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Controllo neurale decentralizzato: applicazione alla robotica di Edgar N. Sanchez (inglese-
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- Compralo SubitoControllo neurale decentralizzato: applicazione alla robotica di Edgar N. Sanchez (inglese
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Numero oggetto eBay:364704305948
Specifiche dell'oggetto
- Condizione
- ISBN-13
- 9783319533117
- Book Title
- Decentralized Neural Control: Application to Robotics
- ISBN
- 9783319533117
- Subject Area
- Computers, Technology & Engineering, Science
- Publication Name
- Decentralized Neural Control: Application to Robotics
- Publisher
- Springer International Publishing A&G
- Item Length
- 9.3 in
- Subject
- Engineering (General), Mechanics / Dynamics, Intelligence (Ai) & Semantics, Neural Networks, Electrical
- Publication Year
- 2017
- Series
- Studies in Systems, Decision and Control Ser.
- Type
- Textbook
- Format
- Hardcover
- Language
- English
- Item Weight
- 16 Oz
- Item Width
- 6.1 in
- Number of Pages
- Xv, 111 Pages
Informazioni su questo prodotto
Product Identifiers
Publisher
Springer International Publishing A&G
ISBN-10
3319533118
ISBN-13
9783319533117
eBay Product ID (ePID)
240412331
Product Key Features
Number of Pages
Xv, 111 Pages
Publication Name
Decentralized Neural Control: Application to Robotics
Language
English
Publication Year
2017
Subject
Engineering (General), Mechanics / Dynamics, Intelligence (Ai) & Semantics, Neural Networks, Electrical
Type
Textbook
Subject Area
Computers, Technology & Engineering, Science
Series
Studies in Systems, Decision and Control Ser.
Format
Hardcover
Dimensions
Item Weight
16 Oz
Item Length
9.3 in
Item Width
6.1 in
Additional Product Features
Dewey Edition
23
Series Volume Number
96
Number of Volumes
1 vol.
Illustrated
Yes
Dewey Decimal
629.892
Table Of Content
Introduction.- Foundations.- Decentralized Neural Block Control.- Decentralized Neural Backstepping Control.- Decentralized Inverse Optimal Control for Stabilization: a CLF Approach.- Decentralized Inverse Optimal Control for Trajectory Tracking.- Robotics Application.- Conclusions.
Synopsis
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., 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 thirdcontrol 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.
LC Classification Number
Q342
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