Stable Adaptive Neural Network Control

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Stable Adaptive Neural Network Control

Stable Adaptive Neural Network Control [Pdf/ePub] eBook ISBN-10: 1475765770
Author: S.S. Ge,C.C. Hang,T.H. Lee,Tao Zhang
Publisher: Springer Science & Business Media
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Stable Adaptive Neural Network Control by S.S. Ge,C.C. Hang,T.H. Lee,Tao Zhang Book Resume:

Recent years have seen a rapid development of neural network control tech niques and their successful applications. Numerous simulation studies and actual industrial implementations show that artificial neural network is a good candidate for function approximation and control system design in solving the control problems of complex nonlinear systems in the presence of different kinds of uncertainties. Many control approaches/methods, reporting inventions and control applications within the fields of adaptive control, neural control and fuzzy systems, have been published in various books, journals and conference proceedings. In spite of these remarkable advances in neural control field, due to the complexity of nonlinear systems, the present research on adaptive neural control is still focused on the development of fundamental methodologies. From a theoretical viewpoint, there is, in general, lack of a firmly mathematical basis in stability, robustness, and performance analysis of neural network adaptive control systems. This book is motivated by the need for systematic design approaches for stable adaptive control using approximation-based techniques. The main objec tives of the book are to develop stable adaptive neural control strategies, and to perform transient performance analysis of the resulted neural control systems analytically. Other linear-in-the-parameter function approximators can replace the linear-in-the-parameter neural networks in the controllers presented in the book without any difficulty, which include polynomials, splines, fuzzy systems, wavelet networks, among others. Stability is one of the most important issues being concerned if an adaptive neural network controller is to be used in practical applications.

Stable Adaptive Control and Estimation for Nonlinear Systems

Stable Adaptive Control and Estimation for Nonlinear Systems [Pdf/ePub] eBook ISBN-10: 0471460974
Author: Jeffrey T. Spooner,Manfredi Maggiore,Raúl Ordóñez,Kevin M. Passino
Publisher: John Wiley & Sons
File Size: 892 KB
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Stable Adaptive Control and Estimation for Nonlinear Systems by Jeffrey T. Spooner,Manfredi Maggiore,Raúl Ordóñez,Kevin M. Passino Book Resume:

Includes a solution manual for problems. Provides MATLAB code for examples and solutions. Deals with robust systems in both theory and practice.

Radial Basis Function (RBF) Neural Network Control for Mechanical Systems

Radial Basis Function (RBF) Neural Network Control for Mechanical Systems [Pdf/ePub] eBook ISBN-10: 3642348165
Author: Jinkun Liu
Publisher: Springer Science & Business Media
File Size: 1582 KB
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Radial Basis Function (RBF) Neural Network Control for Mechanical Systems by Jinkun Liu Book Resume:

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.

Advances in Neural Networks - ISNN 2007

Advances in Neural Networks - ISNN 2007 [Pdf/ePub] eBook ISBN-10: 3540723838
Author: Derong Liu,Shumin Fei,Zeng-Guang Hou,Huaguang Zhang,Changyin Sun
Publisher: Springer
File Size: 1931 KB
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Read Count: 1623309

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Advances in Neural Networks - ISNN 2007 by Derong Liu,Shumin Fei,Zeng-Guang Hou,Huaguang Zhang,Changyin Sun Book Resume:

This book is part of a three volume set that constitutes the refereed proceedings of the 4th International Symposium on Neural Networks, ISNN 2007, held in Nanjing, China in June 2007. Coverage includes neural networks for control applications, robotics, data mining and feature extraction, chaos and synchronization, support vector machines, fault diagnosis/detection, image/video processing, and applications of neural networks.

