for mapping the relationships between the personality traits and the decision preferences. Finally, we have developed an application using our model to simulate pedestrian dynamical behavior in several normal or non-panic scenarios, including a single-exit room, a hallway with obstacles, and a narrowing passage. The effectiveness of the proposed model is validated with a user study. The results show that the proposed model can generate more reasonable and heterogeneous behavior in the simulation and indicate that individual personality has a noticeable effect on pedestrian dynamical behavior.

  5. Performance Modelling of Steam Turbine Performance using Fuzzy ...

    African Journals Online (AJOL)

    Performance Modelling of Steam Turbine Performance using Fuzzy Logic ... AFRICAN JOURNALS ONLINE (AJOL) · Journals · Advanced Search · USING AJOL · RESOURCES. Journal of Applied Sciences and Environmental Management ... A Fuzzy Inference System for predicting the performance of steam turbine

  6. Computation On dP Type power System Stabilizer Using Fuzzy Logic

    International Nuclear Information System (INIS)

    Iskandar, M.A.; Irwan, R.; Husdi; Riza; Mardhana, E.; Triputranto, A.

    1997-01-01

    Power system stabilizers (PSS) are widely applied in power generators to damp power oscillation caused by certain disturbances in order to increase the power supply capacity. PSS design is often suffered from the difficulty on setting periodically its parameters, which are gain and compensators, in order to have an optimal damping characteristic. This paper proposes a methode to determine parameters of dP type PSS by implementing fuzzy logic rules in a computer program,to obtain the appropriate characteristics of synchronous torque and damping torque. PSS with the calculated parameters is investigated on a simulation using a non-linear electric power system of a thermal generator connected to infinite bus system model. Simulation results show that great improvement in damping characteristic and enhancement of stability margin of electric power system are obtained by using the proposed PSS

  7. Embedding Logics into Product Logic

    Czech Academy of Sciences Publication Activity Database

    Baaz, M.; Hájek, Petr; Krajíček, Jan; Švejda, David

    1998-01-01

    Roč. 61, č. 1 (1998), s. 35-47 ISSN 0039-3215 R&D Projects: GA AV ČR IAA1030601 Grant - others:COST(XE) Action 15 Keywords : fuzzy logic * Lukasiewicz logic * Gödel logic * product logic * computational complexity * arithmetical hierarchy Subject RIV: BA - General Mathematics

  8. Using boolean and fuzzy logic combined with analytic hierarchy process for hazardous waste landfill site selection: A case study from Hormozgan province, Iran

    Directory of Open Access Journals (Sweden)

    Mahdieh Saadat Foomani

    2017-01-01

    Full Text Available Hazardous wastes include numerous kinds of discarded chemicals and other wastes generated from industrial, commercial, and institutional activities. These types of waste present immediate or long-term risks to humans, animals, plants, or the environment and therefore require special handling for safe disposal. Landfills that can accept hazardous wastes are excavated or engineered sites where these special types of waste can be disposed of securely. Since landfills are permanent sites, special attention must be afforded in selecting the location. This paper investigated the use of the Boolean theory and Fuzzy logic in combination with Analytic Hierarchy Process (AHP methods by applying GIS and IDRISI software for the selection of a hazardous waste landfill site in the Iranian province of Hormozgan. The best location was determined via the Fuzzy and the Boolean methodologies. By collating the area selected for the hazardous waste landfill, this study found that Fuzzy logic with an AND operator had the best options for this purpose. In the end, the most suitable area for a hazardous waste landfill was about 1.6 km2 which was obtained by employing Fuzzy in combination with AHP and by using an AND operator. In addition, all the fundamental criteria affecting the landfill location were considered.

  9. Analysis of Electrical Safety Conditions Taking into Account Soil Conductivity Determined on the Basis of Fuzzy Logic

    OpenAIRE

    Manusov, V.Z.; Zaytseva, N.M.

    2017-01-01

    The goal of this work is to prove a possibility of determining soil parameters that influence its conductivity being the basis of grounding, step voltage and touch voltage calculation. This in its turn increases the safety level of electric equipment operation. The article is devoted to development of new, no conventional models of soil conductivity using the theory of fuzzy sets and fuzzy logic. The description of the solution includes the following sections: fuzzy models of specific electri...

  10. Fruit Sorting Using Fuzzy Logic Techniques

    Science.gov (United States)

    Elamvazuthi, Irraivan; Sinnadurai, Rajendran; Aftab Ahmed Khan, Mohamed Khan; Vasant, Pandian

    2009-08-01

    Fruit and vegetables market is getting highly selective, requiring their suppliers to distribute the goods according to very strict standards of quality and presentation. In the last years, a number of fruit sorting and grading systems have appeared to fulfill the needs of the fruit processing industry. However, most of them are overly complex and too costly for the small and medium scale industry (SMIs) in Malaysia. In order to address these shortcomings, a prototype machine was developed by integrating the fruit sorting, labeling and packing processes. To realise the prototype, many design issues were dealt with. Special attention is paid to the electronic weighing sub-system for measuring weight, and the opto-electronic sub-system for determining the height and width of the fruits. Specifically, this paper discusses the application of fuzzy logic techniques in the sorting process.

  11. ARTIFICIAL NEURAL NETWORK AND FUZZY LOGIC CONTROLLER FOR GTAW MODELING AND CONTROL

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    An artificial neural network(ANN) and a self-adjusting fuzzy logic controller(FLC) for modeling and control of gas tungsten arc welding(GTAW) process are presented. The discussion is mainly focused on the modeling and control of the weld pool depth with ANN and the intelligent control for weld seam tracking with FLC. The proposed neural network can produce highly complex nonlinear multi-variable model of the GTAW process that offers the accurate prediction of welding penetration depth. A self-adjusting fuzzy controller used for seam tracking adjusts the control parameters on-line automatically according to the tracking errors so that the torch position can be controlled accurately.

  12. The gap values in the profile matching method by fuzzy logic

    Science.gov (United States)

    Sitepu, S. A.; Efendi, S.; Situmorang, Z.

    2018-03-01

    In this research, the determination of the appropriate values of Gap for the assessment of promotion criteria of position in an institution / company. In this study the authors use Fuzzy Sugeno logic on the determination of Gap values used in Profile Matching method. Test results of 5 employees obtained the eligibility of promotion with the position of Z* values between in 3.20 to 4.11.

  13. Profitability analysis of a femtosecond laser system for cataract surgery using a fuzzy logic approach.

    Science.gov (United States)

    Trigueros, José Antonio; Piñero, David P; Ismail, Mahmoud M

    2016-01-01

    To define the financial and management conditions required to introduce a femtosecond laser system for cataract surgery in a clinic using a fuzzy logic approach. In the simulation performed in the current study, the costs associated to the acquisition and use of a commercially available femtosecond laser platform for cataract surgery (VICTUS, TECHNOLAS Perfect Vision GmbH, Bausch & Lomb, Munich, Germany) during a period of 5y were considered. A sensitivity analysis was performed considering such costs and the countable amortization of the system during this 5y period. Furthermore, a fuzzy logic analysis was used to obtain an estimation of the money income associated to each femtosecond laser-assisted cataract surgery (G). According to the sensitivity analysis, the femtosecond laser system under evaluation can be profitable if 1400 cataract surgeries are performed per year and if each surgery can be invoiced more than $500. In contrast, the fuzzy logic analysis confirmed that the patient had to pay more per surgery, between $661.8 and $667.4 per surgery, without considering the cost of the intraocular lens (IOL). A profitability of femtosecond laser systems for cataract surgery can be obtained after a detailed financial analysis, especially in those centers with large volumes of patients. The cost of the surgery for patients should be adapted to the real flow of patients with the ability of paying a reasonable range of cost.

  14. Fuzzy logic utilization for the diagnosis of metallic loose part impact in nuclear power plant

    International Nuclear Information System (INIS)

    Oh, Y.-G.; Hong, H.-P.; Han, S.-J.; Chun, C.S.; Kim, B.-K.

    1996-01-01

    In consideration of the fuzzy nature of impact signals detected from the complex mechanical structures in a nuclear power plant under operation. Loose Part Monitoring System with a signal processing technique utilizing fuzzy logic is proposed. In the proposed Fuzzy Loose Part Monitoring System design, comprehensive relations among the impact signal features are taken into account in the fuzzy rule bases for the alarm discrimination and impact event diagnosis. Through the performance test with a mock-up facility, the proposed approach for the loose parts monitoring and diagnosis has been revealed to be effective not only in suppressing the false alarm generation but also in characterizing the metallic loose-part impact event, from the points of Possible Impacted-Area and Degree of Impact Magnitude

  15. A fuzzy logic based PROMETHEE method for material selection problems

    Directory of Open Access Journals (Sweden)

    Muhammet Gul

    2018-03-01

    Full Text Available Material selection is a complex problem in the design and development of products for diverse engineering applications. This paper presents a fuzzy PROMETHEE (Preference Ranking Organization Method for Enrichment Evaluation method based on trapezoidal fuzzy interval numbers that can be applied to the selection of materials for an automotive instrument panel. Also, it presents uniqueness in making a significant contribution to the literature in terms of the application of fuzzy decision-making approach to material selection problems. The method is illustrated, validated, and compared against three different fuzzy MCDM methods (fuzzy VIKOR, fuzzy TOPSIS, and fuzzy ELECTRE in terms of its ranking performance. Also, the relationships between the compared methods and the proposed scenarios for fuzzy PROMETHEE are evaluated via the Spearman’s correlation coefficient. Styrene Maleic Anhydride and Polypropylene are determined optionally as suitable materials for the automotive instrument panel case. We propose a generic fuzzy MCDM methodology that can be practically implemented to material selection problem. The main advantages of the methodology are consideration of the vagueness, uncertainty, and fuzziness to decision making environment.

  16. Optimization of heat pump using fuzzy logic and genetic algorithm

    Energy Technology Data Exchange (ETDEWEB)

    Sahin, Arzu Sencan [Sueleyman Demirel University, Technology Faculty, Isparta (Turkey); Kilic, Bayram; Kilic, Ulas [Bucak Emin Guelmez Vocational School, Mehmet Akif Ersoy University, Bucak (Turkey)

    2011-12-15

    Heat pumps offer economical alternatives of recovering heat from different sources for use in various industrial, commercial and residential applications. In this study, single-stage air-source vapor compression heat pump system has been optimized using genetic algorithm (GA) and fuzzy logic (FL). The necessary thermodynamic properties for optimization were calculated by FL. Thermodynamic properties obtained with FL were compared with actual results. Then, the optimum working conditions of heat pump system were determined by the GA. (orig.)

  17. Fuzzy Logic based Handoff Latency Reduction Mechanism in Layer 2 of Heterogeneous Mobile IPv6 Networks

    Science.gov (United States)

    Anwar, Farhat; Masud, Mosharrof H.; Latif, Suhaimi A.

    2013-12-01

    Mobile IPv6 (MIPv6) is one of the pioneer standards that support mobility in IPv6 environment. It has been designed to support different types of technologies for providing seamless communications in next generation network. However, MIPv6 and subsequent standards have some limitations due to its handoff latency. In this paper, a fuzzy logic based mechanism is proposed to reduce the handoff latency of MIPv6 for Layer 2 (L2) by scanning the Access Points (APs) while the Mobile Node (MN) is moving among different APs. Handoff latency occurs when the MN switches from one AP to another in L2. Heterogeneous network is considered in this research in order to reduce the delays in L2. Received Signal Strength Indicator (RSSI) and velocity of the MN are considered as the input of fuzzy logic technique. This technique helps the MN to measure optimum signal quality from APs for the speedy mobile node based on fuzzy logic input rules and makes a list of interfaces. A suitable interface from the list of available interfaces can be selected like WiFi, WiMAX or GSM. Simulation results show 55% handoff latency reduction and 50% packet loss improvement in L2 compared to standard to MIPv6.

  18. Fuzzy Logic based Handoff Latency Reduction Mechanism in Layer 2 of Heterogeneous Mobile IPv6 Networks

    International Nuclear Information System (INIS)

    Anwar, Farhat; Masud, Mosharrof H; Latif, Suhaimi A

    2013-01-01

    Mobile IPv6 (MIPv6) is one of the pioneer standards that support mobility in IPv6 environment. It has been designed to support different types of technologies for providing seamless communications in next generation network. However, MIPv6 and subsequent standards have some limitations due to its handoff latency. In this paper, a fuzzy logic based mechanism is proposed to reduce the handoff latency of MIPv6 for Layer 2 (L2) by scanning the Access Points (APs) while the Mobile Node (MN) is moving among different APs. Handoff latency occurs when the MN switches from one AP to another in L2. Heterogeneous network is considered in this research in order to reduce the delays in L2. Received Signal Strength Indicator (RSSI) and velocity of the MN are considered as the input of fuzzy logic technique. This technique helps the MN to measure optimum signal quality from APs for the speedy mobile node based on fuzzy logic input rules and makes a list of interfaces. A suitable interface from the list of available interfaces can be selected like WiFi, WiMAX or GSM. Simulation results show 55% handoff latency reduction and 50% packet loss improvement in L2 compared to standard to MIPv6

  19. Application of the removal of pollutants from textile industry wastewater in constructed wetlands using fuzzy logic.

    Science.gov (United States)

    Dogdu, Gamze; Yalcuk, Arda; Postalcioglu, Seda

    2017-02-01

    There are more than a hundred textile industries in Turkey that discharge large quantities of dye-rich wastewater, resulting in water pollution. Such effluents must be treated to meet discharge limits imposed by the Water Framework Directive in Turkey. Industrial treatment facilities must be required to monitor operations, keep them cost-effective, prevent operational faults, discharge-limit infringements, and water pollution. This paper proposes the treatment of actual textile wastewater by vertical flow constructed wetland (VFCW) systems operation and monitoring effluent wastewater quality using fuzzy logic with a graphical user interface. The treatment performance of VFCW is investigated in terms of chemical oxygen demand and ammonium nitrogen (NH4-N) content, color, and pH parameters during a 75-day period of operation. A computer program was developed with a fuzzy logic system (a decision- making tool) to graphically present (via a status analysis chart) the quality of treated textile effluent in relation to the Turkish Water Pollution Control Regulation. Fuzzy logic is used in the evaluation of data obtained from the VFCW systems and for notification of critical states exceeding the discharge limits. This creates a warning chart that reports any errors encountered in a reactor during the collection of any sample to the concerned party.

