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Radial Basis Function Rbf Neural Network Control For Mechanical Systems

Author: Jinkun Liu
Publisher: Springer Science & Business Media
ISBN: 3642348165
Size: 42.37 MB
Format: PDF, Mobi
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Radial Basis Function (RBF) Neural Network Control for Mechanical Systems is motivated by the need for systematic design approaches to stable adaptive control system design using neural network approximation-based techniques. The main objectives of the book are to introduce the concrete design methods and MATLAB simulation of stable adaptive RBF neural control strategies. In this book, a broad range of implementable neural network control design methods for mechanical systems are presented, such as robot manipulators, inverted pendulums, single link flexible joint robots, motors, etc. Advanced neural network controller design methods and their stability analysis are explored. The book provides readers with the fundamentals of neural network control system design. This book is intended for the researchers in the fields of neural adaptive control, mechanical systems, Matlab simulation, engineering design, robotics and automation. Jinkun Liu is a professor at Beijing University of Aeronautics and Astronautics.

Radial Basis Function Rbf Neural Network Control For Mechanical Systems

Author: Jinkun Liu
Publisher: Springer
ISBN: 9783642434556
Size: 42.27 MB
Format: PDF, Docs
View: 2592
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Radial Basis Function (RBF) Neural Network Control for Mechanical Systems is motivated by the need for systematic design approaches to stable adaptive control system design using neural network approximation-based techniques. The main objectives of the book are to introduce the concrete design methods and MATLAB simulation of stable adaptive RBF neural control strategies. In this book, a broad range of implementable neural network control design methods for mechanical systems are presented, such as robot manipulators, inverted pendulums, single link flexible joint robots, motors, etc. Advanced neural network controller design methods and their stability analysis are explored. The book provides readers with the fundamentals of neural network control system design. This book is intended for the researchers in the fields of neural adaptive control, mechanical systems, Matlab simulation, engineering design, robotics and automation. Jinkun Liu is a professor at Beijing University of Aeronautics and Astronautics.

Sliding Mode Control Using Matlab

Author: Jinkun Liu
Publisher: Academic Press
ISBN: 0128026707
Size: 38.79 MB
Format: PDF, Docs
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Sliding Mode Control Using MATLAB provides many sliding mode controller design examples, along with simulation examples and MATLAB® programs. Following the review of sliding mode control, the book includes sliding mode control for continuous systems, robust adaptive sliding mode control, sliding mode control for underactuated systems, backstepping, and dynamic surface sliding mode control, sliding mode control based on filter and observer, sliding mode control for discrete systems, fuzzy sliding mode control, neural network sliding mode control, and sliding mode control for robot manipulators. The contents of each chapter are independent, providing readers with information they can use for their own needs. It is suitable for the readers who work on mechanical and electronic engineering, electrical automation engineering, etc., and can also be used as a teaching reference for universities. Provides many sliding mode controller design examples to help readers solve their research and design problems Includes various, implementable, robust sliding mode control design solutions from engineering applications Provides the simulation examples and MATLAB programs for each sliding mode control algorithm

Advanced Sliding Mode Control For Mechanical Systems

Author: Jinkun Liu
Publisher: Springer Science & Business Media
ISBN: 3642209076
Size: 10.88 MB
Format: PDF
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"Advanced Sliding Mode Control for Mechanical Systems: Design, Analysis and MATLAB Simulation" takes readers through the basic concepts, covering the most recent research in sliding mode control. The book is written from the perspective of practical engineering and examines numerous classical sliding mode controllers, including continuous time sliding mode control, discrete time sliding mode control, fuzzy sliding mode control, neural sliding mode control, backstepping sliding mode control, dynamic sliding mode control, sliding mode control based on observer, terminal sliding mode control, sliding mode control for robot manipulators, and sliding mode control for aircraft. This book is intended for engineers and researchers working in the field of control. Dr. Jinkun Liu works at Beijing University of Aeronautics and Astronautics and Dr. Xinhua Wang works at the National University of Singapore.

