Adaptive Neural Network Control Of Robotic Manipulators
Adaptive Neural Network Control Of Robotic Manipulators

Author: Sam Shuzhi Ge

Publisher: World Scientific

Published: 1998-12-04

Total Pages: 397

ISBN-13: 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.

Neural Network Control Of Robot Manipulators And Non-Linear Systems
Neural Network Control Of Robot Manipulators And Non-Linear Systems

Author: F W Lewis

Publisher: CRC Press

Published: 1998-11-30

Total Pages: 470

ISBN-13: 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.

Adaptive Neural Network Control of Robotic Manipulators
Adaptive Neural Network Control of Robotic Manipulators

Author: Shuzhi S. Ge

Publisher: World Scientific Series In Robotics And Intelligent Systems

Published: 1998

Total Pages: 381

ISBN-13: 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.

Robot Manipulator Control
Robot Manipulator Control

Author: Frank L. Lewis

Publisher: CRC Press

Published: 2003-12-12

Total Pages: 646

ISBN-13: 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.

Adaptive Control of Robot Manipulators
Adaptive Control of Robot Manipulators

Author: An-Chyau Huang

Publisher: World Scientific

Published: 2010

Total Pages: 274

ISBN-13: 9814307416

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This book introduces an unified function approximation approach to the control of uncertain robot manipulators containing general uncertainties. It works for free space tracking control as well as compliant motion control. It is applicable to the rigid robot and the flexible joint robot. Even with actuator dynamics, the unified approach is still feasible. All these features make the book stand out from other existing publications.

Adaptive Neural Network Control of Robotic Manipulators
Adaptive Neural Network Control of Robotic Manipulators

Author: Tong Heng Lee

Publisher: World Scientific

Published: 1998

Total Pages: 400

ISBN-13: 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.

Neural Systems for Robotics
Neural Systems for Robotics

Author: Omid Omidvar

Publisher: Academic Press

Published: 1997-04-10

Total Pages: 369

ISBN-13: 0125262809

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Neural Systems for Robotics represents the most up-to-date developments in the rapidly growing aplication area of neural networks, which is one of the hottest application areas for neural networks technology. The book not only contains a comprehensive study of neurocontrollers in complex Robotics systems, written by highly respected researchers in the field but outlines a novel approach to solving Robotics problems. The importance of neural networks in all aspects of Robot arm manipulators, neurocontrol, and Robotic systems is also given thorough and in-depth coverage. All researchers and students dealing with Robotics will find Neural Systems for Robotics of immense interest and assistance. Focuses on the use of neural networks in robotics-one of the hottest application areas for neural networks technology Represents the most up-to-date developments in this rapidly growing application area of neural networks Contains a new and novel approach to solving Robotics problems

Advanced Sliding Mode Control for Mechanical Systems
Advanced Sliding Mode Control for Mechanical Systems

Author: Jinkun Liu

Publisher: Springer Science & Business Media

Published: 2012-09-07

Total Pages: 367

ISBN-13: 3642209076

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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.