  20. D-FLER - A Distributed Fuzzy Logic Engine for Rule-Based Wireless Sensor Networks

    NARCIS (Netherlands)

    Marin Perianu, Mihai; Havinga, Paul J.M.

    2007-01-01

    We propose D-FLER, a distributed, general-purpose reasoning engine for WSN. D-FLER uses fuzzy logic for fusing individual and neighborhood observations, in order to produce a more accurate and reliable result. Thorough simulation, we evaluate D-FLER in a fire-detection scenario, using both fire and

  1. D-FLER: A Distributed Fuzzy Logic Engine for Rule-based Wireless Sensor Networks

    NARCIS (Netherlands)

    Marin Perianu, Mihai; Havinga, Paul J.M.

    2007-01-01

    We propose D-FLER, a distributed, general-purpose reasoning engine for WSN. D-FLER uses fuzzy logic for fusing individual and neighborhood observations, in order to produce a more accurate and reliable result. Thorough simulation, we evaluate D-FLER in a fire-detection scenario, using both fire and

  2. Model for Adjustment of Aggregate Forecasts using Fuzzy Logic

    Directory of Open Access Journals (Sweden)

    Taracena–Sanz L. F.

    2010-07-01

    Full Text Available This research suggests a contribution in the implementation of forecasting models. The proposed model is developed with the aim to fit the projection of demand to surroundings of firms, and this is based on three considerations that cause that in many cases the forecasts of the demand are different from reality, such as: 1 one of the problems most difficult to model in the forecasts is the uncertainty related to the information available; 2 the methods traditionally used by firms for the projection of demand mainly are based on past behavior of the market (historical demand; and 3 these methods do not consider in their analysis the factors that are influencing so that the observed behaviour occurs. Therefore, the proposed model is based on the implementation of Fuzzy Logic, integrating the main variables that affect the behavior of market demand, and which are not considered in the classical statistical methods. The model was applied to a bottling of carbonated beverages, and with the adjustment of the projection of demand a more reliable forecast was obtained.

  3. Nursing and fuzzy logic: an integrative review Enfermería y lógica fuzzy: una revisión de integradora Enfermagem e lógica fuzzy: uma revisão integrativa

    Directory of Open Access Journals (Sweden)

    Rodrigo Jensen

    2011-02-01

    Full Text Available This study conducted an integrative review investigating how fuzzy logic has been used in research with the participation of nurses. The article search was carried out in the CINAHL, EMBASE, SCOPUS, PubMed and Medline databases, with no limitation on time of publication. Articles written in Portuguese, English and Spanish with themes related to nursing and fuzzy logic with the authorship or participation of nurses were included. The final sample included 21 articles from eight countries. For the purpose of analysis, the articles were distributed into categories: theory, method and model. In nursing, fuzzy logic has significantly contributed to the understanding of subjects related to: imprecision or the need of an expert; as a research method; and in the development of models or decision support systems and hard technologies. The use of fuzzy logic in nursing has shown great potential and represents a vast field for research.Este estudio tuvo como objetivo realizar una revisión integradora investigando como la lógica fuzzy ha sido utilizada en investigaciones con participación de enfermeros. La búsqueda de los artículos fue realizada en las bases de datos CINAHL, Embase, SCOPUS, Medline y PubMed, sin especificar un intervalo de años determinado. Fueron incluidos artículos en los idiomas: portugués, inglés y castellano; con una temática relacionada a la enfermería y a la lógica fuzzy; y con autoría o participación de enfermeros. La muestra final fue de 21 artículos, de ocho países. Para el análisis, los artículos fueron distribuidos en las categorías: teoría, método y modelo. En la enfermería, la lógica fuzzy ha contribuido significativamente para la comprensión de temas relativos a la imprecisión o a la necesidad del especialista, como método de investigación y en el desarrollo de modelos o sistemas de apoyo a la decisión y de tecnologías duras. El uso de la lógica fuzzy en la enfermería ha demostrado gran

  4. Comparison of fuzzy logic and neural network in maximum power point tracker for PV systems

    Energy Technology Data Exchange (ETDEWEB)

    Ben Salah, Chokri; Ouali, Mohamed [Research Unit on Intelligent Control, Optimization, Design and Optimization of Complex Systems (ICOS), Department of Electrical Engineering, National School of Engineers of Sfax, BP. W, 3038, Sfax (Tunisia)

    2011-01-15

    This paper proposes two methods of maximum power point tracking using a fuzzy logic and a neural network controllers for photovoltaic systems. The two maximum power point tracking controllers receive solar radiation and photovoltaic cell temperature as inputs, and estimated the optimum duty cycle corresponding to maximum power as output. The approach is validated on a 100 Wp PVP (two parallels SM50-H panel) connected to a 24 V dc load. The new method gives a good maximum power operation of any photovoltaic array under different conditions such as changing solar radiation and PV cell temperature. From the simulation and experimental results, the fuzzy logic controller can deliver more power than the neural network controller and can give more power than other different methods in literature. (author)

  5. Systematic design of membership functions for fuzzy-logic control: A case study on one-stage partial nitritation/anammox treatment systems.

    Science.gov (United States)

    Boiocchi, Riccardo; Gernaey, Krist V; Sin, Gürkan

    2016-10-01

    A methodology is developed to systematically design the membership functions of fuzzy-logic controllers for multivariable systems. The methodology consists of a systematic derivation of the critical points of the membership functions as a function of predefined control objectives. Several constrained optimization problems corresponding to different qualitative operation states of the system are defined and solved to identify, in a consistent manner, the critical points of the membership functions for the input variables. The consistently identified critical points, together with the linguistic rules, determine the long term reachability of the control objectives by the fuzzy logic controller. The methodology is highlighted using a single-stage side-stream partial nitritation/Anammox reactor as a case study. As a result, a new fuzzy-logic controller for high and stable total nitrogen removal efficiency is designed. Rigorous simulations are carried out to evaluate and benchmark the performance of the controller. The results demonstrate that the novel control strategy is capable of rejecting the long-term influent disturbances, and can achieve a stable and high TN removal efficiency. Additionally, the controller was tested, and showed robustness, against measurement noise levels typical for wastewater sensors. A feedforward-feedback configuration using the present controller would give even better performance. In comparison, a previously developed fuzzy-logic controller using merely expert and intuitive knowledge performed worse. This proved the importance of using a systematic methodology for the derivation of the membership functions for multivariable systems. These results are promising for future applications of the controller in real full-scale plants. Furthermore, the methodology can be used as a tool to help systematically design fuzzy logic control applications for other biological processes. Copyright © 2016 Elsevier Ltd. All rights reserved.

  6. Fuzzy logic control of air-conditioning system in residential buildings

    Directory of Open Access Journals (Sweden)

    Abdel-Hamid Attia

    2015-09-01

    Full Text Available There has been a rising concern in reducing the energy consumption in building. Heating ventilation and air condition system is the biggest consumer of energy in building. In this study, fuzzy logic control of the air conditioning system of building for efficient energy operation and comfortable environment is investigated. A theoretical model of the fan coil unit (FCU and the heat transfer between air and coolant fluid is derived. The controlled variables are the room temperature and relative humidity and control consequents are the percentage of chilled and hot water flow rates at summer and the percentage of hot water and steam injected flow rates at winter. A computer simulation has been conducted and fuzzy control results are compared with that of conventional Proportional-Integral-Derivative control. It was found that the proposed control strategy satisfies the space load and at the same time to achieve the comfort zone, as defined by the ASHRAE code. Meanwhile PID control fails to adjust the room temperature at part-load operations. It has been demonstrated that fuzzy controller operation is more efficient and consumes less energy than PID control.

  7. FUZZY LOGIC BASED INTELLIGENT CONTROL OF A VARIABLE SPEED CAGE MACHINE WIND GENERATION SYSTEM

    Science.gov (United States)

    The paper describes a variable-speed wind generation system where fuzzy logic principles are used to optimize efficiency and enhance performance control. A squirrel cage induction generator feeds the power to a double-sided pulse width modulated converter system which either pump...

  8. Uncovering transcriptional interactions via an adaptive fuzzy logic approach

    Directory of Open Access Journals (Sweden)

    Chen Chung-Ming

    2009-12-01

    Full Text Available Abstract Background To date, only a limited number of transcriptional regulatory interactions have been uncovered. In a pilot study integrating sequence data with microarray data, a position weight matrix (PWM performed poorly in inferring transcriptional interactions (TIs, which represent physical interactions between transcription factors (TF and upstream sequences of target genes. Inferring a TI means that the promoter sequence of a target is inferred to match the consensus sequence motifs of a potential TF, and their interaction type such as AT or RT is also predicted. Thus, a robust PWM (rPWM was developed to search for consensus sequence motifs. In addition to rPWM, one feature extracted from ChIP-chip data was incorporated to identify potential TIs under specific conditions. An interaction type classifier was assembled to predict activation/repression of potential TIs using microarray data. This approach, combining an adaptive (learning fuzzy inference system and an interaction type classifier to predict transcriptional regulatory networks, was named AdaFuzzy. Results AdaFuzzy was applied to predict TIs using real genomics data from Saccharomyces cerevisiae. Following one of the latest advances in predicting TIs, constrained probabilistic sparse matrix factorization (cPSMF, and using 19 transcription factors (TFs, we compared AdaFuzzy to four well-known approaches using over-representation analysis and gene set enrichment analysis. AdaFuzzy outperformed these four algorithms. Furthermore, AdaFuzzy was shown to perform comparably to 'ChIP-experimental method' in inferring TIs identified by two sets of large scale ChIP-chip data, respectively. AdaFuzzy was also able to classify all predicted TIs into one or more of the four promoter architectures. The results coincided with known promoter architectures in yeast and provided insights into transcriptional regulatory mechanisms. Conclusion AdaFuzzy successfully integrates multiple types of

  9. Electric Drive Control with Rotor Resistance and Rotor Speed Observers Based on Fuzzy Logic

    Directory of Open Access Journals (Sweden)

    C. Ben Regaya

    2014-01-01

    Full Text Available Many scientific researchers have proposed the control of the induction motor without speed sensor. These methods have the disadvantage that the variation of the rotor resistance causes an error of estimating the motor speed. Thus, simultaneous estimation of the rotor resistance and the motor speed is required. In this paper, a scheme for estimating simultaneously the rotor resistance and the rotor speed of an induction motor using fuzzy logic has been developed. We present a method which is based on two adaptive observers using fuzzy logic without affecting each other and a simple algorithm in order to facilitate the determination of the optimal values of the controller gains. The control algorithm is proved by the simulation tests. The results analysis shows the characteristic robustness of the two observers of the proposed method even in the case of variation of the rotor resistance.

  10. Implementation Of Automatic Wiper Speed Control And Headlight Modes Control Systems Using Fuzzy Logic

    Directory of Open Access Journals (Sweden)

    ThetKoKo

    2015-07-01

    Full Text Available Abstract This research paper describes the design and simulation of the automatic wiper speed and headlight modes controllers using fuzzy logic. This proposed system consists of a fuzzy logic controller to control a cars wiper speed and headlight modes. The automatic wiper system detects the rain and its intensity. And according to the rain intensity the wiper speed is automatically controlled. Headlight modes automatically changes either from low beam mode to high beam mode or form high beam mode to low beam mode depending on the light intensity from the other vehicle coming from the opposite direction. The system comprises of PIC impedance sensor piezoelectric vibration sensor LDR headlamps and a DC motor to accurate the windshield wiper. Piezoelectric sensor is used to detect the rain intensity which is based on the piezoelectric effect. MATLAB software is used to achieve the designed goal.

  11. Dual mode linguistic hedge fuzzy logic controller for an isolated wind-diesel hybrid power system with superconducting magnetic energy storage unit

    International Nuclear Information System (INIS)

    Thameem Ansari, M.Md.; Velusami, S.

