Control Of Flexible Link Manipulators Using Neural Networks
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| Author | : H.A. Talebi |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 172 |
| Release | : 2001-01-29 |
| Genre | : Technology & Engineering |
| ISBN | : 9781852334093 |
Control of Flexible-link Manipulators Using Neural Networks addresses the difficulties that arise in controlling the end-point of a manipulator that has a significant amount of structural flexibility in its links. The non-minimum phase characteristic, coupling effects, nonlinearities, parameter variations and unmodeled dynamics in such a manipulator all contribute to these difficulties. Control strategies that ignore these uncertainties and nonlinearities generally fail to provide satisfactory closed-loop performance. This monograph develops and experimentally evaluates several intelligent (neural network based) control techniques to address the problem of controlling the end-point of flexible-link manipulators in the presence of all the aforementioned difficulties. To highlight the main issues, a very flexible-link manipulator whose hub exhibits a considerable amount of friction is considered for the experimental work. Four different neural network schemes are proposed and implemented on the experimental test-bed. The neural networks are trained and employed as online controllers.
| Author | : M. Osman Tokhi |
| Publisher | : IET |
| Total Pages | : 579 |
| Release | : 2008-05-20 |
| Genre | : Technology & Engineering |
| ISBN | : 0863414486 |
This book discusses the latest developmens in modelling, simulation and control of flexible robot manipulators. Coverage includes an overall review of previously developed methodologies, a range of modelling approaches including classical techniques, parametric and neuromodelling approaches and numerical modelling/simulation techniques.
| Author | : H.A. Talebi |
| Publisher | : Springer |
| Total Pages | : 150 |
| Release | : 2014-03-12 |
| Genre | : Technology & Engineering |
| ISBN | : 9781447139515 |
Control of Flexible-link Manipulators Using Neural Networks addresses the difficulties that arise in controlling the end-point of a manipulator that has a significant amount of structural flexibility in its links. The non-minimum phase characteristic, coupling effects, nonlinearities, parameter variations and unmodeled dynamics in such a manipulator all contribute to these difficulties. Control strategies that ignore these uncertainties and nonlinearities generally fail to provide satisfactory closed-loop performance. This monograph develops and experimentally evaluates several intelligent (neural network based) control techniques to address the problem of controlling the end-point of flexible-link manipulators in the presence of all the aforementioned difficulties. To highlight the main issues, a very flexible-link manipulator whose hub exhibits a considerable amount of friction is considered for the experimental work. Four different neural network schemes are proposed and implemented on the experimental test-bed. The neural networks are trained and employed as online controllers.
| Author | : Sam Shuzhi Ge |
| Publisher | : World Scientific |
| Total Pages | : 397 |
| Release | : 1998-12-04 |
| Genre | : Technology & Engineering |
| ISBN | : 9814496227 |
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 |
| Total Pages | : 470 |
| Release | : 1998-11-30 |
| Genre | : Technology & Engineering |
| ISBN | : 9780748405961 |
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 | : Agustin Jimenez |
| Publisher | : BoD – Books on Demand |
| Total Pages | : 680 |
| Release | : 2010-03-01 |
| Genre | : Technology & Engineering |
| ISBN | : 9533070730 |
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.
| Author | : Shuzhi S. Ge |
| Publisher | : World Scientific Series In Robotics And Intelligent Systems |
| Total Pages | : 381 |
| Release | : 1998 |
| Genre | : Technology & Engineering |
| ISBN | : 9789810234522 |
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 | : Kshetrimayum Lochan |
| Publisher | : CRC Press |
| Total Pages | : 236 |
| Release | : 2024-10-13 |
| Genre | : Technology & Engineering |
| ISBN | : 1040152201 |
Various modelling and control of two-link flexible manipulators are presented in this book. The lumped parameter modelling method and the assumed modes method modelling are comprehensively reviewed. The book also reviews the trajectory tracking problem and tip trajectory tracking problem along with the suppression of tip deflection of the links. An exponential time varying signal and a chaotic signal are considered as the desired trajectories. The identical/ non-identical slave manipulator is synchronised with the controlled master manipulator so that the slave manipulator indirectly follows the desired manipulator.
| Author | : Gerasimos Rigatos |
| Publisher | : Springer |
| Total Pages | : 759 |
| Release | : 2018-05-24 |
| Genre | : Technology & Engineering |
| ISBN | : 331977851X |
This monograph addresses problems of: • nonlinear control, estimation and filtering for robotic manipulators (multi-degree-of freedom rigid-link robots, flexible-link robots, underactuated, redundant and cooperating manipulators and closed-chain robotic mechanisms); and• nonlinear control, estimation and filtering for autonomous robotic vehicles operating on the ground, in the air, and on and under water, independently and in cooperating groups. The book is a thorough treatment of the entire range of applications of robotic manipulators and autonomous vehicles. The nonlinear control and estimation methods it develops can be used generically, being suitable for a wide range of robotic systems. Such methods can improve robustness, precision and fault-tolerance in robotic manipulators and vehicles at the same time as enabling the reliable functioning of these systems under variable conditions, model uncertainty and external perturbations.
| Author | : Jinkun Liu |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 375 |
| Release | : 2013-01-26 |
| Genre | : Technology & Engineering |
| ISBN | : 3642348165 |
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.