CONTROL SYSTEMS, ROBOTICS AND AUTOMATION – Volume XIII

CONTROL SYSTEMS, ROBOTICS AND AUTOMATION – Volume XIII [Pdf/ePub] eBook ISBN-10: 1848261527
Author: Heinz D. Unbehauen
Publisher: EOLSS Publications
File Size: 1181 KB
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CONTROL SYSTEMS, ROBOTICS AND AUTOMATION – Volume XIII by Heinz D. Unbehauen Book Resume:

This Encyclopedia of Control Systems, Robotics, and Automation is a component of the global Encyclopedia of Life Support Systems EOLSS, which is an integrated compendium of twenty one Encyclopedias. This 22-volume set contains 240 chapters, each of size 5000-30000 words, with perspectives, applications and extensive illustrations. It is the only publication of its kind carrying state-of-the-art knowledge in the fields of Control Systems, Robotics, and Automation and is aimed, by virtue of the several applications, at the following five major target audiences: University and College Students, Educators, Professional Practitioners, Research Personnel and Policy Analysts, Managers, and Decision Makers and NGOs.

Autonomous Mobile Robots

Autonomous Mobile Robots [Pdf/ePub] eBook ISBN-10: 1420019449
Author: Frank L. Lewis,Shuzhi Sam Ge
Publisher: CRC Press
File Size: 1514 KB
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Autonomous Mobile Robots by Frank L. Lewis,Shuzhi Sam Ge Book Resume:

It has long been the goal of engineers to develop tools that enhance our ability to do work, increase our quality of life, or perform tasks that are either beyond our ability, too hazardous, or too tedious to be left to human efforts. Autonomous mobile robots are the culmination of decades of research and development, and their potential is seemingly unlimited. Roadmap to the Future Serving as the first comprehensive reference on this interdisciplinary technology, Autonomous Mobile Robots: Sensing, Control, Decision Making, and Applications authoritatively addresses the theoretical, technical, and practical aspects of the field. The book examines in detail the key components that form an autonomous mobile robot, from sensors and sensor fusion to modeling and control, map building and path planning, and decision making and autonomy, and to the final integration of these components for diversified applications. Trusted Guidance A duo of accomplished experts leads a team of renowned international researchers and professionals who provide detailed technical reviews and the latest solutions to a variety of important problems. They share hard-won insight into the practical implementation and integration issues involved in developing autonomous and open robotic systems, along with in-depth examples, current and future applications, and extensive illustrations. For anyone involved in researching, designing, or deploying autonomous robotic systems, Autonomous Mobile Robots is the perfect resource.

Neural Network Control of Nonlinear Discrete-Time Systems

Neural Network Control of Nonlinear Discrete-Time Systems [Pdf/ePub] eBook ISBN-10: 1420015451
Author: Jagannathan Sarangapani
Publisher: CRC Press
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Neural Network Control of Nonlinear Discrete-Time Systems by Jagannathan Sarangapani Book Resume:

Intelligent systems are a hallmark of modern feedback control systems. But as these systems mature, we have come to expect higher levels of performance in speed and accuracy in the face of severe nonlinearities, disturbances, unforeseen dynamics, and unstructured uncertainties. Artificial neural networks offer a combination of adaptability, parallel processing, and learning capabilities that outperform other intelligent control methods in more complex systems. Borrowing from Biology Examining neurocontroller design in discrete-time for the first time, Neural Network Control of Nonlinear Discrete-Time Systems presents powerful modern control techniques based on the parallelism and adaptive capabilities of biological nervous systems. At every step, the author derives rigorous stability proofs and presents simulation examples to demonstrate the concepts. Progressive Development After an introduction to neural networks, dynamical systems, control of nonlinear systems, and feedback linearization, the book builds systematically from actuator nonlinearities and strict feedback in nonlinear systems to nonstrict feedback, system identification, model reference adaptive control, and novel optimal control using the Hamilton-Jacobi-Bellman formulation. The author concludes by developing a framework for implementing intelligent control in actual industrial systems using embedded hardware. Neural Network Control of Nonlinear Discrete-Time Systems fosters an understanding of neural network controllers and explains how to build them using detailed derivations, stability analysis, and computer simulations.

