DocumentCode :
3633866
Title :
A neural net controller for robots with Hebbian tuning and guaranteed tracking
Author :
A. Yesildirek;F.L. Lewis
Author_Institution :
Autom. & Robotics Res. Inst., Texas Univ., Arlington, TX, USA
Volume :
4
fYear :
1995
Firstpage :
2784
Abstract :
A neural network controller structure is developed for general unknown serial-link robot manipulators. The control structure is based on a 3-layer neural network learning on-line using modified Hebbian rules. Under some mild assumptions, a Lyapunov proof guarantees that both tracking error and weight estimate errors are bounded and some specific bounds are given. Using Hebbian tuning rules in each layer of the neural network brings a relatively simple adaptation structure and offers computational advantages over gradient descent based algorithms. Without a preliminary off-line training phase, the network weights are easily initialized to enable on-line learning in real-time.
Keywords :
"Neural networks","Robots","Manipulator dynamics","Robotics and automation","Adaptive control","Automatic control","Biological neural networks","Lifting equipment","Computer networks","Linear feedback control systems"
Publisher :
ieee
Conference_Titel :
American Control Conference, Proceedings of the 1995
Print_ISBN :
0-7803-2445-5
Type :
conf
DOI :
10.1109/ACC.1995.532357
Filename :
532357
Link To Document :
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