Fuzzy Control

In: Computers and Technology

Submitted By luishb317
Words 211473
Pages 846
Fuzzy Control
Kevin M. Passino
Department of Electrical Engineering The Ohio State University

Stephen Yurkovich
Department of Electrical Engineering The Ohio State University

An Imprint of Addison-Wesley Longman, Inc.
Menlo Park, California • Reading, Massachusetts Don Mills, Ontaria • Sydney • Bonn

• Harlow, England • Berkeley, California • Amsterdam • Mexico City


Assistant Editor: Laura Cheu Editorial Assistant: Royden Tonomura Senior Production Editor: Teri Hyde Marketing Manager: Rob Merino Manufacturing Supervisor: Janet Weaver Art and Design Manager: Kevin Berry Cover Design: Yvo Riezebos (technical drawing by K. Passino) Text Design: Peter Vacek Design Macro Writer: William Erik Baxter Copyeditor: Brian Jones Proofreader: Holly McLean-Aldis Copyright c 1998 Addison Wesley Longman, Inc. All rights reserved. No part of this publication may be reproduced, or stored in a database or retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, without the prior written permission of the publisher. Printed in the United States of America. Printed simultaneously in Canada. Many of the designations used by manufacturers and sellers to distinguish their products are claimed as trademarks. Where those designations appear in this book, and AddisonWesley was aware of a trademark claim, the designations have been printed in initial caps or in all caps. MATLAB is a registered trademark of The MathWorks, Inc. Library of Congress Cataloging-in-Publication Data Passino, Kevin M. Fuzzy control / Kevin M. Passino and Stephen Yurkovich. p. cm. Includes bibliographical references and index. ISBN 0-201-18074-X 1. Automatic control. 2. Control theory. 3. Fuzzy systems. I. Yurkovich, Stephen. II. Title. TJ213.P317 1997 629.8’9--DC21

97-14003 CIP

Instructional Material Disclaimer: The…...

Similar Documents

Speed Control of Induction Motor Using Fuzzy Logic and Pll

...more advanced control methods to meet the real demand. To overcome the complexities of conventional controllers, fuzzy logic controller have been implemented in many motor applications. A Fuzzy Logic Controller (FLC) is incorporated for combination with Phase Locked Loop (PLL) for precise and robust speed of induction motor. The fuzzy logic controller is used to pull the motor speed into the locking range of PLL. When the speed error is between the set point speed and the measured speed is larger than the preset value, the motor speed is incremented or decremented by the fuzzy logic controller towards the PLL locking range. In order to achieve excellent speed regulation, PLL control replaces the FLC when speed error is within the locking range of PLL. When the system operates in the phase locked loop, the speed of motor is locked by a reference frequency. Synchronization of motor speed to a very accurate reference frequency warrants that the motor speed will not drift due to temperature or component wear. Thus, a precise speed control of induction motor operation is achieved. 1.2 Objective The main objective of this project is design a speed control system of the induction motor based on fuzzy logic controller implemented with phase locked loop controller, employing the scalar control model. The voltage and frequency input to the induction motor are to be controlled in order to obtain the desired speed response. This system will be able to control the induction...

Words: 1757 - Pages: 8

Processual, Rational, Fuzzy, Evolutionary

...Processual, Rational, Fuzzy, Evolutionary 1. Processual approach: Strategy is produced in an incremental fashion, as a 'pattern in a stream of decisions'. Fuzzy approach: Companies sometimes adopt an incremental approach to change. What's different between these two approach? The Processual approach is really talking about strategy emerging from the many different day-to-day decisions taken by the staff. It’s incremental, in that it is occurring by being added to with each decision taken. Each decision taken is based on what seems like the best thing to do at the time; and really, only by looking back can you see the pattern – the strategy – being followed by the organisation. The Fuzzy approach is really when a firm has a stated strategy. It is likely to be following a rational approach to strategy, and it may be doing it very successfully. However, at the same time, it might also be doing something outside of its stated strategy too. This is the “fuzzy” aspect. The example on Page 3.28 is of Macquarie Bank, who had a stated strategy of being the leading investment bank in Australia, but was also involved in 6 different overseas countries at the same time. The idea is that there are reasons why this is a good idea – first, the business might want to change their strategy, but rather than trying to change everything at once they take an incremental approach to making the change – changing some things, and then more later etc. A second reason is that opportunities......

