Decentralized Neural Control Application To Robotics

Author : Ramon Garcia-Hernandez
Publisher : Springer
ISBN 13 : 3319533126
Total Pages : 111 pages
Book Rating : 4.24/5 ( download)

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Download or read book Decentralized Neural Control: Application to Robotics written by Ramon Garcia-Hernandez and published by Springer. This book was released on 2017-02-05 with total page 111 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
ISBN 13 : 0128182474
Total Pages : 176 pages
Book Rating : 4.75/5 ( download)

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Download or read book Artificial Neural Networks for Engineering Applications written by Alma Y. Alanis and published by Academic Press. This book was released on 2019-03-15 with total page 176 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 :
ISBN 13 :
Total Pages : 272 pages
Book Rating : 4.87/5 ( download)

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Download or read book Sensor Fusion and Decentralized Control in Robotic Systems written by and published by . This book was released on 2001 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Author : Kurosh Madani
Publisher : Springer
ISBN 13 : 3642356389
Total Pages : 362 pages
Book Rating : 4.84/5 ( download)

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Download or read book Computational Intelligence written by Kurosh Madani and published by Springer. This book was released on 2012-12-22 with total page 362 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 : G. T. McKee
Publisher : SPIE-International Society for Optical Engineering
ISBN 13 :
Total Pages : 352 pages
Book Rating : 4.09/5 ( download)

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Download or read book Sensor Fusion and Decentralized Control in Robotic Systems II written by G. T. McKee and published by SPIE-International Society for Optical Engineering. This book was released on 1999 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: This work presents a series of papers examining various aspects of sensor fusion and decentralized control in robotic systems.

Author : Arthur G.O. Mutambara
Publisher : Routledge
ISBN 13 : 1351456504
Total Pages : 256 pages
Book Rating : 4.00/5 ( download)

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Download or read book Decentralized Estimation and Control for Multisensor Systems written by Arthur G.O. Mutambara and published by Routledge. This book was released on 2019-05-20 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: Decentralized Estimation and Control for Multisensor Systems explores the problem of developing scalable, decentralized estimation and control algorithms for linear and nonlinear multisensor systems. Such algorithms have extensive applications in modular robotics and complex or large scale systems, including the Mars Rover, the Mir station, and Space Shuttle Columbia. Most existing algorithms use some form of hierarchical or centralized structure for data gathering and processing. In contrast, in a fully decentralized system, all information is processed locally. A decentralized data fusion system includes a network of sensor nodes - each with its own processing facility, which together do not require any central processing or central communication facility. Only node-to-node communication and local system knowledge are permitted. Algorithms for decentralized data fusion systems based on the linear information filter have been developed, obtaining decentrally the same results as those in a conventional centralized data fusion system. However, these algorithms are limited, indicating that existing decentralized data fusion algorithms have limited scalability and are wasteful of communications and computation resources. Decentralized Estimation and Control for Multisensor Systems aims to remove current limitations in decentralized data fusion algorithms and to extend the decentralized principle to problems involving local control and actuation. The text discusses: Generalizing the linear Information filter to the problem of estimation for nonlinear systems Developing a decentralized form of the algorithm Solving the problem of fully connected topologies by using generalized model distribution where the nodal system involves only locally relevant states Reducing computational requirements by using smaller local model sizes Defining internodal communication Developing estima

Author : Tong Heng Lee
Publisher : World Scientific
ISBN 13 : 9789810234522
Total Pages : 400 pages
Book Rating : 4.2X/5 ( download)

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Download or read book Adaptive Neural Network Control of Robotic Manipulators written by Tong Heng Lee and published by World Scientific. This book was released on 1998 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
ISBN 13 : 9780748405961
Total Pages : 470 pages
Book Rating : 4.68/5 ( download)

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Download or read book Neural Network Control Of Robot Manipulators And Non-Linear Systems written by F W Lewis and published by CRC Press. This book was released on 1998-11-30 with total page 470 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 : George A. Bekey
Publisher : Springer Science & Business Media
ISBN 13 : 1461531802
Total Pages : 560 pages
Book Rating : 4.07/5 ( download)

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Download or read book Neural Networks in Robotics written by George A. Bekey and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 560 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 : Hamido Fujita
Publisher : Springer Nature
ISBN 13 : 3030557898
Total Pages : 931 pages
Book Rating : 4.98/5 ( download)

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Download or read book Trends in Artificial Intelligence Theory and Applications. Artificial Intelligence Practices written by Hamido Fujita and published by Springer Nature. This book was released on 2020-09-04 with total page 931 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed proceedings of the 33rd International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2020, held in Kitakyushu, Japan, in September 2020. The 62 full papers and 17 short papers presented were carefully reviewed and selected from 119 submissions. The IEA/AIE 2020 conference will continue the tradition of emphasizing on applications of applied intelligent systems to solve real-life problems in all areas. These areas include are language processing; robotics and drones; knowledge based systems; innovative applications of intelligent systems; industrial applications; networking applications; social network analysis; financial applications and blockchain; medical and health-related applications; anomaly detection and automated diagnosis; decision-support and agent-based systems; multimedia applications; machine learning; data management and data clustering; pattern mining; system control, classification, and fault diagnosis.