    2010-01-01

    A design of dual mode linguistic hedge fuzzy logic controller for an isolated wind-diesel hybrid power system with superconducting magnetic energy storage unit is proposed in this paper. The design methodology of dual mode linguistic hedge fuzzy logic controller is a hybrid model based on the concepts of linguistic hedges and hybrid genetic algorithm-simulated annealing algorithms. The linguistic hedge operators are used to adjust the shape of the system membership functions dynamically and can speed up the control result to fit the system demand. The hybrid genetic algorithm-simulated annealing algorithm is adopted to search the optimal linguistic hedge combination in the linguistic hedge module. Dual mode concept is also incorporated in the proposed controller because it can improve the system performance. The system with the proposed controller was simulated and the frequency deviation resulting from a step load disturbance is presented. The comparison of the proportional plus integral controller, fuzzy logic controller and the proposed dual mode linguistic hedge fuzzy logic controller shows that, with the application of the proposed controller, the system performance is improved significantly. The proposed controller is also found to be less sensitive to the changes in the parameters of the system and also robust under different operating modes of the hybrid power system.

  12. Some uses and limitations of Fuzzy Logic in artificial intelligence reasoning for reactor control

    International Nuclear Information System (INIS)

    Guth, M.A.S.

    1989-01-01

    This paper describes some potential uses for Fuzzy Logic as well as its limitations based on experience designing a small prototype expert system that can be used in a computer laboratory to study a government research reactor. The expert system designed in this study diagnoses problems in the interface between the heat exchanger and the core. Engineers who had first-hand experience with the High Flux Isotope Reactor (HFIR) at Oak Ridge National Laboratory suggested logical relations incorporated in the knowledge base. The expert system has a production rule backward-chaining-based architecture, and the knowledge base incorporates four kinds of information. First, the structural relationship between causes and consequences are given by nuclear engineering experts. Second, numerical values for the initiating events can be taken from observed performance of the HFIR during normal conditions. Third, the causes of particular events are ordinally ranked by their expected chance of occuring based on a combination of knowledge about the reactor design and actual experiences with the reactor in operation. Fourth, Bellman-Zadeh Fuzzy Logic is introduced to maintain truth values for expert system parameter values that can be true with some degree of certainty. (orig.)

  13. Variable structure TITO fuzzy-logic controller implementation for a solar air-conditioning system

    Energy Technology Data Exchange (ETDEWEB)

    Lygouras, J.N.; Pachidis, Th. [Laboratory of Electronics, School of Electrical and Computer Engineering, Democritus University of Thrace, GR-67100 Xanthi (Greece); Kodogiannis, V.S. [Centre for Systems Analysis, School of Computer Science, University of Westminster, London HA1 3TP (United Kingdom); Tarchanidis, K.N. [Department of Petroleum Technology, Technological Education Institute of Kavala, GR-65404, Kavala (Greece); Koukourlis, C.S. [Laboratory of Telecommunications, School of Electrical and Computer Engineering, Democritus University of Thrace, GR-67100 Xanthi (Greece)

    2008-04-15

    The design and implementation of a Two-Input/Two-Output (TITO) variable structure fuzzy-logic controller for a solar-powered air-conditioning system is described in this paper. Two DC motors are used to drive the generator pump and the feed pump of the solar air-conditioner. The first affects the temperature in the generator of the solar air-conditioner, while the second, the pressure in the power loop. The difficulty of Multi-Input/Multi-Output (MIMO) systems control is how to overcome the coupling effects among each degree of freedom. First, a traditional fuzzy-controller has been designed, its output being one of the components of the control signal for each DC motor driver. Secondly, according to the characteristics of the system's dynamics coupling, an appropriate coupling fuzzy-controller (CFC) is incorporated into a traditional fuzzy-controller (TFC) to compensate for the dynamic coupling among each degree of freedom. This control strategy simplifies the implementation problem of fuzzy control, but can also improve the control performance. This mixed fuzzy controller (MFC) can effectively improve the coupling effects of the systems, and this control strategy is easy to design and implement. Experimental results from the implemented system are presented. (author)

  14. Make or buy decision considering uncertainty based on fuzzy logic using simulation and multiple criteria decision making

    Directory of Open Access Journals (Sweden)

    Ali Mohtashami

    2013-01-01

    Full Text Available Decision making on making/buying problem has always been a challenge to decision makers. In this paper a methodology has been proposed to resolve this challenge. This methodology is capable of evaluating making/buying decision making under uncertainty. For uncertainty, the fuzzy logic and simulation approaches have been used. The proposed methodology can be applied to parts with multi stage manufacturing processes and different suppliers. Therefore this methodology provides a scale for decision making from full outsourcing to full manufacturing and with selecting appropriate supplier.

  15. Self-tuning fuzzy logic nuclear reactor controller[Proceedings of the 2nd International FLINS Workshop (Mol, Belgium, September 25-27, 1996)

    Energy Technology Data Exchange (ETDEWEB)

    Sharif Heger, A; Alang-Rashid, N K

    1996-07-01

    We present a method for self-tuning of fuzzy logic controllers based on the estimation of the optimum value of the centroids of its output fuzzy set. The method can be implemented on-line and does not require modification of membership functions and control rules. The main features of this method are: the rules are left intact to retain the operator's expertise in the FLC rule base, and the parameters that require any adjustment are identifiable in advance and their number is kept at a minimum. Therefore, the use of this method preserves the control statements in the original form. Results of simulation and actual tests show that this tuning method improves the performance of fuzzy logic controllers in following the desired reactor power level trajectories. In addition, this method demonstrates a similar improvement for power up and power down experiments, based on both simulation and actual case studies. For these experiments, the control rules for the fuzzy logic controller were derived from control statements that expressed the relationships between error, rate of error change, and duration of direction of control rod movements.

  16. Kontrol Kecepatan Robot Hexapod Pemadam Api menggunakan Metoda Logika Fuzzy

    Directory of Open Access Journals (Sweden)

    Darwison

    2015-09-01

    Full Text Available This study aims to create a hexapod robot speed control fire extinguisher using fuzzy logic method . By applying the method of fuzzy logic will make the robot move smoother and comparable to the distance . The input of the fuzzy logic method is obtained from three ultrasonic sensors as detection distance to the wall / barrier . Hexapod robot using a servomotor with torgue large enough to perform the movement . Robot speed will be faster if the purpose of the movement of the robot is still far from the wall / barrier and vice versa . Microcontroller with fuzzy logic -based program of its use as a controller movement . The results showed that more refined movement based on the distance read by the sensor , where the sensor is experiencing an error distance measurement is influenced by the material wall / barrier . For the wall material / to obstacle of the board experienced a reading error of 0.18 % , amounting to 0.5 % of books and dolls of 1.58 %.

  17. Obstacle avoidance for kinematically redundant robots using an adaptive fuzzy logic algorithm

    International Nuclear Information System (INIS)

    Beheshti, M.T.H.; Tehrani, A.K.

    1999-05-01

    In this paper the Adaptive Fuzzy Logic approach for solving the inverse kinematics of redundant robots in an environment with obstacles is presented. The obstacles are modeled as convex bodies. A fuzzy rule base that is updated via an adaptive law is used to solve the inverse kinematic problem. Additional rules have been introduced to take care of the obstacles avoidance problem. The proposed method has advantages such as high accuracy, simplicity of computations and generality for all redundant robots. Simulation results illustrate much better tracking performance than the dynamic base solution for a given trajectory in cartesian space, while guaranteeing a collision-free trajectory and observation of a mechanical joint limit

  18. Human reliability analysis data obtainment through fuzzy logic in nuclear plants

    International Nuclear Information System (INIS)

    Nascimento, C.S. do; Mesquita, R.N. de

    2012-01-01

    Highlights: ► Human Error Probability estimates from operator's reactions to emergency situations. ► Human Reliability Analysis input data obtainment through fuzzy logic inference. ► Performance Shaping Factors evaluation influence level onto the operator's actions. - Abstract: Human error has been recognized as an important factor for many industrial and nuclear accidents occurrence. Human error data is scarcely available for different reasons among which, lapses in historical database registry methodology is an important one. Human Reliability Analysis (HRA) is an usual tool employed to estimate the probability that an operator will reasonably perform a system required task in required time without degrading the system. This meta-analysis requires specific Human Error Probability estimates for most of its procedure. This work obtains Human Error Probability (HEP) estimates from operator's actions in response to emergency situations hypothesis on Research Reactor IEA-R1 from IPEN, Brazil. Through this proposed methodology HRA should be able to be performed even with shortage of related human error statistical data. A Performance Shaping Factors (PSF's) evaluation in order to classify and estimate their influence level onto the operator's actions and to determine their actual state over the plant was also done. Both HEP estimation and PSF evaluation were done based on expert judgment using interviews and questionnaires. Expert group was established based on selected IEA-R1 operators, and their evaluation were put into a knowledge representation system which used linguistic variables and group evaluation values that were obtained through Fuzzy Logic and Fuzzy Set theory. HEP obtained values show good agreement with literature published data corroborating the proposed methodology as a good alternative to be used on HRA.

  19. Development of an object-oriented software based on fuzzy-logic for controlling temperatures in PAC experiments

    Energy Technology Data Exchange (ETDEWEB)

    Lapolli, Andre L.; Yamagishi, Sueli; Domienikan, Claudio; Schoueri, Roberto M.; Carbonari, Artur W.; Saxena, Rajendra N., E-mail: alapolli@ipen.b [Instituto de Pesquisas Energeticas e Nucleares (IPEN/CNEN-SP), Sao Paulo, SP (Brazil)

    2009-07-01

    The Hyperfine Interaction Laboratory at Instituto de Pesquisas Energeticas e Nucleares (IPEN) has been using Perturbed Angular Correlation (PAC) technique for studying material science for more than 20 years. One of the important aspects of the research involves the study of the behavior of measured properties of samples as a function of temperature. For temperatures higher than room temperature a small resistance furnace is used to heat the sample. The need to carry out the PAC measurement at predefined temperatures steps in a programmed manner is obvious. The present work describes a procedure for the furnace temperature control and automatic data acquisition at different temperatures based on fuzzy logic. The procedure consists in determining the linguistic input (temp, DELTAtemp) and output (pow) variables and their pertinence functions. After defining the variables, an object.oriented program is written in Java language which is an interface between principal data acquisition program and electronic temperature controller of the mini furnace. In addition to the implementation of the class that involves the fuzzy logic and classes with strategic algorithms defined for each temperature range there are classes of communication between systems based on modbus protocol RTU (Remote Terminal Unit) connected to serial interface RS-488. In this manner the applied technology for the development of software permits higher software life requiring only small alterations or implementation of classes in the use with new equipment. (author)

  20. Optimisation of Refrigeration System with Two-Stage and Intercooler Using Fuzzy Logic and Genetic Algorithm

    Directory of Open Access Journals (Sweden)

    Bayram Kılıç

    2017-04-01

    Full Text Available Two-stage compression operation prevents excessive compressor outlet pressure and temperature and this operation provides more efficient working condition in low-temperature refrigeration applications. Vapor compression refrigeration system with two-stage and intercooler is very good solution for low-temperature refrigeration applications. In this study, refrigeration system with two-stage and intercooler were optimized using fuzzy logic and genetic algorithm. The necessary thermodynamic characteristics for optimization were estimated with Fuzzy Logic and liquid phase enthalpy, vapour phase enthalpy, liquid phase entropy, vapour phase entropy values were compared with actual values. As a result, optimum working condition of system was estimated by the Genetic Algorithm as -6.0449 oC for evaporator temperature, 25.0115 oC for condenser temperature and 5.9666 for COP. Morever, irreversibility values of the refrigeration system are calculated.

  1. Landslide susceptibility mapping by comparing weight of evidence, fuzzy logic, and frequency ratio methods

    Directory of Open Access Journals (Sweden)

    V. Vakhshoori

    2016-09-01

    Full Text Available A regional scale basin susceptible to landslide located in Qaemshahr area in northern Iran was chosen for comparing the reliability of weight of evidence (WofE, fuzzy logic, and frequency ratio (FR methods for landslide susceptibility mapping. The locations of 157 landslides were identified using Google Earth® or extracted from archived data, from which, 22 rockslides were eliminated from the data-set due to their different conditions. The 135 remaining landslides were randomly divided into two groups of modelling (70% and validation (30% data-sets. Elevation, slope degree, slope aspect, lithology, land use/cover, normalized difference vegetation index, rainfall, distance to drainage network, roads, and faults were considered as landslide causative factors. The landslide susceptibility maps were prepared using the three mentioned methods. The validation process was measured by the success and prediction rates calculated by area under receiver operating characteristic curve. The ‘OR’, ‘AND’, ‘SUM’, and ‘PRODUCT’ operators of the fuzzy logic method were unacceptable because these operators classify the target area into either very high or very low susceptible zones that are inconsistent with the physical conditions of the study area. The results of fuzzy ‘GAMMA’ operators were relatively reliable while, FR and WofE methods showed results that are more reliable.

  2. Fuzzy logic and information fusion to commemorate the 70th birthday of Professor Gaspar Mayor

    CERN Document Server

    Sastre, Joan

    2016-01-01

    This book offers a timely report on key theories and applications of soft-computing. Written in honour of Professor Gaspar Mayor on his 70th birthday, it primarily focuses on areas related to his research, including fuzzy binary operators, aggregation functions, multi-distances, and fuzzy consensus/decision models. It also discusses a number of interesting applications such as the implementation of fuzzy mathematical morphology based on Mayor-Torrens t-norms. Importantly, the different chapters, authored by leading experts, present novel results and offer new perspectives on different aspects of Mayor’s research. The book also includes an overview of evolutionary fuzzy systems, a topic that is not one of Mayor’s main areas of interest, and a final chapter written by the Spanish pioneer in fuzzy logic, Professor E. Trillas. Computer and decision scientists, knowledge engineers and mathematicians alike will find here an authoritative overview of key soft-computing concepts and techniques.

