Neural networks for control

✍ Scribed by W Thomas Miller; Richard S Sutton; Paul J Werbos; National Science Foundation (U.S.)

Publisher: MIT Press
Year: 1990
Tongue: English
Leaves: 526
Series: Neural network modeling and connectionism
Category: Library

No coin nor oath required. For personal study only.

✦ Table of Contents

Content: based on a workshop held at the University of New Hampshire in October, 1988 and entitled ''The application of neural networks to robotics and control.''

📜 SIMILAR VOLUMES

📁 Neural networks for control

📂 Library 📅 1990 🏛 Cambridge, Mass. : MIT Press 🌐 English

xviii, 524 p. : 24 cm

Neural Networks for Identification, Pred

📁 Neural Networks for Identification, Prediction and Control

✍ Duc Truong Pham, Xing Liu (auth.) 📂 Library 📅 1995 🏛 Springer-Verlag London 🌐 English

In recent years, there has been a growing interest in applying neural networks to dynamic systems identification (modelling), prediction and control. Neural networks are computing systems characterised by the ability to learn from examples rather than having to be programmed in a conventional sen

DIFFERENTIAL NEURAL NETWORKS FOR ROBUST

📁 DIFFERENTIAL NEURAL NETWORKS FOR ROBUST NONLINEAR CONTROL

✍ Alexander S. Poznyak, Edgar N. Sanchez, Wen Yu 📂 Library 📅 2001 🏛 World Scientific Publishing Company 🌐 English

DIFFERENTIAL NEURAL NETWORKS FOR ROBUST

📁 DIFFERENTIAL NEURAL NETWORKS FOR ROBUST NONLINEAR CONTROL

✍ Alexander S. Poznyak, Edgar N. Sanchez, Wen Yu 📂 Library 📅 2001 🏛 World Scientific Publishing Company 🌐 English

This volume deals with continuous time dynamic neural networks theory applied to the solution of basic problems in robust control theory, including identification, state space estimation (based on neuro-observers) and trajectory tracking. The plants to be identified and controlled are assumed to be

Adaptive Sliding Mode Neural Network Con

📁 Adaptive Sliding Mode Neural Network Control for Nonlinear Systems

✍ Yang Li, Jianhua Zhang, Qiong Wu 📂 Library 📅 2018 🏛 Academic Press 🌐 English

Adaptive Sliding Mode Neural Network Control for Nonlinear Systems introduces nonlinear systems basic knowledge, analysis and control methods, and applications in various fields. It offers instructive examples and simulations, along with the source codes, and provides the basic

Neural Networks for Cooperative Control

📁 Neural Networks for Cooperative Control of Multiple Robot Arms

✍ Shuai Li,Yinyan Zhang (auth.) 📂 Library 📅 2018 🏛 Springer Singapore 🌐 English

This is the first book to focus on solving cooperative control problems of multiple robot arms using different centralized or distributed neural network models, presenting methods and algorithms together with the corresponding theoretical analysis and simulated examples. It is intended for gra