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Author: Patricia Melin Publisher: Springer Science & Business Media ISBN: 3540729178 Category : Business & Economics Languages : en Pages : 836
Book Description
This book comprises a selection of papers from IFSA 2007 on new methods and theories that contribute to the foundations of fuzzy logic and soft computing. Coverage includes the application of fuzzy logic and soft computing in flexible querying, philosophical and human-scientific aspects of soft computing, search engine and information processing and retrieval, as well as intelligent agents and knowledge ant colony.
Author: Patricia Melin Publisher: Springer Science & Business Media ISBN: 3540729178 Category : Business & Economics Languages : en Pages : 836
Book Description
This book comprises a selection of papers from IFSA 2007 on new methods and theories that contribute to the foundations of fuzzy logic and soft computing. Coverage includes the application of fuzzy logic and soft computing in flexible querying, philosophical and human-scientific aspects of soft computing, search engine and information processing and retrieval, as well as intelligent agents and knowledge ant colony.
Author: Witold Pedrycz Publisher: Springer Science & Business Media ISBN: 1461313651 Category : Mathematics Languages : en Pages : 399
Book Description
Fuzzy Modelling: Paradigms and Practice provides an up-to-date and authoritative compendium of fuzzy models, identification algorithms and applications. Chapters in this book have been written by the leading scholars and researchers in their respective subject areas. Several of these chapters include both theoretical material and applications. The editor of this volume has organized and edited the chapters into a coherent and uniform framework. The objective of this book is to provide researchers and practitioners involved in the development of models for complex systems with an understanding of fuzzy modelling, and an appreciation of what makes these models unique. The chapters are organized into three major parts covering relational models, fuzzy neural networks and rule-based models. The material on relational models includes theory along with a large number of implemented case studies, including some on speech recognition, prediction, and ecological systems. The part on fuzzy neural networks covers some fundamentals, such as neurocomputing, fuzzy neurocomputing, etc., identifies the nature of the relationship that exists between fuzzy systems and neural networks, and includes extensive coverage of their architectures. The last part addresses the main design principles governing the development of rule-based models. Fuzzy Modelling: Paradigms and Practice provides a wealth of specific fuzzy modelling paradigms, algorithms and tools used in systems modelling. Also included is a panoply of case studies from various computer, engineering and science disciplines. This should be a primary reference work for researchers and practitioners developing models of complex systems.
Author: Hasan Palaz Publisher: ISBN: Category : Languages : tr Pages :
Book Description
The main characteristics of Neural Network (NN) are to recognize patterns and to classify input, and to adapt themselves to dynamic environments by Iearning,but the mapping structure of NN in the intelligent controllers is a black box. it ispossible to understand what the box does, but not how it is done conceptually. In theother words, the resulting NN behavior in the control scheme is difficult tounderstand. In addition, Fuzzy Logic (FL) can cope with human knowledge and canperform inference, but FL does not fundamentally include Iearning mechanism.Neuro-fuzzy computing has developed for overcoming their disadvantages. Ingeneral, the NN part is used for Iearning, while fuzzy Iogic part is used forrepresenting knowledge. Adaptive Neuro-Fuzzy Inference Systems (ANFIS) hasgreatly improved the realization performance of fuzzy system and has extensively been used for identification and control purposes.it is seen that the Variable Structure Control (VSC), NN and FL methodologies are complementary for control objectives and there can be much tobe gained in using them in a combined manner for the control of nonlinear systems.The resulting controller is a nonlinear one and may be suitable to overcome the difficulties involved in using conventional VSC for nonlinear systems. As the application area of neuro-fuzzy control expands from simple systems (in the sense that there are only a few key variables, and that Iarge number of trial-and-error experiments are permitted, Iike in washing machine, air conditioners, rice cookers,etc.) to more complex systems (in the sense that there are many key variables, and that unsuccessful trial-and-error experiments are not permitted, Iike in chemical processes, power plants, robotic systems, aircrafts, etc.), there is a urgent need for systematic design method of the neuro-fuzzy VSC systems which have the following properties,1. They alleviate the chattering phenomena while maintaining sliding behaviorwith accurate tracking performance,2. They have a self organizing capability that can start from an empty rule base,3. They produce an on-line controller that means the control and Iearning take splace simultaneously 4. They have a high degree robustness and fault tolerance,5. They are stable neuro-fuzzy control system,6. They introduce structured fuzzy concept that is easy to understand,7 .They visualize the evaluation of membership functions and the rule basesduring operation,8. They enable the designer to incorporate the experiences of control strategy into controller ,9. They have a self-tuning capability that can tune its parameters in on-line.The neuro-fuzzy approaches to VSC system in this doctoral dissertation tryto solve of this kind of problems. Roughly speaking, the following ideas areproposed. For the first five requirements, A Gaussian Neuro Fuzzy Variable Structure Control (GNFVSC) scheme is presented to tackle drawbacks ofconventional VSC. This controller consists of a Gaussian Radial Basis Function NN(RBFNN), which is considered as a smooth transition between FL and NN.For the first eight requirements, the adaptive neuro-fuzzy control system is introduced to estimate an equivalent control inside the boundary Iayer by incorporating Iinguistic control rules based on knowledge of the sliding surface variable into the controller .Finally , for the ninth requirement, a self tuning neuro-fuzzy V8C system is studied to eliminate fine tuning problem of the controller .
