شماره ركورد كنفرانس :
3208
عنوان مقاله :
Direct Artificial Neural Network Control of Single Link Flexible Joint
پديدآورندگان :
Farzanegan, Behzad Department of Electrical Engineering - Amirkabir University of Technology , Dehghan Banadaki, Saman Department of Electrical Engineering - Amirkabir University of Technology , Menhaj, Mohammad Bagher Department of Electrical Engineering - Amirkabir University of Technology
كليدواژه :
multilayer perceptoron Neural Network , Flexible joint , Direct Control
عنوان كنفرانس :
چهارمين كنفرانس بين المللي كنترل، ابزار دقيق و اتوماسيون
چكيده لاتين :
the currently existing methods for control of a
flexible joint manipulator have not been desirable precision
because of existence of uncertain and nonlinear dynamics. In this
paper, we propose an online neural network controller for singlelink
flexible joint manipulator. The nonlinear dynamical model
of the manipulator is determined by Lagrange's approach, and
its order is four; however, the model is uncertain. A multi-layer
perceptron neural network consists of three layers with one
hidden layer as a controller. The weights of the proposed
controller are regulated by back propagation error online
approach. The learning rate is carefully selected so that the
output response has a minimum oscillation. The control objective
is high precision tracking the angular displacement trajectory.
The simulation results show the effectiveness of the controller.