  3. Data Dissemination Based on Fuzzy Logic and Network Coding in Vehicular Networks

    Directory of Open Access Journals (Sweden)

    Xiaolan Tang

    2017-01-01

    Full Text Available Vehicular networks, as a significant technology in intelligent transportation systems, improve the convenience, efficiency, and safety of driving in smart cities. However, because of the high velocity, the frequent topology change, and the limited bandwidth, it is difficult to efficiently propagate data in vehicular networks. This paper proposes a data dissemination scheme based on fuzzy logic and network coding for vehicular networks, named SFN. It uses fuzzy logic to compute a transmission ability for each vehicle by comprehensively considering the effects of three factors: the velocity change rate, the velocity optimization degree, and the channel quality. Then, two nodes with high abilities are selected as primary backbone and slave backbone in every road segment, which propagate data to other vehicles in this segment and forward them to the backbones in the next segment. The backbone network helps to increase the delivery ratio and avoid invalid transmissions. Additionally, network coding is utilized to reduce transmission overhead and accelerate data retransmission in interbackbone forwarding and intrasegment broadcasting. Experiments show that, compared with existing schemes, SFN has a high delivery ratio and a short dissemination delay, while the backbone network keeps high reliability.

  4. Supervisory System and Multivariable Control Applying Weighted Fuzzy-PID Logic in an Alcoholic Fermentation Process

    Directory of Open Access Journals (Sweden)

    Márcio Mendonça

    2015-10-01

    Full Text Available In this work, it is analyzed a multivariate system control of an alcoholic fermentation process with no minimum phase. The control is made with PID classic controllers associated with a supervisory system based on Fuzzy Systems. The Fuzzy system, a priori, send set-points to PID controllers, but also adds protection functions, such as if the biomass valued is at zero or very close. The Fuzzy controller changes the campaign to prevent or mitigate the paralyzation of the process. Three control architectures based on Fuzzy Control Systems are presented and compared in performance with classic control in different campaigns. The third architecture, in particular, adds an adaptive function. A brief summary of Fuzzy theory and correlated works will be presented. And, finally simulations results, conclusions and future works end the article.

  5. Automatic control with fuzzy logic of home-made beer production in maceration and cooking stages

    Directory of Open Access Journals (Sweden)

    Mariano Luján Corro

    2010-06-01

    Full Text Available The process of home-made beer production in the malt maceration and cooking stages was controlled automatically with fuzzy logic, across different performers considering the time and temperature of the process, using 2009LabVIEW. The equipment was mainly composed of three 20 L capacity stainless steel containers (water supply, maceration and cooking, an additional hops container, a data acquisition card (PIC 16F877a micro controller, three LM35 temperature sensors and 11 on/off type performers, which were governed by a total of 47 Mandani type fuzzy rules with trapezoidal membership functions, using the method of center area for the defuzzification. The performers: electrovalves (5, pumps (2, heaters (3 and a stirrer, in approximately 4 hours, were adequately controlled in their early maceration and cooking stages. The beer obtained by automatic control with fuzzy logic in the maceration and cooking stages, had the following characteristics: 0.98 g/cm3 of density, 3.9 of pH, total acidity expressed as 0.87% of lactic acid, 6.2ºGL of alcoholic degree and 0.91% w/v of CO2 percentage.

  6. Flood Hazard Mapping by Applying Fuzzy TOPSIS Method

    Science.gov (United States)

    Han, K. Y.; Lee, J. Y.; Keum, H.; Kim, B. J.; Kim, T. H.

    2017-12-01

    There are lots of technical methods to integrate various factors for flood hazard mapping. The purpose of this study is to suggest the methodology of integrated flood hazard mapping using MCDM(Multi Criteria Decision Making). MCDM problems involve a set of alternatives that are evaluated on the basis of conflicting and incommensurate criteria. In this study, to apply MCDM to assessing flood risk, maximum flood depth, maximum velocity, and maximum travel time are considered as criterion, and each applied elements are considered as alternatives. The scheme to find the efficient alternative closest to a ideal value is appropriate way to assess flood risk of a lot of element units(alternatives) based on various flood indices. Therefore, TOPSIS which is most commonly used MCDM scheme is adopted to create flood hazard map. The indices for flood hazard mapping(maximum flood depth, maximum velocity, and maximum travel time) have uncertainty concerning simulation results due to various values according to flood scenario and topographical condition. These kind of ambiguity of indices can cause uncertainty of flood hazard map. To consider ambiguity and uncertainty of criterion, fuzzy logic is introduced which is able to handle ambiguous expression. In this paper, we made Flood Hazard Map according to levee breach overflow using the Fuzzy TOPSIS Technique. We confirmed the areas where the highest grade of hazard was recorded through the drawn-up integrated flood hazard map, and then produced flood hazard map can be compared them with those indicated in the existing flood risk maps. Also, we expect that if we can apply the flood hazard map methodology suggested in this paper even to manufacturing the current flood risk maps, we will be able to make a new flood hazard map to even consider the priorities for hazard areas, including more varied and important information than ever before. Keywords : Flood hazard map; levee break analysis; 2D analysis; MCDM; Fuzzy TOPSIS

  7. Temperature prediction in a coal fired boiler with a fixed bed by fuzzy logic based on numerical solution

    International Nuclear Information System (INIS)

    Biyikoglu, A.; Akcayol, M.A.; Oezdemir, V.; Sivrioglu, M.

    2005-01-01

    In this study, steady state combustion in boilers with a fixed bed has been investigated. Temperature distributions in the combustion chamber of a coal fired boiler with a fixed bed are predicted using fuzzy logic based on data obtained from the numerical solution method for various coal and air feeding rates. The numerical solution method and the discretization of the governing equations of two dimensional turbulent flow in the combustion chamber and one dimensional coal combustion in the fixed bed are explained. Control Volume and Finite Difference Methods are used in the discretization of the equations in the combustion chamber and in the fixed bed, respectively. Results are presented as contours within the solution domain and compared with numerical ones. Comparison of the results shows that the difference between the numerical solution and fuzzy logic prediction throughout the computational domain is less than 1.5%. The statistical coefficient of multiple determinations for the investigated cases is about 0.9993 to 0.9998. This accuracy degree is acceptable in predicting the temperature values. So, it can be concluded that fuzzy logic provides a feasible method for defining the system properties

  8. Fuzzy Logic Based Behavior Fusion for Navigation of an Intelligent Mobile Robot

    Institute of Scientific and Technical Information of China (English)

    李伟; 陈祖舜; 等

    1996-01-01

    This paper presents a new method for behavior fusion control of a mobile robot in uncertain environments.Using behavior fusion by fuzzy logic,a mobile robot is able to directly execute its motion according to range information about environments,acquired by ultrasonic sensors,without the need for trajectory planning.Based on low-level behavior control,an efficient strategy for integrating high-level global planning for robot motion can be formulated,since,in most applications,some information on environments is prior knowledge.A global planner,therefore,only to generate some subgoal positions rather than exact geometric paths.Because such subgoals can be easily removed from or added into the plannes,this strategy reduces computational time for global planning and is flexible for replanning in dynamic environments.Simulation results demonstrate that the proposed strategy can be applied to robot motion in complex and dynamic environments.

  9. Single axis control of ball position in magnetic levitation system using fuzzy logic control

    Science.gov (United States)

    Sahoo, Narayan; Tripathy, Ashis; Sharma, Priyaranjan

    2018-03-01

    This paper presents the design and real time implementation of Fuzzy logic control(FLC) for the control of the position of a ferromagnetic ball by manipulating the current flowing in an electromagnet that changes the magnetic field acting on the ball. This system is highly nonlinear and open loop unstable. Many un-measurable disturbances are also acting on the system, making the control of it highly complex but interesting for any researcher in control system domain. First the system is modelled using the fundamental laws, which gives a nonlinear equation. The nonlinear model is then linearized at an operating point. Fuzzy logic controller is designed after studying the system in closed loop under PID control action. The controller is then implemented in real time using Simulink real time environment. The controller is tuned manually to get a stable and robust performance. The set point tracking performance of FLC and PID controllers were compared and analyzed.

  10. On the logos a naïve view on ordinary reasoning and fuzzy logic

    CERN Document Server

    Trillas, Enric

    2017-01-01

    This book offers an inspiring and naïve view on language and reasoning. It presents a new approach to ordinary reasoning that follows the author’s former work on fuzzy logic. Starting from a pragmatic scientific view on meaning as a quantity, and the common sense reasoning from a primitive notion of inference, which is shared by both laypeople and experts, the book shows how this can evolve, through the addition of more and more suppositions, into various formal and specialized modes of precise, imprecise, and approximate reasoning. The logos are intended here as a synonym for rationality, which is usually shown by the processes of questioning, guessing, telling, and computing. Written in a discursive style and without too many technicalities, the book presents a number of reflections on the study of reasoning, together with a new perspective on fuzzy logic and Zadeh’s “computing with words” grounded in both language and reasoning. It also highlights some mathematical developments supporting this vie...

  11. Design of fuzzy learning control systems for steam generator water level control

    International Nuclear Information System (INIS)

    Park, Gee Yong

    1996-02-01

    descent learning algorithm can provide the stable learning and fast learning speed. For more fast learning speed, the modified momentum is applied to the learning scheme. Fuzzy logic controller with learning algorithm described above is applied to water level control of nuclear steam generator through two learning patterns; one is the off-line learning and the other the on-line learning. Fuzzy logic controller trained off-line is useful in the situation that the controller designer is over-burdened with the tuning works for the fuzzy controller structure and the recorded data from plant operation is rich. In the off-line learning, the desired data is required from the control actions of the plant operator or other controllers such as PI controller. The gradient descent learning algorithm extracts the useful rules among total 343 rules which are generated from the relational product of three controller inputs (7x7x7) and tunes membership functions for controller input domain. In practice, it is almost impossible to tune 343 rules constructed in three input dimensions by trial-and-error method of a human designer. The fuzzy logic controller trained off-line shows the good general mapping capability of controller's input-output relationships and also shows excellent robustness to sudden, large load disturbances. Fuzzy logic controller with on-line learning algorithm, which is called Self-Organizing Fuzzy Logic Controller, constructs the controller structure with no control rules at initial in such a way that it creates control rules and tunes controller input membership functions based on the performance criterion as control action goes on and modifies its control structure when uncertain disturbance is suspected during plant operation. Selected tuning parameters of fuzzy logic controller are updated on-line in the learning algorithm. This control algorithm is divided into two types based on the two performance criteria, i.e., performance index table and performance cost

  12. Application of multi response optimization with grey relational analysis and fuzzy logic method

    Science.gov (United States)

    Winarni, Sri; Wahyu Indratno, Sapto

    2018-01-01

    Multi-response optimization is an optimization process by considering multiple responses simultaneously. The purpose of this research is to get the optimum point on multi-response optimization process using grey relational analysis and fuzzy logic method. The optimum point is determined from the Fuzzy-GRG (Grey Relational Grade) variable which is the conversion of the Signal to Noise Ratio of the responses involved. The case study used in this research are case optimization of electrical process parameters in electrical disharge machining. It was found that the combination of treatments resulting to optimum MRR and SR was a 70 V gap voltage factor, peak current 9 A and duty factor 0.8.

  13. DEVELOPMENT OF A PEDESTRIAN INDOOR NAVIGATION SYSTEM BASED ON MULTI-SENSOR FUSION AND FUZZY LOGIC ESTIMATION ALGORITHMS

    Directory of Open Access Journals (Sweden)

    Y. C. Lai

    2015-05-01

    Full Text Available This paper presents a pedestrian indoor navigation system based on the multi-sensor fusion and fuzzy logic estimation algorithms. The proposed navigation system is a self-contained dead reckoning navigation that means no other outside signal is demanded. In order to achieve the self-contained capability, a portable and wearable inertial measure unit (IMU has been developed. Its adopted sensors are the low-cost inertial sensors, accelerometer and gyroscope, based on the micro electro-mechanical system (MEMS. There are two types of the IMU modules, handheld and waist-mounted. The low-cost MEMS sensors suffer from various errors due to the results of manufacturing imperfections and other effects. Therefore, a sensor calibration procedure based on the scalar calibration and the least squares methods has been induced in this study to improve the accuracy of the inertial sensors. With the calibrated data acquired from the inertial sensors, the step length and strength of the pedestrian are estimated by multi-sensor fusion and fuzzy logic estimation algorithms. The developed multi-sensor fusion algorithm provides the amount of the walking steps and the strength of each steps in real-time. Consequently, the estimated walking amount and strength per step are taken into the proposed fuzzy logic estimation algorithm to estimates the step lengths of the user. Since the walking length and direction are both the required information of the dead reckoning navigation, the walking direction is calculated by integrating the angular rate acquired by the gyroscope of the developed IMU module. Both the walking length and direction are calculated on the IMU module and transmit to a smartphone with Bluetooth to perform the dead reckoning navigation which is run on a self-developed APP. Due to the error accumulating of dead reckoning navigation, a particle filter and a pre-loaded map of indoor environment have been applied to the APP of the proposed navigation system

  14. Development of a Pedestrian Indoor Navigation System Based on Multi-Sensor Fusion and Fuzzy Logic Estimation Algorithms

    Science.gov (United States)

    Lai, Y. C.; Chang, C. C.; Tsai, C. M.; Lin, S. Y.; Huang, S. C.