Words: 1267 - Pages: 6


...Control- Defined as any process that directs the activities of individuals toward the achievement of organizational goals. Utilizing control effectively is how managers can make sure that activities are going as planned. Control is a means or mechanism for regulating the behavior of organization members. Left on their own, people may act in ways that they perceive to be beneficial for their selves or the organization they work for but that action may actually harm the organization as a whole. In some cases it’s just plain ignorance, individuals just don’t realize the overall costs of their actions. Thus, control is one of the fundamental forces that keep the organization together and heading in the right direction. Purpose- To ensure that activities are completed in ways that lead to accomplishment of organizational goals. * It can provide organizations with indications on how well they are performing * It allows an organization to adjust performance in order to keep moving in the right direction. Set performance standards Every organization has goals: profitability, innovation, satisfaction of customers and employees, and so on. A standard is the level of expected performance for a given goal. So set standards for any and all activities —financial activities, operating activities, legal compliance, charitable contributions, and so on. Measure performance It’s an ongoing process. Performance measures should be valid indicators (e.g. days......

Words: 591 - Pages: 3

What Is Fuzzy Logic?

...What Is Fuzzy Logic? Fuzzy Logic: | a form of mathematical logic in which truth can assume a continuum of values between 0 and 1. | | Princeton Web Dictionary Fuzzy logic is a form of logic with more than two values. Formally it can be called as probabilistic logic and it simply deals with approximated values rather than exact ones; as in daily language, it includes grays along with black and white. It is also accepted as a problem solving control system methodology. Fuzzy logic is a type of logic that recognizes more than only true and false values. With fuzzy logic, variables can be represented with degrees of truthfulness and falsehood. As an example ‘today is sunny’ statement can be used; this statement, might be 100% true if there are absolutely no clouds, 80% true if there are a few clouds, 50% true if it's partly cloudy and 0% true if it rains all day. Advantages of fuzzy logic can be listed as: * Fuzzy logic is easy to understand. * Fuzzy logic is flexible. * Fuzzy logic is based on natural language. * Fuzzy logic can model nonlinear functions of arbitrary complexity. Advantages of fuzzy logic continued: * Fuzzy logic is tolerant of imprecise data. * Fuzzy logic can be blended with conventional control techniques. * Fuzzy logic can be built on top of the experience of experts. * Fuzzy logic does not solve new problems. It uses new methods to solve everyday problems. * Mathematical concepts within fuzzy......

Words: 1219 - Pages: 5

It Control

...of Information Security Controls Harold F. Tipton Security is generally defined as the freedom from danger or as the condition of safety. Computer security, specifically, is the protection of data in a system against unauthorized disclosure, modification, or destruction and protection of the computer system itself against unauthorized use, modification, or denial of service. Because certain computer security controls inhibit productivity, security is typically a compromise toward which security practitioners, system users, and system operations and administrative personnel work to achieve a satisfactory balance between security and productivity. Controls for providing information security can be physical, technical, or administrative. These three categories of controls can be further classified as either preventive or detective. Preventive controls attempt to avoid the occurrence of unwanted events, whereas detective controls attempt to identify unwanted events after they have occurred. Preventive controls inhibit the free use of computing resources and therefore can be applied only to the degree that the users are willing to accept. Effective security awareness programs can help increase users’ level of tolerance for preventive controls by helping them understand how such controls enable them to trust their computing systems. Common detective controls include audit trails, intrusion detection methods, and checksums. Three other types of controls supplement preventive......