Algorithms—Advances in Research and Application: 2012 Edition

Algorithms—Advances in Research and Application: 2012 Edition [Pdf/ePub] eBook ISBN-10: 1464990611
Author: N.A
Publisher: ScholarlyEditions
File Size: 982 KB
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Algorithms—Advances in Research and Application: 2012 Edition by N.A Book Resume:

Algorithms—Advances in Research and Application: 2012 Edition is a ScholarlyEditions™ eBook that delivers timely, authoritative, and comprehensive information about Algorithms. The editors have built Algorithms—Advances in Research and Application: 2012 Edition on the vast information databases of ScholarlyNews.™ You can expect the information about Algorithms in this eBook to be deeper than what you can access anywhere else, as well as consistently reliable, authoritative, informed, and relevant. The content of Algorithms—Advances in Research and Application: 2012 Edition has been produced by the world’s leading scientists, engineers, analysts, research institutions, and companies. All of the content is from peer-reviewed sources, and all of it is written, assembled, and edited by the editors at ScholarlyEditions™ and available exclusively from us. You now have a source you can cite with authority, confidence, and credibility. More information is available at http://www.ScholarlyEditions.com/.

Stability Theory of Switched Dynamical Systems

Stability Theory of Switched Dynamical Systems [Pdf/ePub] eBook ISBN-10: 9780857292568
Author: Zhendong Sun,Shuzhi Sam Ge
Publisher: Springer Science & Business Media
File Size: 1082 KB
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Read Count: 1894503

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Stability Theory of Switched Dynamical Systems by Zhendong Sun,Shuzhi Sam Ge Book Resume:

There are plenty of challenging and interesting problems open for investigation in the field of switched systems. Stability issues help to generate many complex nonlinear dynamic behaviors within switched systems. The authors present a thorough investigation of stability effects on three broad classes of switching mechanism: arbitrary switching where stability represents robustness to unpredictable and undesirable perturbation, constrained switching, including random (within a known stochastic distribution), dwell-time (with a known minimum duration for each subsystem) and autonomously-generated (with a pre-assigned mechanism) switching; and designed switching in which a measurable and freely-assigned switching mechanism contributes to stability by acting as a control input. For each of these classes this book propounds: detailed stability analysis and/or design, related robustness and performance issues, connections to other control problems and many motivating and illustrative examples.

Functional Adaptive Control

Functional Adaptive Control [Pdf/ePub] eBook ISBN-10: 144710319X
Author: Simon G. Fabri,Visakan Kadirkamanathan
Publisher: Springer Science & Business Media
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Functional Adaptive Control by Simon G. Fabri,Visakan Kadirkamanathan Book Resume:

Unique in its systematic approach to stochastic systems, this book presents a wide range of techniques that lead to novel strategies for effecting intelligent control of complex systems that are typically characterised by uncertainty, nonlinear dynamics, component failure, unpredictable disturbances, multi-modality and high dimensional spaces.

Advances in Neural Networks - ISNN 2005

Advances in Neural Networks - ISNN 2005 [Pdf/ePub] eBook ISBN-10: 3540320652
Author: Jun Wang,Xiaofeng Liao,Zhang Yi
Publisher: Springer
File Size: 360 KB
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Advances in Neural Networks - ISNN 2005 by Jun Wang,Xiaofeng Liao,Zhang Yi Book Resume:

The three volume set LNCS 3496/3497/3498 constitutes the refereed proceedings of the Second International Symposium on Neural Networks, ISNN 2005, held in Chongqing, China in May/June 2005. The 483 revised papers presented were carefully reviewed and selected from 1.425 submissions. The papers are organized in topical sections on theoretical analysis, model design, learning methods, optimization methods, kernel methods, component analysis, pattern analysis, systems modeling, signal processing, image processing, financial analysis, control systems, robotic systems, telecommunication networks, incidence detection, fault diagnosis, power systems, biomedical applications, industrial applications, and other applications.

