| 书目名称 | Decentralized Neural Control: Application to Robotics |
| 编辑 | Ramon Garcia-Hernandez,Michel Lopez-Franco,Jose A. |
| 视频video | |
| 概述 | Presents recent research in decentralized neural control.Includes applications to robotics.Presents results in simulation and real time.Includes supplementary material: |
| 丛书名称 | Studies in Systems, Decision and Control |
| 图书封面 |  |
| 描述 | .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 |
| 出版日期 | Book 2017 |
| 关键词 | Decentralized Neural Control; Robotics; Computational Intelligence; Intelligent Systems; Neural Control |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-319-53312-4 |
| isbn_softcover | 978-3-319-85123-5 |
| isbn_ebook | 978-3-319-53312-4Series ISSN 2198-4182 Series E-ISSN 2198-4190 |
| issn_series | 2198-4182 |
| copyright | Springer International Publishing Switzerland 2017 |
发表于 2025-3-21 17:49:34
