Fuzzy controllers

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  • 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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  • Results obtained from the study of dynamic model over drying process using fuzzy control system for grain moisture reduction have brought prospects to drying technology to increase dried products quality and its economic effectiveness in the area of storage and processing of agro-products.

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  • It is designed and simulated by using Matlab/Simulink. Then, it is applied to control a real magnetic levitation system in the laboratory. The fuzzy controller makes the system stable with high performances in comparison to that of PI controller. Its fuzzy rules are based on the experience obtained from the simulation and there is no usage of mathematical model of the real magnetic levitation system.

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  • The study proposes an intelligent lower extremity rehabilitation training system controlled by adaptive fuzzy controllers (AFCs) and impedance controllers (ICs). The structure of the robotic leg exoskeleton can be divided into three parts including hip joint, knee joint, and ankle joint, which are driven by linear actuators and pulleys. Therefore, the movement of the robotic leg exoskeleton can be controlled by driving the linear actuators. The results of simulation reveal that the design of the proposed controllers presents good performances and effectiveness.

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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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  • 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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  • 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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  • Bài viết Điều khiển trượt cho đối tượng con lắc ngược có liên kết đàn hồi sử dụng đại số gia tử nghiên cứu 2 bộ điều khiển cho đối tượng “con lắc ngược có liên kết đàn hồi – cản nhớt chịu tải chu kỳ” đó là điều khiển mờ trượt sử dụng logic mờ (Sliding Mode Fuzzy Controller – SMFC) và điều khiển mờ trượt sử dụng đại số gia tử (Sliding Mode Hedge-Algebras Controller – SMHAC).

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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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  • Research objectives: Studying and evaluation of active queue management mechanisms to find out the advantages and disadvantages of each mechanism, in order to classify and evaluate application performance for mechanisms and using fuzzy logic to improve active queue management mechanism; the results of the first goals is to perform study motivation first and will be the foundation for the theory and simulation improvements of the thesis.

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  • This paper presents the results of an experimental system design for the optimization of parallel manipulator control based on an optimal configuration. The experimental system is an open design for various different configurations and controllers to support parallel manipulator research and applications.

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  • This paper presents a solution for optimizing controlled release product formulation using a combination of AI techniques (Soft-Computing): neural networks, fuzzy logic and genetic algorithms. This achievement will help to significantly reduce time and labour in R&D process thank to its good accuracy and high processing speed. The results obtained from this research indicate that the alternative approach can be considered as an effective and efficient method for modelling and optimising controlled release formulations.

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