    2015-05-01

    This paper presents a pedestrian indoor navigation system based on the multi-sensor fusion and fuzzy logic estimation algorithms. The proposed navigation system is a self-contained dead reckoning navigation that means no other outside signal is demanded. In order to achieve the self-contained capability, a portable and wearable inertial measure unit (IMU) has been developed. Its adopted sensors are the low-cost inertial sensors, accelerometer and gyroscope, based on the micro electro-mechanical system (MEMS). There are two types of the IMU modules, handheld and waist-mounted. The low-cost MEMS sensors suffer from various errors due to the results of manufacturing imperfections and other effects. Therefore, a sensor calibration procedure based on the scalar calibration and the least squares methods has been induced in this study to improve the accuracy of the inertial sensors. With the calibrated data acquired from the inertial sensors, the step length and strength of the pedestrian are estimated by multi-sensor fusion and fuzzy logic estimation algorithms. The developed multi-sensor fusion algorithm provides the amount of the walking steps and the strength of each steps in real-time. Consequently, the estimated walking amount and strength per step are taken into the proposed fuzzy logic estimation algorithm to estimates the step lengths of the user. Since the walking length and direction are both the required information of the dead reckoning navigation, the walking direction is calculated by integrating the angular rate acquired by the gyroscope of the developed IMU module. Both the walking length and direction are calculated on the IMU module and transmit to a smartphone with Bluetooth to perform the dead reckoning navigation which is run on a self-developed APP. Due to the error accumulating of dead reckoning navigation, a particle filter and a pre-loaded map of indoor environment have been applied to the APP of the proposed navigation system to extend its

  15. A hybrid neural networks-fuzzy logic-genetic algorithm for grade estimation

    Science.gov (United States)

    Tahmasebi, Pejman; Hezarkhani, Ardeshir

    2012-05-01

    The grade estimation is a quite important and money/time-consuming stage in a mine project, which is considered as a challenge for the geologists and mining engineers due to the structural complexities in mineral ore deposits. To overcome this problem, several artificial intelligence techniques such as Artificial Neural Networks (ANN) and Fuzzy Logic (FL) have recently been employed with various architectures and properties. However, due to the constraints of both methods, they yield the desired results only under the specific circumstances. As an example, one major problem in FL is the difficulty of constructing the membership functions (MFs).Other problems such as architecture and local minima could also be located in ANN designing. Therefore, a new methodology is presented in this paper for grade estimation. This method which is based on ANN and FL is called "Coactive Neuro-Fuzzy Inference System" (CANFIS) which combines two approaches, ANN and FL. The combination of these two artificial intelligence approaches is achieved via the verbal and numerical power of intelligent systems. To improve the performance of this system, a Genetic Algorithm (GA) - as a well-known technique to solve the complex optimization problems - is also employed to optimize the network parameters including learning rate, momentum of the network and the number of MFs for each input. A comparison of these techniques (ANN, Adaptive Neuro-Fuzzy Inference System or ANFIS) with this new method (CANFIS-GA) is also carried out through a case study in Sungun copper deposit, located in East-Azerbaijan, Iran. The results show that CANFIS-GA could be a faster and more accurate alternative to the existing time-consuming methodologies for ore grade estimation and that is, therefore, suggested to be applied for grade estimation in similar problems.

  16. Deteksi Kebocoran Gas LPG Menggunakan Detektor Arduino dengan Algoritma Fuzzy Logic Mandani

    OpenAIRE

    Hakim, Lukman; Yonatan, Vidi

    2017-01-01

    Bencana kebakaran yang diakibatkan oleh kebocoran gas LPG (Liquid  Petroleum   Gas) mengalami kenaikan setiap tahun dari tahun 2011 sampai 2015 diantaranya 17% diakibatkan oleh kebocoran gas. Penggunaan detektor kebocoran gas LPG menggunakan arduino yang dilengkapi sensor gas dan suhu memberikan kemudahan untuk deteksi secara awal terjadinya kebocoran dan kebakaran. Perancangan detektor kebocoran gas LPG menggunakan algoritma fuzzy logic mandani, dilengkapi dengan informasi mel...

  17. using fuzzy logic in image processing

    International Nuclear Information System (INIS)

    Ashabrawy, M.A.F.

    2002-01-01

    due to the unavoidable merge between computer and mathematics, the signal processing in general and the processing in particular have greatly improved and advanced. signal processing deals with the processing of any signal data for use by a computer, while image processing deals with all kinds of images (just images). image processing involves the manipulation of image data for better appearance and viewing by people; consequently, it is a rapidly growing and exciting field to be involved in today . this work takes an applications - oriented approach to image processing .the applications; the maps and documents of the first egyptian research reactor (ETRR-1), the x-ray medical images and the fingerprints image. since filters, generally, work continuous ranges rather than discrete values, fuzzy logic techniques are more convenient.thee techniques are powerful in image processing and can deal with one- dimensional, 1-D and two - dimensional images, 2-D images as well

  18. Fuzzy logic prioritization of failures in a system failure mode, effects and criticality analysis

    International Nuclear Information System (INIS)

    Bowles, John B.; Pelaez, C.E.

    1995-01-01

    This paper describes a new technique, based on fuzzy logic, for prioritizing failures for corrective actions in a Failure Mode, Effects and Criticality Analysis (FMECA). As in a traditional criticality analysis, the assessment is based on the severity, frequency of occurrence, and detectability of an item failure. However, these parameters are here represented as members of a fuzzy set, combined by matching them against rules in a rule base, evaluated with min-max inferencing, and then defuzzified to assess the riskiness of the failure. This approach resolves some of the problems in traditional methods of evaluation and it has several advantages compared to strictly numerical methods: 1) it allows the analyst to evaluate the risk associated with item failure modes directly using the linguistic terms that are employed in making the criticality assessment; 2) ambiguous, qualitative, or imprecise information, as well as quantitative data, can be used in the assessment and they are handled in a consistent manner; and 3) it gives a more flexible structure for combining the severity, occurrence, and detectability parameters. Two fuzzy logic based approaches for assessing criticality are presented. The first is based on the numerical rankings used in a conventional Risk Priority Number (RPN) calculation and uses crisp inputs gathered from the user or extracted from a reliability analysis. The second, which can be used early in the design process when less detailed information is available, allows fuzzy inputs and also illustrates the direct use of the linguistic rankings defined for the RPN calculations

  19. Fuzzy pharmacology: theory and applications.

    Science.gov (United States)

    Sproule, Beth A; Naranjo, Claudio A; Türksen, I Burhan

    2002-09-01

    Fuzzy pharmacology is a term coined to represent the application of fuzzy logic and fuzzy set theory to pharmacological problems. Fuzzy logic is the science of reasoning, thinking and inference that recognizes and uses the real world phenomenon that everything is a matter of degree. It is an extension of binary logic that is able to deal with complex systems because it does not require crisp definitions and distinctions for the system components. In pharmacology, fuzzy modeling has been used for the mechanical control of drug delivery in surgical settings, and work has begun evaluating its use in other pharmacokinetic and pharmacodynamic applications. Fuzzy pharmacology is an emerging field that, based on these initial explorations, warrants further investigation.

  20. A novel GUI modeled fuzzy logic controller for a solar powered energy utilization scheme

    International Nuclear Information System (INIS)

    Altas, I. H.; Sharaf, A. M.

    2007-01-01

    Photovoltaic PVA-solar powered electrical systems comprise different components and subsystems to be controlled separately. Since the generated solar power is dependant on uncontrollable environmental conditions, it requires extra caution to design controllers that handle unpredictable events and maintain efficient load matching power. In this study, a photovoltaic (PV) solar array model is developed for Matlab/Simulink GUI environment and controlled using a fuzzy logic controller (FLC), which is also developed for GUI environment. The FLC is also used to control the DC load bus voltage at constant value as well as controlling the speed of a PMDC motor as one of the loads being fed. The FLC controller designed using the Matlab/Simuling GUI environment has flexible design criteria's so that it can easily be modified and extended for controlling different systems. The proposed FLC is used in three different parts of the PVA stand alone utilization scheme here. One of these parts is the speed control of the PMDC load, one of the other parts is controlling the DC load bus voltage, and the third part is the maximum power point (MPPT) tracking control, which is used to operate the PVA at its available maximum power as the solar insolation and ambient temperature change. This paper presents a study of a standalone Photovoltaic energy utilization system feeding a DC and AC hybrid electric load and is fully controlled by a novel and simple on-line fuzzy logic based dynamic search, detection and tracking controller that ensures maximum power point operation under excursions in Solar Insolation, Ambient temperature and electric load variations. The maximum power point MPP-Search and Detection algorithm is fully dynamic in nature and operates without any required direct measurement or forecasted PV array information about the irradiation and temperature. An added Search sensitivity measure is defined and also used in the MPP search algorithm to sense and dynamic response for

  1. Fuzzy logic control for improved pressurizer systems in nuclear power plants

    International Nuclear Information System (INIS)

    Brown, Chris; Gabbar, Hossam A.

    2014-01-01

    Highlights: • Improved performance of the pressurizer system in a CANDU nuclear power plant (NPP). • Inventory control for the pressurizer system in NPP. • Compare fuzzy logic with PID in pressurizer system in NPP. • Develop a fuzzy controller to regulate the pressurizer inventory control. • Compare control performance with current proportional controller used at NPP. - Abstract: The pressurizer system in a CANDU nuclear power plant is responsible for maintaining the pressure of the primary heat transport system to ensure the plant is operated within its safe operating envelope. The inventory control for the pressurizer system use a combination of level sensors, feed valves and bleed valves to ensure that there is adequate room in the pressurizer to accommodate any swell or shrinkage in the PHT system. The Darlington Nuclear Generating Station (DNGS) in Ontario, Canada currently uses a proportional controller for the bleed and feed valves to regulate the pressurizer inventory control which can result in large coolant level overshoot along with excessive settling times. The purpose of this paper is to develop a fuzzy controller to regulate the pressurizer inventory control and compare its performance to the current proportional controller used at DNGS. The simulation of the pressurizer inventory control system shows the fuzzy controller performs better than the proportional controller in terms of settling time and overshoot

  2. The stock-flow model of spatial data infrastructure development refined by fuzzy logic.

    Science.gov (United States)

    Abdolmajidi, Ehsan; Harrie, Lars; Mansourian, Ali

    2016-01-01

    The system dynamics technique has been demonstrated to be a proper method by which to model and simulate the development of spatial data infrastructures (SDI). An SDI is a collaborative effort to manage and share spatial data at different political and administrative levels. It is comprised of various dynamically interacting quantitative and qualitative (linguistic) variables. To incorporate linguistic variables and their joint effects in an SDI-development model more effectively, we suggest employing fuzzy logic. Not all fuzzy models are able to model the dynamic behavior of SDIs properly. Therefore, this paper aims to investigate different fuzzy models and their suitability for modeling SDIs. To that end, two inference and two defuzzification methods were used for the fuzzification of the joint effect of two variables in an existing SDI model. The results show that the Average-Average inference and Center of Area defuzzification can better model the dynamics of SDI development.

  3. Fuzzy Logic Based Anomaly Detection for Embedded Network Security Cyber Sensor

    Energy Technology Data Exchange (ETDEWEB)

    Ondrej Linda; Todd Vollmer; Jason Wright; Milos Manic

    2011-04-01

    Resiliency and security in critical infrastructure control systems in the modern world of cyber terrorism constitute a relevant concern. Developing a network security system specifically tailored to the requirements of such critical assets is of a primary importance. This paper proposes a novel learning algorithm for anomaly based network security cyber sensor together with its hardware implementation. The presented learning algorithm constructs a fuzzy logic rule based model of normal network behavior. Individual fuzzy rules are extracted directly from the stream of incoming packets using an online clustering algorithm. This learning algorithm was specifically developed to comply with the constrained computational requirements of low-cost embedded network security cyber sensors. The performance of the system was evaluated on a set of network data recorded from an experimental test-bed mimicking the environment of a critical infrastructure control system.

  4. Foundations Of Fuzzy Control

    DEFF Research Database (Denmark)

    Jantzen, Jan

    The objective of this textbook is to acquire an understanding of the behaviour of fuzzy logic controllers. Under certain conditions a fuzzy controller is equivalent to a proportional-integral-derivative (PID) controller. Using that equivalence as a link, the book applies analysis methods from...... linear and nonlinear control theory. In the linear domain, PID tuning methods and stability analyses are transferred to linear fuzzy controllers. The Nyquist plot shows the robustness of different settings of the fuzzy gain parameters. As a result, a fuzzy controller is guaranteed to perform as well...... as any PID controller. In the nonlinear domain, the stability of four standard control surfaces is analysed by means of describing functions and Nyquist plots. The self-organizing controller (SOC) is shown to be a model reference adaptive controller. There is a possibility that a nonlinear fuzzy PID...

