Fuzzy controllers are used to control consumer products, such as washing machines, video cameras, and rice cookers, as well as industrial processes, such as cement kilns, underground trains, and robots. Fuzzy control is a control method based on fuzzy logic. Just as Fuzzy logic can be described simply as “computing with words rather than numbers’’ and Fuzzy control can be described simply as “control with sentences rather than equations’’. A Fuzzy controller can include empirical rules, and that is especially useful in operator controlled plants.This is the world of automation. The majority of the products allow actions to be automatically triggered by events. The Performance of a SCADA system can be much improved using a fuzzy logic controller based SCADA in industries. This book describes design of fuzzy logic based SCADA Systems using MATLAB fuzzy logic toolbox.This Book is useful for Engineers and Research Scholars in the field of Electrical & Power Engineering.
Over the last few decades industrial automation has become the most desirous subject to increase the productivity with quality and quantity enhancement and consider the cost management of the product. A new approach of Fuzzy Logic Time Control Discrete Event System DEV provides an opportunity to establish a control design with certain time constraint of activation under the fuzzy control of input variables. A multi-agent based approach helps the control strategy to be motivated with all internal and external factors effecting the system casually under un predetermined conditions.An approach to use the fuzzy system in local and distributed environment is explored using a simplified design algorithmic approach.Design Models of: Liquids Mixing System,Grinding and Mixing System, and Muti- Dimensional Supervisory Control System with Fuzzy Logic time control DEV strategy are explored for industrial automation.
This study is aimed at characterization of Fuzzy logic control based system with varying span of Member Function by establishing region of stable operation for different cases using range provided by 'k' for setting the span for desired performance.The performed work may be used as reference, by designers for designing a Fuzzy logic based control system depending upon the requirement of desired application.
The main part of the book is a comprehensive overview of the development of fuzzy logic and its applications in various areas of human affair since its genesis in the mid 1960s. This overview is then employed for assessing the significance of fuzzy logic and mathematics based on fuzzy logic.
Over the recent years, Process control systems have found application in many new areas. Integration of knowledge from Computational Intelligence, Telecommunication and Microarchitectures, has led to evolution of many different flavors of process control like Distributed Control System (DCS), Supervisory Control and Data Acquisition System (SCADA) etc. This book describes development of SCADA system for Heating Ventilation and Air Conditioning System. Introduction of Process control logic in a HVAC system helps to optimize its power consumption. SCADA system described in this book is based on an actual project undertaken in 2009 at GIK Institute, Pakistan. HVAC system discussed comprises of 100HP Electrical load and 250 tons of air conditioning load. Effectiveness of introduced SCADA system can be judged by the saving rate of 96% at a negligible operational cost of 3%. Discussed SCADA system is based on innovative use of readily available components for inexpensive development. This text should be particularly helpful for those who are considering customized development of a process control system.
This book presents the details theory and applications of Fuzzy sets,fuzzy systems,membership functions & controller designed. A logic based on the two truth values True and False is sometimes inadequate when describing human reasoning. Fuzzy logic uses the whole interval between 0 (False) and 1 (True ) to describe human reasoning. As a result, fuzzy logic is being applied in rule based automatic controllers. A fuzzy control method for automatic steering and a method for line tracking are conveyed in this article. The principal for fuzzy control steering and the construction of fuzzy controller are described in detail.For Example,A vehicle is refitted with a storage battery car. Navigation control system is developed based on digital compass and other sensors. The vehicle acquires the location information using the fuzzy control steering and line tracking method. Test results indicated that the navigation lateral error was less than 0.3m when the robot ran following the predefined line route. Finally, a power system network with UPFC has been considered & A POD controller has designed by using Fuzzy Logic to improve the damping oscillation of power system network.
Information retrieval system is heart of information system. The primary purpose of establishing an information retrieval system lies in assisting the users to effectively acquire drsired information. That is, users' query must be properly understood and answered. The present work falls in the area of information retrieval and to be more specific : query processing of information retrieval. This has been influenced by the limitation and disadvantages of the commercially available Boolean logic retrieval model. The limitation and disadvantages of the query processing of the Boolean logic model have been pointed out and logical solution using fuzzy set theory and fuzzy logic have been presenteted.
Fuzzy logic which was first introduced by Lotfi A. Zadeh in 1965, transcends the “black and white” approach of the Aristotelian logic, and tries to capture the wide grey areas of imprecision in between. This logic provides a mathematical approach to interpret the grey zones of imprecision. Some authors consider EBM and Fuzzy logic as two sides of a same coin. We believe that fuzzy logic approach is not in contrast to the EBM approach, but it is a complementary tool for a more realistic approach to the practice of evidence-based medicine. By merging and concurrent use of these two approaches (EBM and Fuzzy logic) in the process of decision-making, fuzzy logic can yield its suitable place in the field of medicine, considering the rapidly progression of EBM in this field. In this book we are trying to report our experience in integrating fuzzy logic in the decision process of VTE prophylaxis in hospitalized patients according to an Evidence-based risk assessment model (RAM), developed by Joseph A. Caprini. We believe that the application of Fuzzy thinking model in developing decision support systems can resolve most of the shortcomings of RAMs & practice guidelines.