Words: 456 - Pages: 2

Team Development Measurement by Dynamic Fuzzy

...The 1st International Conference on Information Science and Engineering (ICISE2009) Team Development Measurement by Dynamic Fuzzy Social Network Analysis Lixin Zhou School of Software and Microelectronics, Peking University, 102600 zhoulx@vip.sina.com Abstract—How to obtain a high performing team quickly and effectively is very important in a project management. Communication is most essential part in a project team. In this paper, a method of measuring team performance by dynamic social network analysis is put forward. With dynamic fuzzy social network analysis, we can find the organizational structure of a team, the pattern of communication in a team. Then, the performance of a team can be analyzed by the organizational structure and communication pattern of a team. Keywords- fuzzy social network analysis, team development, measurement team development are described in section 2, in section 3, we describe social network in a project, in section 4, we describe how to build relationships and networks in project management team development; in section 5, we put forward the approach of fuzzy social network analysis; in section 6, the conclusion has been presented. II. STAGES IN PROJECT MANAGEMENT TEAM DEVELOPMENT I. INTRODUCTION Team development includes developing individual and group competencies to enhance project performance. By coming together as a true team, the project will be more successful. Team development can be achieved a variety of different......

Words: 1851 - Pages: 8

Optimum Thresholding Using Fuzzy Techniques

...Dissertation Phase-I: Synopsis Topic: OPTIMUM THRESHOLDING USING FUZZY TECHNIQUES Guided by- Presented by- Mr.Puneet Manocha Anupama (Roll No.1600872) Assit. Professor IIIrd Semester, M.Tech (ICE) OBJECTIVE: * To review different research papers based on Fuzzy Thresholding. * To apply fuzzy thresholding technique to an image * To calculate optimum threshold using Gamma membership function. LITERATURE REVIEW: Introduction: Typical computer vision applications usually require an image segmentation-preprocessing algorithm as a first procedure. At the output of this stage, each object of the image, represented by a set of pixels, is isolated from the rest of the scene. The purpose of this step is that objects and background are separated into non-overlapping sets. There are various techniques of segmentation and among them threshold is much simpler than other segmentation techniques. Usually, this segmentation process is based on the image gray-level histogram. In that case, the aim is to find a critical value or threshold. Through this threshold, applied to the whole image, pixels whose gray levels exceed this critical value are assigned to one set and the rest to the other. For a well-defined image, its histogram has a deep valley between two peaks. Around these peaks the object and......

Words: 2221 - Pages: 9

Fuzzy Hugs

...Penelope Ramirez BUS 230 Bill Forte June 2, 2013 Fuzzy Hugs Maintaining a high-quality, low-cost strategy is a philosophy many companies try to pursue in today’s competitive market. Not everyone can achieve that without hard work, massive time and other resources dedicated to ensure methods. Keeping a diverse work force is what we strive for. It allows employees from different backgrounds, different educational and occupational experience to collaborate and reach common goals. Adverse impact and validity are among the topics in this analysis; as follows. Effectively using information to make business decisions is vital to a company’s success. Analyzing data can help organizations determine if they have a high quality and talented workforce that can perform, meet objectives, and implement strategy. Successful data analysis can also help with hiring, training, and planning decisions. Yet, this same information can be used for decisions on down-sizing, and layoffs. It is important and fundamental to have measurements t assist in making decisions. The problem we face is deciding between two assessment systems, both of which are relatively expensive. As Fuzzy Hugs pursuing and maintaining a high quality low cost strategy is the business model. Furthermore, underperforming manufacturing employees cannot be afforded to be employed given the lean staffing model. The first system brought forth by Fuzzy Hugs has high validity and predicts job success well, but it results in......

Words: 928 - Pages: 4


...Lógica Fuzzi Americana – 2014 Resumo Considerando os problemas reais que cercam a sociedade hoje tanto nas indústrias, no comércio ou mesmo no dia a dia das pessoas, fica claro a ausência de certezas absolutas quanto a alguns aspectos. Heisenberg em 1927 já falava sobre o princípio da incerteza que serviu como alicerce principal da teoria quântica. Este princípio mais tarde iria auxiliar no desenvolvimento da lógica fuzzy, onde sua forma de raciocinar é muito semelhante ao modelo de raciocínio humano, baseado em aproximações e cercado de incertezas e suposições. Esses algoritmos são amplamente utilizados atualmente em diversas áreas como: robótica, automação de linhas de produção, simulações financeiras entre outras. O sistema lógico apresentado pela lógica fuzzy quando aplicado vai além do raciocínio booleano, pois busca atribuir graus para os elementos em questão de forma que a resposta contido ou não contido somente, não satisfaz e busca-se saber o quão contido ou o quão não contido esta determinado elemento. Sumário Introdução...................................................................................................................................1 O que é Lógica Fuzzi..................................................................................................................2 Raciocínio Dedutivo...................................................................................................................4 Raciocínio Indedutivo.............