  5. Decision support system for triage management: A hybrid approach using rule-based reasoning and fuzzy logic.

    Science.gov (United States)

    Dehghani Soufi, Mahsa; Samad-Soltani, Taha; Shams Vahdati, Samad; Rezaei-Hachesu, Peyman

    2018-06-01

    Fast and accurate patient triage for the response process is a critical first step in emergency situations. This process is often performed using a paper-based mode, which intensifies workload and difficulty, wastes time, and is at risk of human errors. This study aims to design and evaluate a decision support system (DSS) to determine the triage level. A combination of the Rule-Based Reasoning (RBR) and Fuzzy Logic Classifier (FLC) approaches were used to predict the triage level of patients according to the triage specialist's opinions and Emergency Severity Index (ESI) guidelines. RBR was applied for modeling the first to fourth decision points of the ESI algorithm. The data relating to vital signs were used as input variables and modeled using fuzzy logic. Narrative knowledge was converted to If-Then rules using XML. The extracted rules were then used to create the rule-based engine and predict the triage levels. Fourteen RBR and 27 fuzzy rules were extracted and used in the rule-based engine. The performance of the system was evaluated using three methods with real triage data. The accuracy of the clinical decision support systems (CDSSs; in the test data) was 99.44%. The evaluation of the error rate revealed that, when using the traditional method, 13.4% of the patients were miss-triaged, which is statically significant. The completeness of the documentation also improved from 76.72% to 98.5%. Designed system was effective in determining the triage level of patients and it proved helpful for nurses as they made decisions, generated nursing diagnoses based on triage guidelines. The hybrid approach can reduce triage misdiagnosis in a highly accurate manner and improve the triage outcomes. Copyright © 2018 Elsevier B.V. All rights reserved.

  6. Application of an advanced fuzzy logic model for landslide susceptibility analysis

    Directory of Open Access Journals (Sweden)

    Biswajeet Pradhan

    2010-09-01

    Full Text Available The aim of this study is to evaluate the susceptibility of landslides at Klang valley area, Malaysia, using a Geographic Information System (GIS and remote sensing. Landslide locations were identified in the study area from interpretation of aerial photographs and from field surveys. Topographical and geological data and satellite images were collected, processed, and constructed into a spatial database using GIS and image processing. A data derived model (frequency ratio and a knowledge-derived model (fuzzy operator were combined for landslide susceptibility analysis. The nine factors that influence landslide occurrence were extracted from the database and the frequency ratio coefficient for each factor was computed. Using the factors and the identified landslide, the fuzzy membership values were calculated. Then fuzzy algebraic operators were applied to the fuzzy membership values for landslide susceptibility mapping. Finally, the produced map was verified by comparing with existing landslide locations for calculating prediction accuracy. Among the fuzzy operators, in the case in which the gamma operator (l = 0.8 showed the best accuracy (91% while the case in which the fuzzy algebraic product was applied showed the worst accuracy (79%.

  7. Point-like Particles in Fuzzy Space-time

    OpenAIRE

    Francis, Charles

    1999-01-01

    This paper is withdrawn as I am no longer using the term "fuzzy space- time" to describe the uncertainty in co-ordinate systems implicit in quantum logic. Nor am I using the interpretation that quantum logic can be regarded as a special case of fuzzy logic. This is because there are sufficient differences between quantum logic and fuzzy logic that the explanation is confusing. I give an interpretation of quantum logic in "A Theory of Quantum Space-time"

  8. Quality Improvement of Liver Ultrasound Images Using Fuzzy Techniques.

    Science.gov (United States)

    Bayani, Azadeh; Langarizadeh, Mostafa; Radmard, Amir Reza; Nejad, Ahmadreza Farzaneh

    2016-12-01

    Liver ultrasound images are so common and are applied so often to diagnose diffuse liver diseases like fatty liver. However, the low quality of such images makes it difficult to analyze them and diagnose diseases. The purpose of this study, therefore, is to improve the contrast and quality of liver ultrasound images. In this study, a number of image contrast enhancement algorithms which are based on fuzzy logic were applied to liver ultrasound images - in which the view of kidney is observable - using Matlab2013b to improve the image contrast and quality which has a fuzzy definition; just like image contrast improvement algorithms using a fuzzy intensification operator, contrast improvement algorithms applying fuzzy image histogram hyperbolization, and contrast improvement algorithms by fuzzy IF-THEN rules. With the measurement of Mean Squared Error and Peak Signal to Noise Ratio obtained from different images, fuzzy methods provided better results, and their implementation - compared with histogram equalization method - led both to the improvement of contrast and visual quality of images and to the improvement of liver segmentation algorithms results in images. Comparison of the four algorithms revealed the power of fuzzy logic in improving image contrast compared with traditional image processing algorithms. Moreover, contrast improvement algorithm based on a fuzzy intensification operator was selected as the strongest algorithm considering the measured indicators. This method can also be used in future studies on other ultrasound images for quality improvement and other image processing and analysis applications.

  9. Human reliability analysis data obtainment through fuzzy logic in nuclear plants

    Energy Technology Data Exchange (ETDEWEB)

    Nascimento, C.S. do, E-mail: claudio.souza@ctmsp.mar.mil.br [Centro Tecnologico da Marinha em Sao Paulo (CTMSP), Av. Professor Lineu Prestes 2468, 05508-000 Sao Paulo, SP (Brazil); Mesquita, R.N. de, E-mail: rnavarro@ipen.br [Instituto de Pesquisas Energeticas e Nucleares (IPEN/CNEN - SP), Av. Professor Lineu Prestes 2242, 05508-000 Sao Paulo, SP (Brazil)

    2012-09-15

    Highlights: Black-Right-Pointing-Pointer Human Error Probability estimates from operator's reactions to emergency situations. Black-Right-Pointing-Pointer Human Reliability Analysis input data obtainment through fuzzy logic inference. Black-Right-Pointing-Pointer Performance Shaping Factors evaluation influence level onto the operator's actions. - Abstract: Human error has been recognized as an important factor for many industrial and nuclear accidents occurrence. Human error data is scarcely available for different reasons among which, lapses in historical database registry methodology is an important one. Human Reliability Analysis (HRA) is an usual tool employed to estimate the probability that an operator will reasonably perform a system required task in required time without degrading the system. This meta-analysis requires specific Human Error Probability estimates for most of its procedure. This work obtains Human Error Probability (HEP) estimates from operator's actions in response to emergency situations hypothesis on Research Reactor IEA-R1 from IPEN, Brazil. Through this proposed methodology HRA should be able to be performed even with shortage of related human error statistical data. A Performance Shaping Factors (PSF's) evaluation in order to classify and estimate their influence level onto the operator's actions and to determine their actual state over the plant was also done. Both HEP estimation and PSF evaluation were done based on expert judgment using interviews and questionnaires. Expert group was established based on selected IEA-R1 operators, and their evaluation were put into a knowledge representation system which used linguistic variables and group evaluation values that were obtained through Fuzzy Logic and Fuzzy Set theory. HEP obtained values show good agreement with literature published data corroborating the proposed methodology as a good alternative to be used on HRA.

  10. Structural Health Monitoring of Transport Aircraft with Fuzzy Logic Modeling

    Directory of Open Access Journals (Sweden)

    Ray C. Chang

    2013-01-01

    Full Text Available A structural health monitoring method based on the concept of static aeroelasticity is presented in this paper. This paper focuses on the estimation of these aeroelastic effects on older transport aircraft, in particular the structural components that are most affected, in severe atmospheric turbulence. Because the structural flexibility properties are mostly unknown to aircraft operators, only the trend, not the magnitude, of these effects is estimated. For this purpose, one useful concept in static aeroelastic effects for conventional aircraft structures is that under aeroelastic deformation the aerodynamic center should move aft. This concept is applied in the present paper by using the fuzzy-logic aerodynamic models. A twin-jet transport aircraft in severe atmospheric turbulence involving plunging motion is examined. It is found that the pitching moment derivatives in cruise with moderate to severe turbulence in transonic flight indicate some degree of abnormality in the stabilizer (i.e., the horizontal tail. Therefore, the horizontal tail is the most severely affected structural component of the aircraft probably caused by vibration under the dynamic loads induced by turbulence.

  11. FUZZY MAPPING IN DATA SONIFICATION SYSTEM OF WIRELESS SENSOR NETWORK

    Directory of Open Access Journals (Sweden)

    Arseny A. Markhotin

    2016-11-01

    Full Text Available Problem Statement. This paper describes the modeling of sonification system with possible types of wireless sensor network data. Fuzzy logic is used for the data-to-sound mapping. Methods. Devised sonification system includes input data model and sound synthesis core. It was created in Pure Data. For fuzzy output of mapped data the Fuzzy Logic Toolboxof MATLABwas used. Moreover, the system model has an ability to send data to the side application via UDP protocol. Results. We offer the method of timbre space organization for sonification system output and the following output of control sound characteristics depending on the type of input data. Practical Relevance. The offered approach of using fuzzy logic in sonification systems can be applied in development of new applications when the formalization of data-to-sound mapping is difficult and also complicated timbal space organization is required.

  12. Análise de projetos para unidades de conservação, usando lógica fuzzy Analysis of projects in conservation units, using fuzzy logic

    Directory of Open Access Journals (Sweden)

    Sandro Medeiros

    2007-08-01

    Full Text Available Este trabalho apresenta um método para a análise de projetos candidatos à implantação em Unidades de Conservação, que usa a operação dos principais indicadores da economia, sociologia e ecologia, por meio da lógica fuzzy. São estruturadas árvores de decisão no modo top-down, onde as entradas são os indicadores primários e cada output é resultado de operações lógicas em um bloco de regras do tipo "se, e, ou, então". A lógica fuzzy foi escolhida em função da sua transparência para operar as informações, permitindo aos decisores uma clara compreensão sobre as conseqüências decorrentes das decisões tomadas ao longo do processo de análise. Como objeto de análise, foi considerada a possibilidade da implantação de um projeto turístico em uma área de restinga pertencente ao Estado de Santa Catarina. O resultado da aplicação do método mostra que ele é capaz de indicar aos decisores os níveis de apropriação de um projeto específico às condições dadas.This work presents a method for projects analyses, which are applying for implantation in Conservation Units, which operates economics, sociology, and ecology indicators by fuzzy logic. Top-down decision trees are structured, where the entries are the primary indicators and each output is the result of logic operations in a block of rules with operators "if", and, or, so". The fuzzy logic was chosen due to its transparency when operating the information, allowing the stakeholders to clearly understand the consequences caused by the decisions made throughout the analysis process. The possibility of implanting a tourist project was considered as object of analysis, in an area that belongs to the state of Santa Catarina, Brazil. The State government has already showed the intention of building a ecological park in such area. The result of the utilization of the method shows that it can show the stakeholders the levels of adequacy of a specific project to the given

  13. Autonomous Control of a Quadrotor UAV Using Fuzzy Logic

    Science.gov (United States)

    Sureshkumar, Vijaykumar

    UAVs are being increasingly used today than ever before in both military and civil applications. They are heavily preferred in "dull, dirty or dangerous" mission scenarios. Increasingly, UAVs of all kinds are being used in policing, fire-fighting, inspection of structures, pipelines etc. Recently, the FAA gave its permission for UAVs to be used on film sets for motion capture and high definition video recording. The rapid development in MEMS and actuator technology has made possible a plethora of UAVs that are suited for commercial applications in an increasingly cost effective manner. An emerging popular rotary wing UAV platform is the Quadrotor A Quadrotor is a helicopter with four rotors, that make it more stable; but more complex to model and control. Characteristics that provide a clear advantage over other fixed wing UAVs are VTOL and hovering capabilities as well as a greater maneuverability. It is also simple in construction and design compared to a scaled single rotorcraft. Flying such UAVs using a traditional radio Transmitter-Receiver setup can be a daunting task especially in high stress situations. In order to make such platforms widely applicable, a certain level of autonomy is imperative to the future of such UAVs. This thesis paper presents a methodology for the autonomous control of a Quadrotor UAV using Fuzzy Logic. Fuzzy logic control has been chosen over conventional control methods as it can deal effectively with highly nonlinear systems, allows for imprecise data and is extremely modular. Modularity and adaptability are the key cornerstones of FLC. The objective of this thesis is to present the steps of designing, building and simulating an intelligent flight control module for a Quadrotor UAV. In the course of this research effort, a Quadrotor UAV is indigenously developed utilizing the resources of an online open source project called Aeroquad. System design is comprehensively dealt with. A math model for the Quadrotor is developed and a

  14. Intelligent Mechatronics Systems for Transport Climate Parameters Optimization Using Fuzzy Logic Control

    OpenAIRE

    Beinarts, I; Ļevčenkovs, A; Kuņicina, N

    2007-01-01

    In article interest is concentrated on the climate parameters optimization in passengers’ salon of public electric transportation vehicles. The article presents mathematical problem for using intelligent agents in mechatronics problems for climate parameters optimal control. Idea is to use fuzzy logic and intelligent algorithms to create coordination mechanism for climate parameters control to save electrical energy, and it increases the level of comfort for passengers. A special interest for...

  15. Deteksi Kebocoran Gas LPG Menggunakan Detektor Arduino dengan Algoritma Fuzzy Logic Mandani

    OpenAIRE

    Lukman Hakim; Vidi Yonatan

    2017-01-01

    Bencana kebakaran yang diakibatkan oleh kebocoran gas LPG (Liquid  Petroleum   Gas) mengalami kenaikan setiap tahun dari tahun 2011 sampai 2015 diantaranya 17% diakibatkan oleh kebocoran gas. Penggunaan detektor kebocoran gas LPG menggunakan arduino yang dilengkapi sensor gas dan suhu memberikan kemudahan untuk deteksi secara awal terjadinya kebocoran dan kebakaran. Perancangan detektor kebocoran gas LPG menggunakan algoritma fuzzy logic mandani, dilengkapi dengan informasi melalui Short Mess...