Author: Clarence W. de Silva Publisher: CRC Press ISBN: 1351437682 Category : Computers Languages : en Pages : 362
Book Description
The emergence of fuzzy logic and its applications has dramatically changed the face of industrial control engineering. Over the last two decades, fuzzy logic has allowed control engineers to meet and overcome the challenges of developing effective controllers for increasingly complex systems with poorly defined dynamics. Today's engineers need a working knowledge of the principles and techniques of fuzzy logic-Intelligent Control provides it. The author first introduces the traditional control techniques and contrasts them with intelligent control. He then presents several methods of representing and processing knowledge and introduces fuzzy logic as one such method. He highlights the advantages of fuzzy logic over other techniques, indicates its limitations, and describes in detail a hierarchical control structure appropriate for use in intelligent control systems. He introduces a variety of applications, most in the areas of robotics and mechatronics but with others including air conditioning and process/production control. One appendix provides discussion of some advanced analytical concepts of fuzzy logic, another describes a commercially available software system for developing fuzzy logic application. Intelligent Control is filled with worked examples, exercises, problems, and references. No prior knowledge of the subject nor advanced mathematics are needed to comprehend much of the book, making it well-suited as a senior undergraduate or first-year graduate text and a convenient reference tool for practicing professionals.
Author: Clarence W. DeSilva Publisher: Springer ISBN: Category : Computers Languages : en Pages : 214
Book Description
This monograph considers the integration of knowledge-based soft control with hard control algorithms. As a specific application, the development of a knowledge-based controller for robotic manipulators is addressed. Servo control alone is known to be inadequate for nonlinear and high-speed processes including robots. Furthermore, knowledge-based control such as fuzzy control, when directly included in the servo loop, has produced insatisfactory performance in research robots. These considerations, along with the fact that human experts can very effectively perform tuning functions in process controllers, form the basis for the control structure proposed in this work. The book is suitable for students, researchers and practising professionals in the fields of Automatic Control and Robotics. The material is presented in simple and clear language with sufficient introductory information. Someone with an undergraduate knowledge in dynamics and control should be able to use the book without any difficulty.
Author: Xiaoqing Ma Publisher: ISBN: Category : Fuzzy algorithms Languages : en Pages : 0
Book Description
Control of under-actuated mechanical systems (robots) represents an important class of control problem. This thesis studies several related control problems associated with an under-actuated robot, Pendubot, from the point view of fuzzy logic control. To swing up the Pendubot from a rest position to the upright configuration, a fuzzy algorithm is proposed from non-complete sets of linguistic rules that link some mechanism states to the sign of a single control action. Therein, a simplified Tsukamoto's reasoning method and quasi-linear-mean aggregating operators are used to derive and analyze the controller input-out mappings. In order to balance the Pendubot at the unstable upright top configuration after swinging up, another simple fuzzy controller is derived according to its joint states: This combining fuzzy algorithm for swinging-up and balancing is successfully applied to the Pendubot. This thesis also investigates the case that the Pendubot tracks a desired signal and a corresponding fuzzy scheme is proposed, which combines the linear regulator theory with the Takagi-Sugeno fuzzy methodology. The stability and stability conditions for this fuzzy scheme are analyzed. Numerical simulations for all the above controllers are carried out to validate the theoretical analysis by using SIMULINK. Finally, the hardware experiments in the Pendubot have successfully been conducted in the Robotics and Mechatronics Laboratory.
Author: Israa Taqa Publisher: LAP Lambert Academic Publishing ISBN: 9783659575785 Category : Languages : en Pages : 168
Book Description
The emergence of computational intelligence technology inspired by biological and human intelligence is one of the most exciting and important fields in engineering . It is expected that these technologies like fuzzy logic, will play a significant role in the development of intelligent robotic systems, machine systems, and mechatronics systems . In this work; a Fuzzy Logic Controller is presented to control the motion of a robotic arm and avoid the obstacles existed in its mission road, using a real platform robotic arm in combination with a vision system . This work involves constructing an integrated and autonomic MATLAB program. It could be applicable for any robotic arm . It depends on a new approach in analyzing the robotic environment videos acquired by a fixed webcam. The approach uses colors to detect and recognize the changeable locations and objects' dimensions for each of the robot's end-effector, the goal, and the obstacles .
Author: Patricia Melin
Author: Patricia Melin
Author: Seinz Ficici
Author: 
Author: Jimit Patel
Author: Witold Pedrycz
Author: Hasan Palaz
Author: Clarence W. de Silva
Author: Clarence W. DeSilva
Author: Xiaoqing Ma
Author: Israa Taqa