Decentralized Neural Control Application To Robotics PDF Download
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Author | : Ramon Garcia-Hernandez |
Publisher | : Springer |
Total Pages | : 111 |
Release | : 2017-02-05 |
Genre | : Technology & Engineering |
ISBN | : 3319533126 |
Download Decentralized Neural Control: Application to Robotics Book in PDF, ePub and Kindle
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.
Author | : Alma Y. Alanis |
Publisher | : Academic Press |
Total Pages | : 176 |
Release | : 2019-03-15 |
Genre | : Science |
ISBN | : 0128182474 |
Download Artificial Neural Networks for Engineering Applications Book in PDF, ePub and Kindle
Artificial Neural Networks for Engineering Applications presents current trends for the solution of complex engineering problems that cannot be solved through conventional methods. The proposed methodologies can be applied to modeling, pattern recognition, classification, forecasting, estimation, and more. Readers will find different methodologies to solve various problems, including complex nonlinear systems, cellular computational networks, waste water treatment, attack detection on cyber-physical systems, control of UAVs, biomechanical and biomedical systems, time series forecasting, biofuels, and more. Besides the real-time implementations, the book contains all the theory required to use the proposed methodologies for different applications. Presents the current trends for the solution of complex engineering problems that cannot be solved through conventional methods Includes real-life scenarios where a wide range of artificial neural network architectures can be used to solve the problems encountered in engineering Contains all the theory required to use the proposed methodologies for different applications
Author | : |
Publisher | : |
Total Pages | : 508 |
Release | : 2000 |
Genre | : Autonomous robots |
ISBN | : |
Download Sensor Fusion and Decentralized Control in Robotic Systems Book in PDF, ePub and Kindle
Author | : Donald T. Gavel |
Publisher | : |
Total Pages | : 242 |
Release | : 1988 |
Genre | : |
ISBN | : |
Download Decentralized Adaptive Control of Large Scale Systems, with Application to Robotics Book in PDF, ePub and Kindle
Author | : Kurosh Madani |
Publisher | : Springer |
Total Pages | : 362 |
Release | : 2012-12-22 |
Genre | : Technology & Engineering |
ISBN | : 3642356389 |
Download Computational Intelligence Book in PDF, ePub and Kindle
The present book includes a set of selected extended papers from the third International Joint Conference on Computational Intelligence (IJCCI 2011), held in Paris, France, from 24 to 26 October 2011. The conference was composed of three co-located conferences: The International Conference on Fuzzy Computation (ICFC), the International Conference on Evolutionary Computation (ICEC), and the International Conference on Neural Computation (ICNC). Recent progresses in scientific developments and applications in these three areas are reported in this book. IJCCI received 283 submissions, from 59 countries, in all continents. This book includes the revised and extended versions of a strict selection of the best papers presented at the conference.
Author | : Kai Liu |
Publisher | : |
Total Pages | : 342 |
Release | : 1990 |
Genre | : Adaptive control systems |
ISBN | : |
Download Decentralized Control of Interconnected Systems with Applications to Mobile Robots Book in PDF, ePub and Kindle
Author | : G. T. McKee |
Publisher | : SPIE-International Society for Optical Engineering |
Total Pages | : 352 |
Release | : 1999 |
Genre | : Technology & Engineering |
ISBN | : |
Download Sensor Fusion and Decentralized Control in Robotic Systems II Book in PDF, ePub and Kindle
This work presents a series of papers examining various aspects of sensor fusion and decentralized control in robotic systems.
Author | : George A. Bekey |
Publisher | : Springer Science & Business Media |
Total Pages | : 560 |
Release | : 2012-12-06 |
Genre | : Technology & Engineering |
ISBN | : 1461531802 |
Download Neural Networks in Robotics Book in PDF, ePub and Kindle
Neural Networks in Robotics is the first book to present an integrated view of both the application of artificial neural networks to robot control and the neuromuscular models from which robots were created. The behavior of biological systems provides both the inspiration and the challenge for robotics. The goal is to build robots which can emulate the ability of living organisms to integrate perceptual inputs smoothly with motor responses, even in the presence of novel stimuli and changes in the environment. The ability of living systems to learn and to adapt provides the standard against which robotic systems are judged. In order to emulate these abilities, a number of investigators have attempted to create robot controllers which are modelled on known processes in the brain and musculo-skeletal system. Several of these models are described in this book. On the other hand, connectionist (artificial neural network) formulations are attractive for the computation of inverse kinematics and dynamics of robots, because they can be trained for this purpose without explicit programming. Some of the computational advantages and problems of this approach are also presented. For any serious student of robotics, Neural Networks in Robotics provides an indispensable reference to the work of major researchers in the field. Similarly, since robotics is an outstanding application area for artificial neural networks, Neural Networks in Robotics is equally important to workers in connectionism and to students for sensormonitor control in living systems.
Author | : Tong Heng Lee |
Publisher | : World Scientific |
Total Pages | : 400 |
Release | : 1998 |
Genre | : |
ISBN | : 9789810234522 |
Download Adaptive Neural Network Control of Robotic Manipulators Book in PDF, ePub and Kindle
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 | : F W Lewis |
Publisher | : CRC Press |
Total Pages | : 470 |
Release | : 1998-11-30 |
Genre | : Technology & Engineering |
ISBN | : 9780748405961 |
Download Neural Network Control Of Robot Manipulators And Non-Linear Systems Book in PDF, ePub and Kindle
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.