Title :
Using time-discrete recurrent neural networks in nonlinear control
Author :
Kolb, Thorsten ; Ilg, Winfried ; Wille, Jörg
Author_Institution :
Brandenburg Univ. of Technol., Cottbus, Germany
Abstract :
We introduce a type of fully connected recurrent neural networks (RNN) with special mathematical features which allows one to determine its qualitative dynamical behaviour. Based on this family of RNN we describe a learning framework for the generation of trajectories with which we are able to solve adaptive control problems, which is illustrated by the realization of adaptive leg control of a six-legged walking machine
Keywords :
adaptive control; learning (artificial intelligence); legged locomotion; motion control; neurocontrollers; nonlinear control systems; recurrent neural nets; adaptive control; learning; legged walking machine; mobile robot; neurocontrol; nonlinear control; time-discrete recurrent neural networks; Adaptive control; Backpropagation algorithms; Biological system modeling; Intelligent networks; Leg; Legged locomotion; Machine learning; Programmable control; Recurrent neural networks; Transfer functions;
Conference_Titel :
Neural Networks Proceedings, 1998. IEEE World Congress on Computational Intelligence. The 1998 IEEE International Joint Conference on
Conference_Location :
Anchorage, AK
Print_ISBN :
0-7803-4859-1
DOI :
10.1109/IJCNN.1998.685974
