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After an introductory chapter explaining recent applications of fuzzy sets in IE, this book explores the seven major areas of IE to which fuzzy set theory can contribute: Control and Reliability, Engineering Economics and Investment Analysis, Group and Multi-criteria Decision-making, Human Factors Engineering and Ergonomics, Manufacturing Systems and Technology Management, Optimization Techniques, and Statistical Decision-making. Under these major areas, every chapter includes didactic numerical applications.
Provides an up-to-date integration of expert systems with fuzzy logic and neural networks. Includes coverage of simulation models not present in other books. Presents cases and examples taken from the authors' experience in research and applying the technology to real-world situations.
This book introduces a dynamic, on-line fuzzy inference system. In this system membership functions and control rules are not determined until the system is applied and each output of its lookup table is calculated based on current inputs. The book describes the real-world uses of new fuzzy techniques to simplify readers’ tuning processes and enhance the performance of their control systems. It further contains application examples.
Fuzzy control methods are critical for meeting the demands of complex nonlinear systems. They bestow robust, adaptive, and self-correcting character to complex systems that demand high stability and functionality beyond the capabilities of traditional methods. A thorough treatise on the theory of fuzzy logic control is out of place on the design bench. That is why Fuzzy Controller Design: Theory and Applications offers laboratory- and industry-tested algorithms, techniques, and formulations of real-world problems for immediate implementation. With surgical precision, the authors carefully select the fundamental elements of fuzzy logic control theory necessary to formulate effective and efficient designs. The book supplies a springboard of knowledge, punctuated with examples worked out in MATLAB®/SIMULINK®, from which newcomers to the field can dive directly into applications. It systematically covers the design of hybrid, adaptive, and self-learning fuzzy control structures along with strategies for fuzzy controller design suitable for on-line and off-line operation. Examples occupy an entire chapter, with a section devoted to the simulation of an electro-hydraulic servo system. The final chapter explores industrial applications with emphasis on techniques for fuzzy controller implementation and different implementation platforms for various applications. With proven methods based on more than a decade of experience, Fuzzy Controller Design: Theory and Applications is a concise guide to the methodology, design steps, and formulations for effective control solutions.
The application of fuzzy technology is widely known as a technological revolution. Shortly after it appeared, its value has rapidly become appreciated. It is absolutely indispensable for introducing the latest developments not only domestically but also internationally. This book is arranged to introduce easy to understand explanations mainly centered on concrete applications. It consists of twelve chapters in total which are all independently readable and provide different approaches on various projects. The minimum of Fuzzy Theory that is needed to understand its practical applications is given in Chapter 1. Chapters 2 to 5 discuss hardware, including chips, and software tools used in constructing system. Chapters 6 to 12 cover a series of practical applications. These in clude applications for industrial processes and plants, transportation systems, which were among the first applications, and applications for consumer products such as household electrical appliances. These elements together finally produced the worldwide "Fuzzy Boom". This book can be read by a wide variety of people, from undergraduate and graduate students in universities to practical engineers and project managers working in plants. The information contained in this book is a first step to this field of interest.
Fuzzy logic allows computer programmers to interpret ambiguous commands that ordinary, rigid programs are unable to decipher. For instance, computers can work with words like "tall" and "expensive" rather than 6'5" or $669.95. This book covers the use of fuzzy logic in the information science and information engineering fields.
Introduction to fuzzy logic control. History of industrial applications of fuzzy logic in Japan. Fuzzy logic applications at OMRON Corporation. Survey of fuzzy logic applications in image-processing equipment. Applications of neural networks and fuzzy logic to consumer products. Knowledge processing based on fuzzy associative memory and its application to a helicopter control. Fuzzy logic hierarchical controller for a recuperative turboshaft engine: from mode selection to mode melding. Progress in reseacrh on autonomous vehicle motion planning. Autonomous navigation of a mobile robot using the behaviorist theory and VLSI fuzzy inferencing chips. Artificial intelligence, fuzzy logic, and sensor clusters. Intelligent sensor systems for space operations. Two automated tuning methods for fuzzy logic-based process control. On fuzzy control of nonchlorofluorocarbon air-conditioning systems. Fuzzy logic applications in Europe. Software tools for fuzzy control.
This volume gathers the latest advances, innovations, and applications in the field of robotics engineering, as presented by leading international researchers and engineers at the Latin American Symposium on Industrial and Robotic Systems (LASIRS), held in Tampico, Mexico on October-November 30-01 2019. The contributions cover all major areas of R&D and innovation in simulation, optimization, and control of robotics, such as design and optimization of robots using numerical and metaheuristic methods, autonomous and control systems, industrial compliance solutions, numerical simulations for manipulators and robots, metaheuristics applied to robotics problems, Industry 4.0, control and automation in petrochemical processes, simulation and control in aerospace and aeronautics, and education in robotics. The conference represented a unique platform to share the latest research and developments in simulation, control and optimization of robotic systems, and to promote cooperation among specialists in machine and mechanism area.
Fuzzy logic refers to a set of methods used to characterize and quantify uncertainty in engineering systems. This edition covers major advances that have been made with regard to both theory and applications.