  16. Study and simulation of a MPPT controller based on fuzzy logic controller for photovoltaic system

    Energy Technology Data Exchange (ETDEWEB)

    Belaidi, R.; Chikouche, A.; Fathi, M.; Mohand Kaci, G.; Smara, Z. [Unite de Developpement des Equipements Solaires (Algeria); Haddouche, A. [Universite Badji Mokhtar (Algeria)], E-mail: rachidi3434@yahoo.fr

    2011-07-01

    With the depletion of fossil fuels and the increasing concerns about the environment, renewable energies have become more and more attractive. Photovoltaic systems convert solar energy into electric energy through the use of photovoltaic cells. The aim of this paper is to compare the capacity of fuzzy logic and perturb and observe controllers in optimizing the control performance of photovoltaic systems. Simulations were performed using Matlab and Simulink and were analyzed to determine the effectiveness of both controllers and compare them. Results showed that the fuzzy controller has a better dynamic performance than the perturb and observe controller in terms of response time and damping characteristics. In addition, the fuzzy controller was found to better follow the maximum power point and to provide faster convergence and lower statistical error. This study demonstrated that the fuzzy controller gives a better performance than traditional controllers in optimizing the performance of photovoltaic systems.

  17. On the use of fuzzy logics in the operator support system of an experimental facility

    International Nuclear Information System (INIS)

    Mozhaev, A.A.

    1988-01-01

    Problems of consrtuction of the computerized operator support system of the experimental device are considered on the basis of the imitation decision-making model which uses the fuzzy logic apparatus for a formal description of the decision-making process. 22 refs.; 4 figs.; 2 tabs

  18. Hierarchical type-2 fuzzy aggregation of fuzzy controllers

    CERN Document Server

    Cervantes, Leticia

    2016-01-01

    This book focuses on the fields of fuzzy logic, granular computing and also considering the control area. These areas can work together to solve various control problems, the idea is that this combination of areas would enable even more complex problem solving and better results. In this book we test the proposed method using two benchmark problems: the total flight control and the problem of water level control for a 3 tank system. When fuzzy logic is used it make it easy to performed the simulations, these fuzzy systems help to model the behavior of a real systems, using the fuzzy systems fuzzy rules are generated and with this can generate the behavior of any variable depending on the inputs and linguistic value. For this reason this work considers the proposed architecture using fuzzy systems and with this improve the behavior of the complex control problems.

  19. Fuzzy logic-based battery charge controller

    International Nuclear Information System (INIS)

    Daoud, A.; Midoun, A.

    2006-01-01

    Photovoltaic power system are generally classified according to their functional and operational requirements, their component configurations, and how the equipment is connected to other power sources and electrical loads, photovoltaic systems can be designed to provide DC and/or AC power service, can operate interconnected with or independent of the utility grid, and can be connected with other energy sources and energy storage systems. Batteries are often used in PV systems for the purpose of storing energy produced by the PV array during the day, and to supply it to electrical loads as needed (during the night and periods of cloudy weather). The lead acid battery, although know for more than one hundred years, has currently offered the best response in terms of price, energetic efficiency and lifetime. The main function of controller or regulator in PV system is too fully charge the battery without permitting overcharge while preventing reverse current flow at night. If a no-self-regulating solar array is connected to lead acid batteries with no overcharge protection, battery life will be compromised. Simple controllers contain a transistor that disconnects or reconnects the PV in the charging circuit once a pre-set voltage is reached. More sophisticated controllers utilize pulse with modulation (PWM) to assure the battery is being fully charged. The first 70% to 80% of battery capacity is easily replaced, but the last 20% to 30% requires more attention and therefore more complexity. This complexity is avoided by using a skilled operators experience in the form of the rules. Thus a fuzzy control system seeks to control the battery that cannot be controlled well by a conventional control such as PID, PD, PI etc., due to the unavailability of an accurate mathematical model of the battery. In this paper design of an intelligent battery charger, in which the control algorithm is implemented with fuzzy logic is discussed. The digital architecture is implemented with

  20. Study on scenario evaluation methodology for decommissioning nuclear facilities using fuzzy logic

    International Nuclear Information System (INIS)

    Matsuhashi, Kazuya; Yanagihara, Satoshi

    2015-01-01

    Since there are many scenarios of the process from start to completion of a decommissioning project, it is important to study scenarios of decommissioning by evaluating such properties as safety, cost, and technology. An optimum scenario with the highest feasibility in accordance with the facility and environmental conditions should be selected on the basis of the results of the study. For analyzing a scenario of decommissioning, we prepared structured work packages by using the work breakdown structures (WBS) method together with qualitative evaluation of the technologies being applied to work packages located at the bottom (the third level) of the WBS. A calculation model was constructed to evaluate the feasibility of a scenario where fuzzy logic is applied to derive a score of technology performance and TOPSIS is applied for getting a feasibility grade of the scenario from technical performance scoring. As a case study, the model was applied to the debris removal scenario of Fukushima Daiichi Nuclear Power Plant to confirm its applicability. Two scenarios, underwater and in-air debris removal cases, were characterized by extracting the work packages with the lowest feasibility and by obtaining total average scores of the scenarios. It is confirmed that the methodology developed is useful for the scenario evaluation of decommissioning nuclear facilities. (author)

  1. Design of a fuzzy logic based controller for neutron power regulation; Diseno de un controlador basado en logica difusa para la regulacion de flujo neutronico

    Energy Technology Data Exchange (ETDEWEB)

    Velez D, D

    2000-07-01

    This work presents a fuzzy logic controller design for neutron power control, from its source to its full power level, applied to a nuclear reactor model. First, we present the basic definitions on fuzzy sets as generalized definitions of the crisp (non fuzzy) set theory. Likewise, we define the basic operations on fuzzy sets (complement, union, and intersection), and the operations on fuzzy relations such as projection and cylindrical extension operations. Furthermore, some concepts of the fuzzy control theory, such as the main modules of the typical fuzzy controller structure and its internal variables, are defined. After the knowledge base is obtained by simulation of the reactor behavior, where the controlled system is modeled by a simple nonlinear reactor model, this model is used to infer a set of fuzzy rules for the reactor response to different insertions of reactivity. The reduction of the response time, using fuzzy rule based controllers on this reactor, is possible by adjusting the output membership functions, by selecting fuzzy rule sets, or by increasing the number of crisp inputs to the fuzzy controller. System characteristics, such as number of rules, response times, and safety parameter values, were considered in the evaluation of each controller merits. Different fuzzy controllers are designed to attain the desired power level, to maintain a constant level for long periods of time, and to keep the reactor away from a shutdown condition. The basic differences among the controllers are the number of crisp inputs and the novel implementation of a crisp power level-based selection of different sets of output membership functions. Simulation results highlight, mainly: (1) A decrease of the response variations at low power level, and (2) a decrease in the time required to attain the desired neutron power. Finally, we present a comparative study of different fuzzy control algorithms applied to a nuclear model. (Author)

  2. Development of an object-oriented software based on fuzzy-logic for controlling temperatures in PAC experiments

    International Nuclear Information System (INIS)

    Lapolli, Andre L.; Yamagishi, Sueli; Domienikan, Claudio; Schoueri, Roberto M.; Carbonari, Artur W.; Saxena, Rajendra N.

    2009-01-01

    The Hyperfine Interaction Laboratory at Instituto de Pesquisas Energeticas e Nucleares (IPEN) has been using Perturbed Angular Correlation (PAC) technique for studying material science for more than 20 years. One of the important aspects of the research involves the study of the behavior of measured properties of samples as a function of temperature. For temperatures higher than room temperature a small resistance furnace is used to heat the sample. The need to carry out the PAC measurement at predefined temperatures steps in a programmed manner is obvious. The present work describes a procedure for the furnace temperature control and automatic data acquisition at different temperatures based on fuzzy logic. The procedure consists in determining the linguistic input (temp, Δtemp) and output (pow) variables and their pertinence functions. After defining the variables, an object.oriented program is written in Java language which is an interface between principal data acquisition program and electronic temperature controller of the mini furnace. In addition to the implementation of the class that involves the fuzzy logic and classes with strategic algorithms defined for each temperature range there are classes of communication between systems based on modbus protocol RTU (Remote Terminal Unit) connected to serial interface RS-488. In this manner the applied technology for the development of software permits higher software life requiring only small alterations or implementation of classes in the use with new equipment. (author)

  3. The Fuzzy Logic Method to Efficiently Optimize Electricity Consumption in Individual Housing

    Directory of Open Access Journals (Sweden)

    Sébastien Bissey

    2017-10-01

    Full Text Available Electricity demand shifting and reduction still raise a huge interest for end-users at the household level, especially because of the ongoing design of a dynamic pricing approach. In particular, end-users must act as the starting point for decreasing their consumption during peak hours to prevent the need to extend the grid and thus save considerable costs. This article points out the relevance of a fuzzy logic algorithm to efficiently predict short term load consumption (STLC. This approach is the cornerstone of a new home energy management (HEM algorithm which is able to optimize the cost of electricity consumption, while smoothing the peak demand. The fuzzy logic modeling involves a strong reliance on a complete database of real consumption data from many instrumented show houses. The proposed HEM algorithm enables any end-user to manage his electricity consumption with a high degree of flexibility and transparency, and “reshape” the load profile. For example, this can be mainly achieved using smart control of a storage system coupled with remote management of the electric appliances. The simulation results demonstrate that an accurate prediction of STLC gives the possibility of achieving optimal planning and operation of the HEM system.

  4. Fuzzy logic control to be conventional method

    International Nuclear Information System (INIS)

    Eker, Ilyas; Torun, Yunis

    2006-01-01

    Increasing demands for flexibility and fast reactions in modern process operation and production methods result in nonlinear system behaviour of partly unknown systems, and this necessitates application of alternative control methods to meet the demands. Fuzzy logic (FL) control can play an important role because knowledge based design rules can easily be implemented in systems with unknown structure, and it is going to be a conventional control method since the control design strategy is simple and practical and is based on linguistic information. Computational complexity is not a limitation any more because the computing power of computers has been significantly improved even for high speed industrial applications. This makes FL control an important alternative method to the conventional PID control method for use in nonlinear industrial systems. This paper presents a practical implementation of the FL control to an electrical drive system. Such drive systems used in industry are composed of masses moving under the action of position and velocity dependent forces. These forces exhibit nonlinear behaviour. For a multi-mass drive system, the nonlinearities, like Coulomb friction and dead zone, significantly influence the operation of the systems. The proposed FL control configuration is based on speed error and change of speed error. The feasibility and effectiveness of the control method are experimentally demonstrated. The results obtained from conventional FL control, fuzzy PID and adaptive FL control are compared with traditional PID control for the dynamic responses of the closed loop drive system

  5. Fuzzy logic control to be conventional method

    Energy Technology Data Exchange (ETDEWEB)

    Eker, Ilyas [University of Gaziantep, Gaziantep (Turkey). Department of Electrical and Electronic Engineering; Torun, Yunis [University of Gaziantep, Gaziantep (Turkey). Technical Vocational School of Higher Education

    2006-03-01

    Increasing demands for flexibility and fast reactions in modern process operation and production methods result in nonlinear system behaviour of partly unknown systems, and this necessitates application of alternative control methods to meet the demands. Fuzzy logic (FL) control can play an important role because knowledge based design rules can easily be implemented in systems with unknown structure, and it is going to be a conventional control method since the control design strategy is simple and practical and is based on linguistic information. Computational complexity is not a limitation any more because the computing power of computers has been significantly improved even for high speed industrial applications. This makes FL control an important alternative method to the conventional PID control method for use in nonlinear industrial systems. This paper presents a practical implementation of the FL control to an electrical drive system. Such drive systems used in industry are composed of masses moving under the action of position and velocity dependent forces. These forces exhibit nonlinear behaviour. For a multi-mass drive system, the nonlinearities, like Coulomb friction and dead zone, significantly influence the operation of the systems. The proposed FL control configuration is based on speed error and change of speed error. The feasibility and effectiveness of the control method are experimentally demonstrated. The results obtained from conventional FL control, fuzzy PID and adaptive FL control are compared with traditional PID control for the dynamic responses of the closed loop drive system. (author)

  6. Efficient Fuzzy Logic Controller for Magnetic Levitation Systems

    African Journals Online (AJOL)

    Akorede

    ABSTRACT: Magnetic levitation is a system of suspending a body or a complete system against gravity. Suspending a system ... disturbance signal was applied to the input of the control system. Fuzzy ..... Automatic Control System, fifth edition.

