[PDF] Adaptive Neural Network Control Of Robotic Manipulators eBook

Author : Sam Shuzhi Ge
Publisher : World Scientific
Page : 397 pages
File Size : 45,25 MB
Release : 1998-12-04
Category : Technology & Engineering
ISBN : 9814496227

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Recently, there has been considerable research interest in neural network control of robots, and satisfactory results have been obtained in solving some of the special issues associated with the problems of robot control in an “on-and-off” fashion. This book is dedicated to issues on adaptive control of robots based on neural networks. The text has been carefully tailored to (i) give a comprehensive study of robot dynamics, (ii) present structured network models for robots, and (iii) provide systematic approaches for neural network based adaptive controller design for rigid robots, flexible joint robots, and robots in constraint motion. Rigorous proof of the stability properties of adaptive neural network controllers is provided. Simulation examples are also presented to verify the effectiveness of the controllers, and practical implementation issues associated with the controllers are also discussed.

Author : Shuzhi S. Ge
Publisher : World Scientific Series In Robotics And Intelligent Systems
Page : 381 pages
File Size : 18,16 MB
Release : 1998
Category : Technology & Engineering
ISBN : 9789810234522

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Recently, there has been considerable research interest in neural network control of robots, and satisfactory results have been obtained in solving some of the special issues associated with the problems of robot control in an "on-and-off" fashion. This book is dedicated to issues on adaptive control of robots based on neural networks. The text has been carefully tailored to (i) give a comprehensive study of robot dynamics, (ii) present structured network models for robots, and (iii) provide systematic approaches for neural network based adaptive controller design for rigid robots, flexible joint robots, and robots in constraint motion. Rigorous proof of the stability properties of adaptive neural network controllers is provided. Simulation examples are also presented to verify the effectiveness of the controllers, and practical implementation issues associated with the controllers are also discussed.

Author : F W Lewis
Publisher : CRC Press
Page : 470 pages
File Size : 42,21 MB
Release : 1998-11-30
Category : Technology & Engineering
ISBN : 9780748405961

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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.

Author : Tong Heng Lee
Publisher : World Scientific
Page : 400 pages
File Size : 20,95 MB
Release : 1998
Category :
ISBN : 9789810234522

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Introduction; Mathematical background; Dynamic modelling of robots; Structured network modelling of robots; Adaptive neural network control of robots; Neural network model reference adaptive control; Flexible joint robots; task space and force control; Bibliography; Computer simulation; Simulation software in C.

Author : Frank L. Lewis
Publisher : CRC Press
Page : 646 pages
File Size : 45,21 MB
Release : 2003-12-12
Category : Technology & Engineering
ISBN : 9780203026953

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Robot Manipulator Control offers a complete survey of control systems for serial-link robot arms and acknowledges how robotic device performance hinges upon a well-developed control system. Containing over 750 essential equations, this thoroughly up-to-date Second Edition, the book explicates theoretical and mathematical requisites for controls design and summarizes current techniques in computer simulation and implementation of controllers. It also addresses procedures and issues in computed-torque, robust, adaptive, neural network, and force control. New chapters relay practical information on commercial robot manipulators and devices and cutting-edge methods in neural network control.

Author : Ali M. S. Zalzala
Publisher : Prentice Hall
Page : 296 pages
File Size : 20,94 MB
Release : 1996
Category : Computers
ISBN :

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1. An overview of neural networks in control applications; 2. Artificial neural network based intelligent robot dynamic control; 3. Neural servo controller for position, force stabbing control of robotic manipulators; 4. Model-based adaptive neural structures for robotic control; 5. Intelligent co-ordination of multiple systems with neural networks; 6. Neural networks for mobile robot piloting control; 7. A neural network controller for the navigation and obstacle avoidance of a mobile robot; An ultrasonic 3-D robot vision system based on the statistical properties of artificial neural networks; Visual control of robotic manipulator based on neural networks; 10. Brain building for a biological robot; 11. Robustness of a distributed neural network controller for locomotion in a hexapod robot.

Author : 林楠林
Publisher :
Page : pages
File Size : 29,96 MB
Release : 2017-01-27
Category :
ISBN : 9781374772892

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This dissertation, "A Neural-network Approach to High-performance Adaptive Control for Robot Manipulators" by 林楠林, Nanlin, Lin, was obtained from The University of Hong Kong (Pokfulam, Hong Kong) and is being sold pursuant to Creative Commons: Attribution 3.0 Hong Kong License. The content of this dissertation has not been altered in any way. We have altered the formatting in order to facilitate the ease of printing and reading of the dissertation. All rights not granted by the above license are retained by the author. DOI: 10.5353/th_b3123741 Subjects: Manipulators (Mechanism) Neural networks (Computer science) Robots - Control systems