Advances in Neural Networks - ISNN 2006

Advances in Neural Networks - ISNN 2006 [Pdf/ePub] eBook ISBN-10: 3540344403
Author: Jun Wang,Zhang Yi,Jacek M. Zurada,Bao-Liang Lu,Yin Hujun
Publisher: Springer
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Advances in Neural Networks - ISNN 2006 by Jun Wang,Zhang Yi,Jacek M. Zurada,Bao-Liang Lu,Yin Hujun Book Resume:

This is Volume I of a three volume set constituting the refereed proceedings of the Third International Symposium on Neural Networks, ISNN 2006. 616 revised papers are organized in topical sections on neurobiological analysis, theoretical analysis, neurodynamic optimization, learning algorithms, model design, kernel methods, data preprocessing, pattern classification, computer vision, image and signal processing, system modeling, robotic systems, transportation systems, communication networks, information security, fault detection, financial analysis, bioinformatics, biomedical and industrial applications, and more.

Mechanical and Electronics Engineering III

Mechanical and Electronics Engineering III [Pdf/ePub] eBook ISBN-10: 3038137189
Author: Han Zhao
Publisher: Trans Tech Publications Ltd
File Size: 1748 KB
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Read Count: 4505839

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Mechanical and Electronics Engineering III by Han Zhao Book Resume:

Volume is indexed by Thomson Reuters CPCI-S (WoS). These peer-reviewed proceedings comprise the papers presented at a conference whose main theme was Mechanical and Electronics Engineering. The main goal of the event was to provide an international scientific forum for the exchange of new ideas in a number of fields and for in-depth interaction via discussions with peers from around the world. Core areas of Information and Network Technology, plus multidisciplinary, interdisciplinary and applied aspects were covered.

Adaptive Dynamic Programming for Control

Adaptive Dynamic Programming for Control [Pdf/ePub] eBook ISBN-10: 144714757X
Author: Huaguang Zhang,Derong Liu,Yanhong Luo,Ding Wang
Publisher: Springer Science & Business Media
File Size: 378 KB
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Read Count: 1605608

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Adaptive Dynamic Programming for Control by Huaguang Zhang,Derong Liu,Yanhong Luo,Ding Wang Book Resume:

There are many methods of stable controller design for nonlinear systems. In seeking to go beyond the minimum requirement of stability, Adaptive Dynamic Programming in Discrete Time approaches the challenging topic of optimal control for nonlinear systems using the tools of adaptive dynamic programming (ADP). The range of systems treated is extensive; affine, switched, singularly perturbed and time-delay nonlinear systems are discussed as are the uses of neural networks and techniques of value and policy iteration. The text features three main aspects of ADP in which the methods proposed for stabilization and for tracking and games benefit from the incorporation of optimal control methods: • infinite-horizon control for which the difficulty of solving partial differential Hamilton–Jacobi–Bellman equations directly is overcome, and proof provided that the iterative value function updating sequence converges to the infimum of all the value functions obtained by admissible control law sequences; • finite-horizon control, implemented in discrete-time nonlinear systems showing the reader how to obtain suboptimal control solutions within a fixed number of control steps and with results more easily applied in real systems than those usually gained from infinite-horizon control; • nonlinear games for which a pair of mixed optimal policies are derived for solving games both when the saddle point does not exist, and, when it does, avoiding the existence conditions of the saddle point. Non-zero-sum games are studied in the context of a single network scheme in which policies are obtained guaranteeing system stability and minimizing the individual performance function yielding a Nash equilibrium. In order to make the coverage suitable for the student as well as for the expert reader, Adaptive Dynamic Programming in Discrete Time: • establishes the fundamental theory involved clearly with each chapter devoted to a clearly identifiable control paradigm; • demonstrates convergence proofs of the ADP algorithms to deepen understanding of the derivation of stability and convergence with the iterative computational methods used; and • shows how ADP methods can be put to use both in simulation and in real applications. This text will be of considerable interest to researchers interested in optimal control and its applications in operations research, applied mathematics computational intelligence and engineering. Graduate students working in control and operations research will also find the ideas presented here to be a source of powerful methods for furthering their study.