  7. Adaptive Interval Type-2 Fuzzy Logic Control for PMSM Drives with a Modified Reference Frame

    KAUST Repository

    Chaoui, Hicham

    2017-01-10

    In this paper, an adaptive interval type-2 fuzzy logic control scheme is proposed for high-performance permanent magnet synchronous machine drives. This strategy combines the power of type-2 fuzzy logic systems with the adaptive control theory to achieve accurate tracking and robustness to higher uncertainties. Unlike other controllers, the proposed strategy does not require electrical transducers and hence, no explicit currents loop regulation is needed, which yields a simplified control scheme. But, this limits the machine\\'s operation range since it results in a higher energy consumption. Therefore, a modified reference frame is also proposed in this paper to decrease the machine\\'s consumption. To better assess the performance of the new reference frame, comparison against its original counterpart is carried-out under the same conditions. Moreover, the stability of the closed-loop control scheme is guaranteed by a Lyapunov theorem. Simulation and experimental results for numerous situations highlight the effectiveness of the proposed controller in standstill, transient, and steady-state conditions.

  8. A Novel Strain-Based Method to Estimate Tire Conditions Using Fuzzy Logic for Intelligent Tires

    Directory of Open Access Journals (Sweden)

    Daniel Garcia-Pozuelo

    2017-02-01

    Full Text Available The so-called intelligent tires are one of the most promising research fields for automotive engineers. These tires are equipped with sensors which provide information about vehicle dynamics. Up to now, the commercial intelligent tires only provide information about inflation pressure and their contribution to stability control systems is currently very limited. Nowadays one of the major problems for intelligent tire development is how to embed feasible and low cost sensors to obtain reliable information such as inflation pressure, vertical load or rolling speed. These parameters provide key information for vehicle dynamics characterization. In this paper, we propose a novel algorithm based on fuzzy logic to estimate the mentioned parameters by means of a single strain-based system. Experimental tests have been carried out in order to prove the suitability and durability of the proposed on-board strain sensor system, as well as its low cost advantages, and the accuracy of the obtained estimations by means of fuzzy logic.

  9. A VIRTUAL REALITY EXPOSURE THERAPY FOR PTSD PATIENTS CONTROLLED BY A FUZZY LOGIC SYSTEM

    OpenAIRE

    Rosa Maria Esteves Moreira da Costa; Fernando Moraes de Oliveira; Regina Serrão Lanzillotti; Raquel Gonçalves; Luis Alfredo Vidal de Carvalho

    2014-01-01

    This paper describes the main characteristics of two integrated systems that explore Virtual Reality technology and Fuzzy Logic to support and to control the assessment of people with Post-Traumatic Stress Disorder during the Virtual Reality Exposure Therapy. The integration of different technologies, the development methodology and the test procedures are described throughout the paper.

  10. Energy Management of An Extended Hybrid Renewable Energy System For Isolated Sites Using A Fuzzy Logic Controller

    Science.gov (United States)

    Faquir, Sanaa; Yahyaouy, Ali; Tairi, Hamid; Sabor, Jalal

    2018-05-01

    This paper presents the implementation of a fuzzy logic controller to manage the flow of energy in an extended hybrid renewable energy system employed to satisfy the load for a wide isolated site at the city of Essaouira in Morocco. To achieve Efficient energy management, the system is combining two important renewable energies: solar and wind. Lithium Ion batteries were also used as storage devices to store the excess of energy provided by the renewable sources or to supply the system with the required energy when the energy delivered by the input sources is not enough to satisfy the load demand. To manage the energy in the system, a controller based on fuzzy logic was implemented. Real data taken from previous research and meteorological sites was used to test the controller.

  11. Comparative Analysis between Conventional PI and Fuzzy LogicPI Controllers for Indoor Benzene Concentrations

    Directory of Open Access Journals (Sweden)

    Nun Pitalúa-Díaz

    2015-05-01

    Full Text Available Exposure to hazardous concentrations of volatile organic compounds indoors in small workshops could affect the health of workers, resulting in respirative diseases, severe intoxication or even cancer. Controlling the concentration of volatile organic compounds is required to prevent harmful conditions for workers in indoor environments. In this document, PI and fuzzy PI controllers were used to reduce hazardous indoor air benzene concentrations in small workplaces. The workshop is represented by means of a well-mixed room model. From the knowledge obtained from the model, PI and fuzzy PI controllers were designed and their performances were compared. Both controllers were able to maintain the benzene concentration within secure levels for the workers. The fuzzy PI controller performed more efficiently than the PI controller. Both approaches could be expanded to control multiple extractor fans in order to reduce the air pollution in a shorter time. The results from the comparative analysis showed that implementing a fuzzy logic PI controller is promising for assuring indoor air quality in this kind of hazardous work environment.

  12. Coastal vulnerability assessment using Fuzzy Logic and Bayesian Belief Network approaches

    Science.gov (United States)

    Valentini, Emiliana; Nguyen Xuan, Alessandra; Filipponi, Federico; Taramelli, Andrea

    2017-04-01

    Natural hazards such as sea surge are threatening low-lying coastal plains. In order to deal with disturbances a deeper understanding of benefits deriving from ecosystem services assessment, management and planning can contribute to enhance the resilience of coastal systems. In this frame assessing current and future vulnerability is a key concern of many Systems Of Systems SOS (social, ecological, institutional) that deals with several challenges like the definition of Essential Variables (EVs) able to synthesize the required information, the assignment of different weight to be attributed to each considered variable, the selection of method for combining the relevant variables. It is widely recognized that ecosystems contribute to human wellbeing and then their conservation increases the resilience capacities and could play a key role in reducing climate related risk and thus physical and economic losses. A way to fully exploit ecosystems potential, i.e. their so called ecopotential (see H2020 EU funded project "ECOPOTENTIAL"), is the Ecosystem based Adaptation (EbA): the use of ecosystem services as part of an adaptation strategy. In order to provide insight in understanding regulating ecosystem services to surge and which variables influence them and to make the best use of available data and information (EO products, in situ data and modelling), we propose a multi-component surge vulnerability assessment, focusing on coastal sandy dunes as natural barriers. The aim is to combine together eco-geomorphological and socio-economic variables with the hazard component on the base of different approaches: 1) Fuzzy Logic; 2) Bayesian Belief Networks (BBN). The Fuzzy Logic approach is very useful to get a spatialized information and it can easily combine variables coming from different sources. It provides information on vulnerability moving along-shore and across-shore (beach-dune transect), highlighting the variability of vulnerability conditions in the spatial

  13. Implementation of fuzzy logic for mitigating conflicts of frequency containment control

    DEFF Research Database (Denmark)

    Rikos, Evangelos; Syed, Mazheruddin; Caerts, Chris

    2017-01-01

    Ever increasing shares of intermittent renewable energy sources (RES) in present and future power systems pose new challenges with regard to operation, particularly balance, frequency and voltage stability. Towards effective solutions, the ELECTRA IRP project has developed a novel structure...... imposed by different system conditions. To this end, a design method based on fuzzy logic for avoiding conflicts caused from these conditions or multiple control loops implemented on the same resource is proposed. Simulation results for various selected scenarios and controllers show the effectiveness...

  14. Selection of relevant items for decommissioning costing estimation of a PWR using fuzzy logic

    International Nuclear Information System (INIS)

    Monteiro, Deiglys Borges; Busse, Alexander Lucas; Moreira, Joao M.L.; Maiorino, Jose Rubens

    2015-01-01

    The decommissioning is an important part of a nuclear power plant life cycle which may occur by technical, economical or safety reasons. Decommissioning requires carrying out a large number of tasks that should be planned in advance, involves cost evaluations, preparation of plans of activity and actual operational actions. Despite the large number of tasks, only part of them is relevant for cost estimation purpose. The technical literature and international regulatory agencies suggest a variety of methods for decommissioning cost estimation. Most of them require a very detailed knowledge of the plant and data available suitable for plants that are starting their decommissioning but not for those in the planning stage. The present work aims to apply fuzzy logic to sort out relevant items to cost estimation in order to reduce the work effort involved. The scheme uses parametric equations for specific cost items, and is applied to specific parts of the process of nuclear power plant decommissioning. (author)

  15. Selection of relevant items for decommissioning costing estimation of a PWR using fuzzy logic

    Energy Technology Data Exchange (ETDEWEB)

    Monteiro, Deiglys Borges; Busse, Alexander Lucas; Moreira, Joao M.L.; Maiorino, Jose Rubens, E-mail: deiglys.monteiro@ufabc.edu.br, E-mail: alexlucasb@gmail.com, E-mail: joao.moreira@ufabc.edu.br, E-mail: joserubens.maiorino@ufabc.edu.br [Universidade Federal do ABC (CECS/UFABC), Santo Andre, SP (Brazil). Centro de Engenharia, Modelagem e Ciencias Aplicadas. Programa de Pos-Graduacao em Energia e Engenharia da Energia

    2015-07-01

    The decommissioning is an important part of a nuclear power plant life cycle which may occur by technical, economical or safety reasons. Decommissioning requires carrying out a large number of tasks that should be planned in advance, involves cost evaluations, preparation of plans of activity and actual operational actions. Despite the large number of tasks, only part of them is relevant for cost estimation purpose. The technical literature and international regulatory agencies suggest a variety of methods for decommissioning cost estimation. Most of them require a very detailed knowledge of the plant and data available suitable for plants that are starting their decommissioning but not for those in the planning stage. The present work aims to apply fuzzy logic to sort out relevant items to cost estimation in order to reduce the work effort involved. The scheme uses parametric equations for specific cost items, and is applied to specific parts of the process of nuclear power plant decommissioning. (author)

  16. A VIRTUAL REALITY EXPOSURE THERAPY FOR PTSD PATIENTS CONTROLLED BY A FUZZY LOGIC SYSTEM

    Directory of Open Access Journals (Sweden)

    Rosa Maria Esteves Moreira da Costa

    2014-06-01

    Full Text Available This paper describes the main characteristics of two integrated systems that explore Virtual Reality technology and Fuzzy Logic to support and to control the assessment of people with Post-Traumatic Stress Disorder during the Virtual Reality Exposure Therapy. The integration of different technologies, the development methodology and the test procedures are described throughout the paper.

  17. A virtual reality exposure therapy for PTSD patients controlled by a fuzzy logic system

    OpenAIRE

    Oliveira, F. M.; Lanzillotti, R. S.; Da Costa, R. M. E. M.; Gonçalves, R.; Ventura, P.; Carvalho, L. A. V. de

    2014-01-01

    This paper describes the main characteristics of two integrated systems that explore Virtual Reality technology and Fuzzy Logic to support and to control the assessment of people with Post-Traumatic Stress Disorder during the Virtual Reality Exposure Therapy. The integration of different technologies, the development methodology and the test procedures are described throughout the paper. Peer Reviewed

  18. Fuzziness and fuzzy modelling in Bulgaria's energy policy decision-making dilemma

    International Nuclear Information System (INIS)

    Wang Xingquan

    2006-01-01

    The decision complexity resulting from imprecision in decision variables and parameters, a major difficulty for conventional decision analysis methods, can be relevantly analysed and modelled by fuzzy logic. Bulgaria's nuclear policy decision-making process implicates such complexity of imprecise nature: stakeholders, criteria, measurement, etc. Given the suitable applicability of fuzzy logic in this case, this article tries to offer a concrete fuzzy paradigm including delimitation of decision space, quantification of imprecise variables, and, of course, parameterisation. (author)

  19. An optimized Fuzzy Logic Controller by Water Cycle Algorithm for power management of Stand-alone Hybrid Green Power generation

    International Nuclear Information System (INIS)

    Sarvi, Mohammad; Avanaki, Isa Nasiri

    2015-01-01

    Highlights: • A new method to improve the performance of renewable power management is proposed. • The proposed method is based on Fuzzy Logic optimized by the Water Cycle Algorithm. • The proposed method characteristics are compared with two other methods. • The comparisons confirm that the proposed method is robust and effectiveness one. - Abstract: This paper aims to improve the power management system of a Stand-alone Hybrid Green Power generation based on the Fuzzy Logic Controller optimized by the Water Cycle Algorithm. The proposed Stand-alone Hybrid Green Power consists of wind energy conversion and photovoltaic systems as primary power sources and a battery, fuel cell, and Electrolyzer as energy storage systems. Hydrogen is produced from surplus power generated by the wind energy conversion and photovoltaic systems of Stand-alone Hybrid Green Power and stored in the hydrogen storage tank for fuel cell later using when the power generated by primary sources is lower than load demand. The proposed optimized Fuzzy Logic Controller based power management system determines the power that is generated by fuel cell or use by Electrolyzer. In a hybrid system, operation and maintenance cost and reliability of the system are the important issues that should be considered in studies. In this regard, Water Cycle Algorithm is used to optimize membership functions in order to simultaneously minimize the Loss of Power Supply Probability and operation and maintenance. The results are compared with the particle swarm optimization and the un-optimized Fuzzy Logic Controller power management system to prove that the proposed method is robust and effective. Reduction in Loss of Power Supply Probability and operation and maintenance, are the most advantages of the proposed method. Moreover the level of the State of Charge of the battery in the proposed method is higher than other mentioned methods which leads to increase battery lifetime.

  20. Fuzzy control and identification

    CERN Document Server

    Lilly, John H

    2010-01-01

    This book gives an introduction to basic fuzzy logic and Mamdani and Takagi-Sugeno fuzzy systems. The text shows how these can be used to control complex nonlinear engineering systems, while also also suggesting several approaches to modeling of complex engineering systems with unknown models. Finally, fuzzy modeling and control methods are combined in the book, to create adaptive fuzzy controllers, ending with an example of an obstacle-avoidance controller for an autonomous vehicle using modus ponendo tollens logic.