Petri nets are considered to be the alternative approach for analysis, design and implementation of DES. However, the prospect of uncertain and vague information still creates a problem. Hence, to handle the uncertainty, fuzzy logic is integrated into Petri nets to form Fuzzy Automation Petri nets as a modeling tool to handle these uncertainties. The use of Fuzzy Automation Petri nets (FAPN) demands a valid translation of the formalism to Ladder Logic Diagrams for implementation. This is achieved using Token Passing Methodology. This work investigates the use of Fuzzy Petri nets in supervisory control and suggests a modified and improved version called Fuzzy Automation Petri net (FAPN) as a modeling tool. It presents a systematic approach to the synthesis of Fuzzy Petri net based supervisor for the forbidden state problem using supervisory design procedure. The controlled model of the system can be constructed from this FAPN net structure. The implementation is using Flexible Manufacturing System as an example of DES.
The goal of this book is to let people know about the information retrieval system. It cover the problems in this domain and reviews the solution in current space. It explains how to build the fuzzy inference system in order to score the documents in such a way that most relevant documents will get the higher score against the user's information need. Relevant documents are ranked and then fetched on the basis on these scores. This book provides an overview of fuzzy logic and explains the core concepts underlying fuzzy logic. It also explains the design and implementation strategy of neuro fuzzy inference system for information retrieval by using Adaptive Neuro Fuzzy Inference System (ANFIS) toolbox available in MATLAB. Results and Evaluation are also given at the end for neuro fuzzy inference system and its comparison with the existing techniques for information retrieval.
The design of controllers for non- linear systems in industry is a complex and difficult task. The development of non-linear control techniques has been approaches in many different ways with varied results. One approach, which has shown promise for solving nonlinear control problems, is the use of fuzzy logic control. This book will discuss the Magnetic Levitation (Maglev) models as an example of nonlinear systems. It will also show the design of fuzzy logic controllers for this model to prove that the fuzzy controller can work properly with nonlinear system. Genetic Algorithm (GA) is used in this book as optimization method that optimizes the membership, output gain and inputs gain of the fuzzy controllers. Finally, fuzzy controller will be implemented using FPGA chip. The design will use a high-level programming language HDL for implementing the fuzzy logic controller using the Xfuzzy CAD tools to implement the fuzzy logic controller into HDL code. This book is designed for the professional and academic audience interested primarily in applications of fuzzy logic in engineering and technology.
The last decade has shown that object-oriented concept by itself is not that powerful to cope with the rapidly changing requirements of on-going applications. Component based system achieves flexibility by clearly separating the stable parts of systems (i.e. components) form the specification of their composition. In order to realize the reuse of components effectively in component based software development, it is required to measure the reusability of components. However, due to the black-box nature of components where the source of these components are not available, it is difficult to use conventional metrics in components based development as these metrics require analysis of source codes. In this research, we adopt FUZZY Logic based approach to estimate the reusability of components. Several factors of reusability are taken into account.
Systems based on fuzzy rules are widely used in the development of control, pattern recognition and machine intelligence systems. The structure of the fuzzy rule base is the most influential factor for the performance of fuzzy rule-based systems. This structure is defined by the number of fuzzy partitions and the formation relations used. The number and structure of the fuzzy partitions have to be defined during the design process. Thus, a large number of rules have to be generated. To avoid large computational costs, a reduction process is required. Current procedures for the design of fuzzy-based systems often do not take into account the signal or data specifications for the system considered. In the present study, a new approach for building a fuzzy rule-based system is developed. In this approach, design of the fuzzy rule base is based on the statistical properties of the data considered. A new framework is developed for automated and improved generation of fuzzy-based rules for identification and classification processes. Different benchmark data, comparative approaches, practical application , and hypothesis techniques are used to evaluate the effectiveness of this approach.
Coordinated traffic signals regulate traffic flow through urban areas and minimize delay and maximize traffic flow. In this study an attempt is made to design coordinated traffic signal using the concept of fuzzy logic. Fuzzy logic is very effective in incorporating those parameters which have an inherent fuzziness in them like the user perception. Coordinated signal is designed using fuzzy logic by formulating fuzzy rules relating the qualitative parameter (Quality of progression) and other important quantitative parameters like average stream speed, V/C ratio and average control delay .Measures of effectiveness like average control delay per vehicle per cycle length, band width and efficiency are used to determine the efficiency of signal coordination. It was found that design using Fuzzy logic concept is more efficient and can also account for the dynamic traffic flow conditions.
Relative-Fuzzy is a new approach for handling the complex ambiguity type of uncertainty that may exist in data, for software engineering of predictive Data Mining (DM) classification models. This approach is based on a novel type of fuzzy logic which has been called Relative-Fuzzy Logic (RFL). RFL defines a new formulation of the problem of ambiguity type of uncertainty in terms of States Of Proposition (SOP). RFL describes its membership (semantic) value by using the new definition of Domain of Proposition (DOP), which is based on the relativity principle as defined by possible-worlds logic. Two types of logic; namely fuzzy logic and possible-world logic, have been mixed to produce a new membership value set that is able to handle fuzziness and multiple viewpoints at the same time, which called Relative-Fuzzy membership value set. For implementation purpose, a new architecture of Hierarchical Neural Network (HNN) called ML/RFL-Based Net along with its new learning and recalling algorithms has been developed. This new type of HNN is considered to be a RFL computation based machine.