Advances in Neural Networks - ISNN 2017

Advances in Neural Networks - ISNN 2017 [Pdf/ePub] eBook ISBN-10: 3319590812
Author: Fengyu Cong,Andrew Leung,Qinglai Wei
Publisher: Springer
File Size: 943 KB
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Advances in Neural Networks - ISNN 2017 by Fengyu Cong,Andrew Leung,Qinglai Wei Book Resume:

This book constitutes the refereed proceedings of the 14th International Symposium on Neural Networks, ISNN 2017, held in Sapporo, Hakodate, and Muroran, Hokkaido, Japan, in June 2017. The 135 revised full papers presented in this two-volume set were carefully reviewed and selected from 259 submissions. The papers cover topics like perception, emotion and development, action and motor control, attractor and associative memory, neurodynamics, complex systems, and chaos.

Adaptive Control with Recurrent High-order Neural Networks

Adaptive Control with Recurrent High-order Neural Networks [Pdf/ePub] eBook ISBN-10: 1447107853
Author: George A. Rovithakis,Manolis A. Christodoulou
Publisher: Springer Science & Business Media
File Size: 1797 KB
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Adaptive Control with Recurrent High-order Neural Networks by George A. Rovithakis,Manolis A. Christodoulou Book Resume:

The series Advances in Industrial Control aims to report and encourage technology transfer in control engineering. The rapid development of control technology has an impact on all areas of the control discipline. New theory, new controllers, actuators, sensors, new industrial processes, computer methods, new applications, new philosophies ... , new challenges. Much of this development work resides in industrial reports, feasibility study papers and the reports of advanced collaborative projects. The series offers an opportunity for researchers to present an extended exposition of such new work in all aspects of industrial control for wider and rapid dissemination. Neural networks is one of those areas where an initial burst of enthusiasm and optimism leads to an explosion of papers in the journals and many presentations at conferences but it is only in the last decade that significant theoretical work on stability, convergence and robustness for the use of neural networks in control systems has been tackled. George Rovithakis and Manolis Christodoulou have been interested in these theoretical problems and in the practical aspects of neural network applications to industrial problems. This very welcome addition to the Advances in Industrial Control series provides a succinct report of their research. The neural network model at the core of their work is the Recurrent High Order Neural Network (RHONN) and a complete theoretical and simulation development is presented. Different readers will find different aspects of the development of interest. The last chapter of the monograph discusses the problem of manufacturing or production process scheduling.

Knowledge-Based and Intelligent Information and Engineering Systems

Knowledge-Based and Intelligent Information and Engineering Systems [Pdf/ePub] eBook ISBN-10: 3642153909
Author: Rossitza Setchi,Ivan Jordanov
Publisher: Springer
File Size: 1913 KB
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Read Count: 9496588

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Knowledge-Based and Intelligent Information and Engineering Systems by Rossitza Setchi,Ivan Jordanov Book Resume:

