Fuzzy controllers

Xem 1-20 trên 50 kết quả Fuzzy controllers
  • Fuzzy control is a practical alternative for a variety of challenging control applications since it provides a convenient method for constructing nonlinear controllers via the use of heuristic information. Such heuristic information may come from an operator who has acted as a “human-in-the-loop” controller for a process. In the fuzzy control design methodology, we ask this operator to write down a set of rules on how to control the process, then we incorporate these into a fuzzy controller that emulates the decision-making process of the human.

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  • Fuzzy control theory is an emerging area of research. At the core of many engineering problems is the problem of control of different systems. These systems range all the way from classical inverted pendulum to auto-focusing system of a digital camera. Fuzzy control systems have demonstrated their enhanced performance in all these areas.

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  • Trying to meet the requirements in the field, present book treats different fuzzy control architectures both in terms of the theoretical design and in terms of comparative validation studies in various applications, numerically simulated or experimentally developed. Through the subject matter and through the inter and multidisciplinary content, this book is addressed mainly to the researchers, doctoral students and students interested in developing new applications of intelligent control, but also to the people who want to become familiar with the control concepts based on fuzzy techniques....

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  • Design of a fuzzy controller requires more design decisions than usual, for example regarding rule base, inference engine, defuzzification, and data pre- and post processing. This tutorial paper identifies and describes the design choices related to single-loop fuzzy control, based on an international standard which is underway.

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  • Tham khảo tài liệu 'fuzzy control- phần 2', công nghệ thông tin, kỹ thuật lập trình phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả

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  • Neuro-Fuzzy Control of a Robotic Exoskeleton With EMG Signals Kazuo Kiguchi, Member, IEEE, Takakazu Tanaka, and Toshio Fukuda, Fellow, IEEE Abstract—We have been developing robotic exoskeletons to assist motion of physically weak persons such as elderly, disabled, and injured persons. The robotic exoskeleton is controlled basically based on the electromyogram (EMG) signals, since the EMG signals of human muscles are important signals to understand how the user intends to move.

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  • Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article Fairness and QoS Guarantees of WiMAX OFDMA Scheduling with Fuzzy Controls

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  • In [5], we have offered the neccesary conditions of Sheaf-Optimal Control Problem in Fyzzy type (SOFCP), that means the controls u (t) ∈ U ⊂ E p not belong to R p . This paper shows some comparison of sheaf-solutions H t,u and H t,u for many kinds of fuzzy controls u (t), u(t) ∈ U ⊂ E p in Sheaf Fuzzy Control...

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  • Tham khảo sách 'neuro fuzzy control of a robotic exoskeleton with emg signals transactions on fuzzy systems, vol. 12', kỹ thuật - công nghệ, cơ khí - chế tạo máy phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả

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  • Despite the great technological advancement experienced in recent years, Programmable Logic Controllers (PLC) are still used in many applications from the real world and still play a central role in infrastructure of industrial automation. PLC operate in the factory-floor level and are responsible typically for implementing logical control, regulatory control strategies, such as PID and fuzzy-based algorithms, and safety logics. Usually PLC are interconnected with the supervision level through communication network, such as Ethernet networks, in order to work in an integrated form....

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  • Evolution of global technologies has prompted increasing complexity of applications developed in both, the industry and the scientific research fields. These complexities are generally attributed to nonlinearities, poorly defined dynamics and absence of apriori information about the systems. Imprecision, uncertainties and vagueness in information about the system are also playing vital roles in enhancing the complexity of application.

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  • This book introduces new concepts and theories of Fuzzy Logic Control for the application and development of robotics and intelligent machines. The book consists of nineteen chapters categorized into 1) Robotics and Electrical Machines 2) Intelligent Control Systems with various applications, and 3) New Fuzzy Logic Concepts and Theories. The intended readers of this book are engineers, researchers, and graduate students interested in fuzzy logic control systems.

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  • Since the idea of the fuzzy set was proposed in 1965, many developments have occurred in this area. Applications have been made in such diverse areas as medicine, engineering, management, behavioral science, just to mention some. The application of the fuzzy sets involves different technologies, such as fuzzy clustering on image processing, classification, identification and fault detection, fuzzy controllers to map expert knowledge into control systems, fuzzy modeling combining expert knowledge, fuzzy optimization to solve design problems....

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  • Giới thiệu về Logic mờ - Các khải niệm cơ bản về Logic Mờ - Bộ điều khiển Mờ ( Fuzzy Control) 3.1.Giới thiệu về logic Mờ (Fuzzy Logic) Khái niệm về logic mờ được giáo sư L.A Zadeh công bố lần đầu tiên tại Mỹ năm 1965, tại trường đại học Berkelay, bang Califormia, Mỹ. Từ đó lý thuyết mờ đã có nhiều phát triển và được ứng dụng rộng rãi trong lĩnh vực điều khiển- tự động hóa.

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  • Bài viết này giới thiệu về nguyên lý hoạt động của bộ điều khiển logic mờ và ứng dụng cụ thể của nó trong máy lái tự động tàu thuỷ. Máy lái tự động này được lập trình trong Matlab và được lắp đặt, chạy thử nghiệm trên tàu mô hình tỉ lệ 1:24 của một tàu VLCC. Các kết quả thực nghiệm, chi tiết của máy lái được nêu trong bài viết này. Abstract: This paper introduces the overview of fuzzy logic controller and its application in a ship’s autopilot.

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  • A hybrid neural fuzzy system is proposed to monitor both process mean and variance shifts simultaneously.

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  • In industrial automation, fuzzy logic technologies enable the efficient and transparent implementation of human control expertise.

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  • A CONTROL ENGINEERING APPROACH TO FUZZY CONTROL This book gives a comprehensive treatment of model-based fuzzy control systems. The central subject of this book is a systematic framework for the stability and design of nonlinear fuzzy control systems. Building on the so-called Takagi-Sugeno fuzzy model, a number of most important issues in fuzzy control systems are addressed. These include stability analysis, systematic design procedures, incorporation of performance specifications, robustness, optimality, numerical implementations, and last but not the least, applications. ...

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  • Artificial Intelligence (AI) is often referred to as a branch of science which deals with helping machines find solutions to complex problems in a more human-like fashion. It is generally associated with Computer Science, but it has many important links with other fields such as Maths, Psychology, Cognition, Biology and Philosophy. The AI success is due to its technology has diffused into everyday life. Neural networks, fuzzy controls, decision trees and rule-based systems are already in our mobile phones, washing machines and business applications....

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  • 24 Intelligent Soft-Computing Techniques in Robotics 24.1 24.2 Introduction Connectionist Approach in Robotics Basic Concepts • Connectionist Models with Applications in Robotics • Learning Principles and Rules 24.3 Neural Network Issues in Robotics Kinematic Robot Learning by Neural Networks • Dynamic Robot Learning at the Executive Control Level • Sensor-Based Robot Learning 24.4 Dustic M.

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