Title :
Identification and decentralized adaptive control of robotic manipulators using dynamical neural networks
Author :
Karakasoglu, A. ; Sudharsanan, S.I. ; Sundareshan, M.K.
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Arizona, Tucson, AZ
Abstract :
Summary form only given, as follows. A multilayer dynamical neural network together with a supervised training scheme that employs an LMS updating rule was used for the online identification and decentralized adaptive control of multijointed robotic manipulators. Some characteristic features of the control scheme were obtained, and a quantitative evaluation of its performance in terms of tracking desired motions was carried out
Keywords :
adaptive control; computerised control; decentralised control; identification; neural nets; position control; robots; LMS updating rule; decentralized adaptive control; dynamical neural networks; motion tracking; multijointed robotic manipulators; online identification; supervised training; Adaptive control; Backpropagation; Computer networks; Intelligent robots; Least squares approximation; Manipulator dynamics; Motion control; Multi-layer neural network; Neural networks; Robotics and automation;
Conference_Titel :
Neural Networks, 1991., IJCNN-91-Seattle International Joint Conference on
Conference_Location :
Seattle, WA
Print_ISBN :
0-7803-0164-1
DOI :
10.1109/IJCNN.1991.155674