th The 14 International Conference on Knowledge-Based and Intelligent Information and Engineering Systems was held during September 8–10, 2010 in Cardiff, UK. The conference was organized by the School of Engineering at Cardiff University, UK and KES International. KES2010 provided an international scientific forum for the presentation of the - sults of high-quality research on a broad range of intelligent systems topics. The c- ference attracted over 360 submissions from 42 countries and 6 continents: Argentina, Australia, Belgium, Brazil, Bulgaria, Canada, Chile, China, Croatia, Czech Republic, Denmark, Finland, France, Germany, Greece, Hong Kong ROC, Hungary, India, Iran, Ireland, Israel, Italy, Japan, Korea, Malaysia, Mexico, The Netherlands, New Zealand, Pakistan, Poland, Romania, Singapore, Slovenia, Spain, Sweden, Syria, Taiwan, - nisia, Turkey, UK, USA and Vietnam. The conference consisted of 6 keynote talks, 11 general tracks and 29 invited s- sions and workshops, on the applications and theory of intelligent systems and related areas. The distinguished keynote speakers were Christopher Bishop, UK, Nikola - sabov, New Zealand, Saeid Nahavandi, Australia, Tetsuo Sawaragi, Japan, Yuzuru Tanaka, Japan and Roger Whitaker, UK. Over 240 oral and poster presentations provided excellent opportunities for the presentation of interesting new research results and discussion about them, leading to knowledge transfer and generation of new ideas. Extended versions of selected papers were considered for publication in the Int- national Journal of Knowledge-Based and Intelligent Engineering Systems, Engine- ing Applications of Artificial Intelligence, Journal of Intelligent Manufacturing, and Neural Computing and Applications.

Vehicle, Mechatronics and Information Technologies

Vehicle, Mechatronics and Information Technologies [Pdf/ePub] eBook ISBN-10: 3038262013
Author: X.D. Yu
Publisher: Trans Tech Publications Ltd
File Size: 837 KB
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Read Count: 3356004

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Vehicle, Mechatronics and Information Technologies by X.D. Yu Book Resume:

Collection of selected, peer reviewed papers from the 2013 International Conference on Vehicle & Mechanical Engineering and Information Technology (VMEIT 2013), August 17-18, 2013, Zhengzhou, Henan, China. The 1094 papers are grouped as follows: Chapter 1: Design and Researches in Area of Vehicle and General Mechanical Engineering; Chapter 2: Mechatronics, Automation and Control; Chapter 3: Measurement and Instrumentation, Monitoring and Detection Technologies, Fault Diagnosis; Chapter 4: Computation Methods and Algorithms for Modeling, Simulation and Optimization, Data Mining and Data Processing; Chapter 5: Information Technologies, WEB and Networks Engineering, Information Security, Software Application and Development; Chapter 6: Power and Electric Systems, Electronics and Microelectronics, Embedded and Integrated Systems; Chapter 7: Communication, Signal and Image Processing, Data Acquisition, Identification and Recognition Technologies; Chapter 8: Information Technologies in Urban and Civil Engineering, Medicine and Biotechnology; Chapter 9: Material Science and Manufacturing Technology; Chapter 10: Information Technology in Management Engineering, Logistics, Economics, Finance, Assessment; Chapter 11: Related Themes.

Neural Network Control Of Robot Manipulators And Non-Linear Systems

Neural Network Control Of Robot Manipulators And Non-Linear Systems [Pdf/ePub] eBook ISBN-10: 100016277X
Author: F W Lewis,S. Jagannathan,A Yesildirak
Publisher: CRC Press
File Size: 1691 KB
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Read Count: 1837318

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Neural Network Control Of Robot Manipulators And Non-Linear Systems by F W Lewis,S. Jagannathan,A Yesildirak Book Resume:

There has been great interest in "universal controllers" that mimic the functions of human processes to learn about the systems they are controlling on-line so that performance improves automatically. Neural network controllers are derived for robot manipulators in a variety of applications including position control, force control, link flexibility stabilization and the management of high-frequency joint and motor dynamics. The first chapter provides a background on neural networks and the second on dynamical systems and control. Chapter three introduces the robot control problem and standard techniques such as torque, adaptive and robust control. Subsequent chapters give design techniques and Stability Proofs For NN Controllers For Robot Arms, Practical Robotic systems with high frequency vibratory modes, force control and a general class of non-linear systems. The last chapters are devoted to discrete- time NN controllers. Throughout the text, worked examples are provided.