Words: 1452 - Pages: 6

Fuzzy Math

...FUZZY MATH BUSINESS CASE Prof: Sandra Malach Student: Adam Fehr ID: 10115447 Joe Davis is a new hire and as such he has not figured out the exact inner workings of the company. With his limited experience he has already witnessed what he has thought to be a lack of ethical and accounting practices. Gallagher and MacDonald do not seem to care about their clients and are only focused on paying the lowest possible penalties to Symbol. Joe needs to decide if he should bypass both Gallagher and MacDonald and talk directly to the CEO about what he thinks is dishonest business dealings with Symbol. He has tried to get a neutral opinion by going to the company’s controller. The controller took a passive stance and was not helpful in regards to what direction Davis should take. This passive inaction made Davis question again what ethics this company has. With three of Davis’s contacts appearing to him as unethical and having poor accounting practices, Davis should talk directly to the CEO. He has already tried to bring the accounting errors to his superiors and has little success in them acknowledging the issue. Steve from Symbol has already let Davis know that there is an accounting issue. The client should not have to badger the company for its money which is owed to it. Symbol being their largest client, the utmost must be done to keep Symbol happy. Davis knows that ConnectCo owes Symbol money but is unsure how much based on ethics. By removing training days of ConnectCo’s...

Words: 730 - Pages: 3


...2 CONTINGENCY PLAN Control: The organization: a. Develops a contingency plan for the information system that: - Identifies essential missions and business functions and associated contingency requirements; - Provides recovery objectives, restoration priorities, and metrics; - Addresses contingency roles, responsibilities, assigned individuals with contact information; - Addresses maintaining essential missions and business functions despite an information system disruption, compromise, or failure; - Addresses eventual, full information system restoration without deterioration of the security measures originally planned and implemented; and - Is reviewed and approved by designated officials within the organization; b. Distributes copies of the contingency plan to [Assignment: organization-defined list of key contingency personnel (identified by name and/or by role) and organizational elements]; c. Coordinates contingency planning activities with incident handling activities; d. Reviews the contingency plan for the information system [Assignment: organization-defined frequency]; APPENDIX F-CP PAGE F-47 ________________________________________________________________________________________________ cial Publication 800-53 Recommended Security Controls for Federal Information Systems and Organizations e. Revises the contingency plan to address changes to the organization, information system, or environment of......

Words: 914 - Pages: 4

Control of Bldc Motor

...DESIGN OF FUZZY PID CONTROLLER FOR SPEED CONTROL OF BLDC MOTOR PHASE I REPORT Submitted by ARJUN M Register No. 710012428003 in partial fulfilment for the award of the degree of MASTER OF ENGINEERING in CONTROL AND INSTRUMENTATION DEPARTMENT OF ELECTRICAL AND ELECTRONICS ENGINEERING ANNA UNIVERSITY REGIONAL CENTRE, COIMBATORE COIMBATORE-641 047 DECEMBER 2013 ii ANNA UNIVERSITY REGIONAL CENTRE, COIMBATORE COIMBATORE-641 047 DEPARTMENT OF ELECTRICAL AND ELECTRONICS ENGINEERING PROJECT WORK PHASE I DECEMBER 2013 This is to certify that the project entitled DESIGN OF FUZZY PID CONTROLLER FOR SPEED CONTROL OF BLDC MOTOR is the bonafide record of project work done by ARJUN M Register No: - 710012428003 Of M.E. (CONTROL AND INSTRUMENTATION) during the year 2013-2014 Head of the Department Dr.S.N.DEEPA, M.E., Ph.D., Project Guide Mr.P.HARI KRISHNAN, M.E., Submitted for the Project Viva-Voce examination held on Internal Examiner External Examiner iii DECLARATION I affirm that the project titled DESIGN OF FUZZY PID CONTROLLER FOR SPEED CONTROL OF BLDC MOTOR being submitted in partial fulfilment for the award of Master of Engineering (M.E.) in Control and Instrumentation is the original work carried out by me. It has not formed the part of any other project work submitted for award of any degree or diploma, either in this or any other University. Signature of the Candidate ARJUN M Register......