Intelligent Control Design And Matlab Simulation

Author: Jinkun Liu
Publisher: Springer
ISBN: 9811052638
Size: 18.59 MB
Format: PDF
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This book offers a comprehensive introduction to intelligent control system design, using MATLAB simulation to verify typical intelligent controller designs. It also uses real-world case studies that present the results of intelligent controller implementations to illustrate the successful application of the theory. Addressing the need for systematic design approaches to intelligent control system design using neural network and fuzzy-based techniques, the book introduces the concrete design method and MATLAB simulation of intelligent control strategies; offers a catalog of implementable intelligent control design methods for engineering applications; provides advanced intelligent controller design methods and their stability analysis methods; and presents a sample simulation and Matlab program for each intelligent control algorithm. The main topics addressed are expert control, fuzzy logic control, adaptive fuzzy control, neural network control, adaptive neural control and intelligent optimization algorithms, providing several engineering application examples for each method.

Adaptive Systems In Control And Signal Processing 1995

Author: Cs. Banyasz
Publisher: Elsevier
ISBN: 148329689X
Size: 42.60 MB
Format: PDF, Kindle
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Leading academic and industrial researchers working with adaptive systems and signal processing have been given the opportunity to exchange ideas, concepts and solutions at the IFAC Symposia on Adaptive Systems in Control and Signal Processing. This postprint volume contains all those papers which were presented at the 5th IFAC Symposium in Budapest in 1995. The technical program was composed of a number of invited and contributed sessions and a special case study session, providing a good balance between applications and theory oriented papers.

Design And Modeling Of Mechanical Systems

Author: Mohamed Haddar
Publisher: Springer Science & Business Media
ISBN: 3642371434
Size: 38.63 MB
Format: PDF, ePub, Docs
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The 5th International Congress on Design and Modeling of Mechanical Systems (CMSM) was held in Djerba, Tunisia on March 25-27, 2013 and followed four previous successful editions, which brought together international experts in the fields of design and modeling of mechanical systems, thus contributing to the exchange of information and skills and leading to a considerable progress in research among the participating teams. The fifth edition of the congress (CMSM ́2013), organized by the Unit of Mechanics, Modeling and Manufacturing (U2MP) of the National School of Engineers of Sfax, Tunisia, the Mechanical Engineering Laboratory (MBL) of the National School of Engineers of Monastir, Tunisia and the Mechanics Laboratory of Sousse (LMS) of the National School of Engineers of Sousse, Tunisia, saw a significant increase of the international participation. This edition brought together nearly 300 attendees who exposed their work on the following topics: mechatronics and robotics, dynamics of mechanical systems, fluid structure interaction and vibroacoustics, modeling and analysis of materials and structures, design and manufacturing of mechanical systems. This book is the proceedings of CMSM ́2013 and contains a careful selection of high quality contributions, which were exposed during various sessions of the congress. The original articles presented here provide an overview of recent research advancements accomplished in the field mechanical engineering.

Data Mining And Machine Learning In Building Energy Analysis

Author: Frédéric Magoules
Publisher: John Wiley & Sons
ISBN: 1118577590
Size: 51.84 MB
Format: PDF
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Focusing on up-to-date artificial intelligence models to solve building energy problems, Artificial Intelligence for Building Energy Analysis reviews recently developed models for solving these issues, including detailed and simplified engineering methods, statistical methods, and artificial intelligence methods. The text also simulates energy consumption profiles for single and multiple buildings. Based on these datasets, Support Vector Machine (SVM) models are trained and tested to do the prediction. Suitable for novice, intermediate, and advanced readers, this is a vital resource for building designers, engineers, and students.

Neural Network Design 2nd Edition

Author: Martin Hagan
Publisher:
ISBN: 9780971732117
Size: 61.73 MB
Format: PDF, Mobi
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This book provides a clear and detailed coverage of fundamental neural network architectures and learning rules. In it, the authors emphasize a coherent presentation of the principal neural networks, methods for training them and their applications to practical problems.