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High-level Feedback Control With Neural Networks

1998-09-28 Technology & Engineering
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Release : 1998-09-28
Genre : Technology & Engineering
Kind : eBook
Book Rating : 456/5 ( reviews)

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Book Synopsis High-level Feedback Control With Neural Networks by : Young Ho Kim

Download or read book High-level Feedback Control With Neural Networks written by Young Ho Kim. This book was released on 1998-09-28. Available in PDF, EPUB and Kindle. Book excerpt: 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.

High-Level Feedback Control with Neural Networks

1998 Computers
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Author :
Release : 1998
Genre : Computers
Kind : eBook
Book Rating : 761/5 ( reviews)

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Book Synopsis High-Level Feedback Control with Neural Networks by : Young Ho Kim

Download or read book High-Level Feedback Control with Neural Networks written by Young Ho Kim. This book was released on 1998. Available in PDF, EPUB and Kindle. Book excerpt: 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 areintuitive, 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.

Neural Network Control Of Robot Manipulators And Non-Linear Systems

1998-11-30 Technology & Engineering
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Release : 1998-11-30
Genre : Technology & Engineering
Kind : eBook
Book Rating : 961/5 ( reviews)

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Book Synopsis Neural Network Control Of Robot Manipulators And Non-Linear Systems by : F W Lewis

Download or read book Neural Network Control Of Robot Manipulators And Non-Linear Systems written by F W Lewis. This book was released on 1998-11-30. 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.

Reinforcement Learning and Approximate Dynamic Programming for Feedback Control

2013-01-28 Technology & Engineering
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Release : 2013-01-28
Genre : Technology & Engineering
Kind : eBook
Book Rating : 972/5 ( reviews)

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Book Synopsis Reinforcement Learning and Approximate Dynamic Programming for Feedback Control by : Frank L. Lewis

Download or read book Reinforcement Learning and Approximate Dynamic Programming for Feedback Control written by Frank L. Lewis. This book was released on 2013-01-28. Available in PDF, EPUB and Kindle. Book excerpt: Reinforcement learning (RL) and adaptive dynamic programming (ADP) has been one of the most critical research fields in science and engineering for modern complex systems. This book describes the latest RL and ADP techniques for decision and control in human engineered systems, covering both single player decision and control and multi-player games. Edited by the pioneers of RL and ADP research, the book brings together ideas and methods from many fields and provides an important and timely guidance on controlling a wide variety of systems, such as robots, industrial processes, and economic decision-making.

Neural Networks for Robotics

2018-08-21 Technology & Engineering
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Release : 2018-08-21
Genre : Technology & Engineering
Kind : eBook
Book Rating : 774/5 ( reviews)

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Book Synopsis Neural Networks for Robotics by : Nancy Arana-Daniel

Download or read book Neural Networks for Robotics written by Nancy Arana-Daniel. This book was released on 2018-08-21. Available in PDF, EPUB and Kindle. Book excerpt: The book offers an insight on artificial neural networks for giving a robot a high level of autonomous tasks, such as navigation, cost mapping, object recognition, intelligent control of ground and aerial robots, and clustering, with real-time implementations. The reader will learn various methodologies that can be used to solve each stage on autonomous navigation for robots, from object recognition, clustering of obstacles, cost mapping of environments, path planning, and vision to low level control. These methodologies include real-life scenarios to implement a wide range of artificial neural network architectures.

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