Words: 7692 - Pages: 31

Ebusiness-Process-Personalization Using Neuro-Fuzzy Adaptive Control for Interactive Systems

...International Review of Business Research Papers Vol.2. No.4. December 2006, Pp. 39-50 eBusiness-Process-Personalization using Neuro-Fuzzy Adaptive Control for Interactive Systems Zunaira Munir1 , Nie Gui Hua2 , Adeel Talib3 and Mudassir Ilyas4 ‘Personalization’, which was earlier recognized as the 5th ‘P’ of e-marketing , is now becoming a strategic success factor in the present customer-centric e-business environment. This paper proposes two changes in the current structure of personalization efforts in ebusinesses. Firstly, a move towards business-process personalization instead of only website-content personalization and secondly use of an interactive adaptive scheme instead of the commonly employed algorithmic filtering approaches. These can be achieved by applying a neuro-intelligence model to web based real time interactive systems and by integrating it with converging internal and external e-business processes. This paper presents a framework, showing how it is possible to personalize e-business processes by adapting the interactive system to customer preferences. The proposed model applies Neuro-Fuzzy Adaptive Control for Interactive Systems (NFACIS) model to converging business processes to get the desired results. Field of Research: Marketing, e-business 1. Introduction: As Kasanoff (2001) mentioned, the ability to treat different people differently is the most fundamental form of human intelligence. "You talk differently to your boss than......

Words: 4114 - Pages: 17


...that Ms. Benson is ineffective in leading her section * Had lost the respect of the personnel manager and that she can’t control the employees in her section b. Benefits section * Handles employee insurance, life insurance, retirement benefits, educational benefits, and worker compensation claims * It is composed of six (6) employees who have worked together for the past five (5) years and who have become a very close-knit cohesive group (strong task structure) who cooperate well with other city employees * Has an excellent reputation based on the few complaints it receives on how it handles employee benefits c. Sharon Garcia * The informal leader of the benefits section whom other employees look up for advice and assistance * As an informal leader, she has both power and influence, though she has no authority * Told other employees that Ms Benson did not understand the new procedures during the training session on the new procedures for processing health insurance claims * Advised the other employees not to follow Ms. Benson’s instructions d. Other employees of the benefits section * Agreed to Ms Garcia’s advise and ignored the new procedures described by Ms. Benson e. Bill Castro * An employee of the section who complained to the city personnel manager that Ms. Benson could not control the operation of the section * Suggested that Ms. Benson should be removed as supervisor and that the employees wanted......

Words: 2438 - Pages: 10

A Fuzzy Expert System for Task Distribution

...A Fuzzy Expert System for Task Distribution in Teams under Unbalanced Workload Conditions José A. Benito Calleja and Jimmy Troost Thales Nederland, Hengelo, The Netherlands jose.benito@nl.thalesgroup.com, jimmy.troost@nl.thalesgroup.com Abstract Inappropriate workload levels on the team members of a naval force have been detected as a problem that can threaten the performance and safety of future naval operations. A suitable distribution of tasks among the members of a team is a crucial issue in order to prevent high and low workload levels. In this paper, we propose a rule-based expert system, the Task Distribution Expert System (TDES), which assists team leaders to manage mental workload in a team by suggesting appropriate task assignments. The TDES emulates the behavior of a team leader deciding which member of the team should perform a task and how. The system handles mental workload as an uncertain fuzzy concept comprising three fuzzy variables that represent the way mental workload affects performance. Automation issues and different recommendations for effective workload management in teams are analyzed and incorporated. A prototype demonstrates the system. 1. Introduction Naval Command and Control (C2) systems support organizations formed by a number of people cooperating on a multitude of tasks simultaneously to achieve overall goals. Future naval C2 systems are characterized by less people, more information available, shorter......

Words: 5411 - Pages: 22

Spirit Riding Free: Season 5 | saison 17, épisode 2 - Épisode 2 | Baby Girls TIGHTS PLAIN Opaque Microfibre 40 DEN Size 6 M - 13 Y