Neural Network Control Of Robot Manipulators And Non Linear Systems
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Neural Network Control Of Robot Manipulators And Non Linear Systems
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Author : F W Lewis
language : en
Publisher: CRC Press
Release Date : 1998-11-30
Neural Network Control Of Robot Manipulators And Non Linear Systems written by F W Lewis and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998-11-30 with Technology & Engineering categories.
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
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Author :
language : en
Publisher:
Release Date :
Adaptive Neural Network Control Of Robotic Manipulators written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.
Adaptive Neural Network Control Of Robotic Manipulators
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Author : Tong Heng Lee
language : en
Publisher: World Scientific
Release Date : 1998
Adaptive Neural Network Control Of Robotic Manipulators written by Tong Heng Lee and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998 with categories.
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.
Differential Neural Networks For Robust Nonlinear Control
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Author : Alexander S. Poznyak
language : en
Publisher: World Scientific
Release Date : 2001
Differential Neural Networks For Robust Nonlinear Control written by Alexander S. Poznyak and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001 with Science categories.
This book deals with continuous time dynamic neural networks theory applied to the solution of basic problems in robust control theory, including identification, state space estimation (based on neuro-observers) and trajectory tracking. The plants to be identified and controlled are assumed to be a priori unknown but belonging to a given class containing internal unmodelled dynamics and external perturbations as well. The error stability analysis and the corresponding error bounds for different problems are presented. The effectiveness of the suggested approach is illustrated by its application to various controlled physical systems (robotic, chaotic, chemical, etc.). Contents: Theoretical Study: Neural Networks Structures; Nonlinear System Identification: Differential Learning; Sliding Mode Identification: Algebraic Learning; Neural State Estimation; Passivation via Neuro Control; Neuro Trajectory Tracking; Neurocontrol Applications: Neural Control for Chaos; Neuro Control for Robot Manipulators; Identification of Chemical Processes; Neuro Control for Distillation Column; General Conclusions and Future Work; Appendices: Some Useful Mathematical Facts; Elements of Qualitative Theory of ODE; Locally Optimal Control and Optimization. Readership: Graduate students, researchers, academics/lecturers and industrialists in neural networks.
Neural Network Control Of Robot Manipulators And Non Linear Systems
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Author : F W Lewis
language : en
Publisher: CRC Press
Release Date : 2020-08-14
Neural Network Control Of Robot Manipulators And Non Linear Systems written by F W Lewis and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-08-14 with Technology & Engineering categories.
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.
Decentralized Neural Control Application To Robotics
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Author : Ramon Garcia-Hernandez
language : en
Publisher: Springer
Release Date : 2017-02-05
Decentralized Neural Control Application To Robotics written by Ramon Garcia-Hernandez and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-02-05 with Technology & Engineering categories.
This book provides a decentralized approach for the identification and control of robotics systems. It also presents recent research in decentralized neural control and includes applications to robotics. Decentralized control is free from difficulties due to complexity in design, debugging, data gathering and storage requirements, making it preferable for interconnected systems. Furthermore, as opposed to the centralized approach, it can be implemented with parallel processors. This approach deals with four decentralized control schemes, which are able to identify the robot dynamics. The training of each neural network is performed on-line using an extended Kalman filter (EKF). The first indirect decentralized control scheme applies the discrete-time block control approach, to formulate a nonlinear sliding manifold. The second direct decentralized neural control scheme is based on the backstepping technique, approximated by a high order neural network. The third control scheme applies a decentralized neural inverse optimal control for stabilization. The fourth decentralized neural inverse optimal control is designed for trajectory tracking. This comprehensive work on decentralized control of robot manipulators and mobile robots is intended for professors, students and professionals wanting to understand and apply advanced knowledge in their field of work.
Robot Manipulator Control
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Author : Frank L. Lewis
language : en
Publisher: CRC Press
Release Date : 2003-12-12
Robot Manipulator Control written by Frank L. Lewis and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003-12-12 with Technology & Engineering categories.
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.
High Level Feedback Control With Neural Networks
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Author : Young Ho Kim
language : en
Publisher: World Scientific
Release Date : 1998-09-28
High Level Feedback Control With Neural Networks written by Young Ho Kim and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998-09-28 with Technology & Engineering categories.
Complex industrial or robotic systems with uncertainty and disturbances are difficult to control. As system uncertainty or performance requirements increase, it becomes necessary to augment traditional feedback controllers with additional feedback loops that effectively “add intelligence” to the system. Some theories of artificial intelligence (AI) are now showing how complex machine systems should mimic human cognitive and biological processes to improve their capabilities for dealing with uncertainty.This book bridges the gap between feedback control and AI. It provides design techniques for “high-level” neural-network feedback-control topologies that contain servo-level feedback-control loops as well as AI decision and training at the higher levels. Several advanced feedback topologies containing neural networks are presented, including “dynamic output feedback”, “reinforcement learning” and “optimal design”, as well as a “fuzzy-logic reinforcement” controller. The control topologies are intuitive, yet are derived using sound mathematical principles where proofs of stability are given so that closed-loop performance can be relied upon in using these control systems. Computer-simulation examples are given to illustrate the performance.
Robot Manipulators
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Author : Agustin Jimenez
language : en
Publisher: BoD – Books on Demand
Release Date : 2010-03-01
Robot Manipulators written by Agustin Jimenez and has been published by BoD – Books on Demand this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-03-01 with Technology & Engineering categories.
This book presents the most recent research advances in robot manipulators. It offers a complete survey to the kinematic and dynamic modelling, simulation, computer vision, software engineering, optimization and design of control algorithms applied for robotic systems. It is devoted for a large scale of applications, such as manufacturing, manipulation, medicine and automation. Several control methods are included such as optimal, adaptive, robust, force, fuzzy and neural network control strategies. The trajectory planning is discussed in details for point-to-point and path motions control. The results in obtained in this book are expected to be of great interest for researchers, engineers, scientists and students, in engineering studies and industrial sectors related to robot modelling, design, control, and application. The book also details theoretical, mathematical and practical requirements for mathematicians and control engineers. It surveys recent techniques in modelling, computer simulation and implementation of advanced and intelligent controllers.
Neural Networks For Robotic Control
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Author : Ali M. S. Zalzala
language : en
Publisher: Prentice Hall
Release Date : 1996
Neural Networks For Robotic Control written by Ali M. S. Zalzala and has been published by Prentice Hall this book supported file pdf, txt, epub, kindle and other format this book has been release on 1996 with Computers categories.
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.