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Please use this identifier to cite or link to this item: http://eprint.iitd.ac.in/handle/2074/2297

Title: Trajectory tracking of robot manipulator using Gaussian networks
Authors: Behera, L
Gopal, M
Chaudhury, Santanu
Keywords: gaussian networks
inverse and forward dynamics
linear perturbation model
Issue Date: 1994
Citation: Robotics and Autonomous Systems, 13(2), 107-115p.
Abstract: This paper presents a neural network based control scheme for robot tracking applications. Gaussian networks are used to model both the forward and the inverse dynamics of a robot arm. The feedforward torque is actuated by the output of inverse dynamic mapping while the feedback control law is derived using the linear perturbation model of the identified forward dynamics along the desired trajectory. The gradient based learning algorithm is used and the effectiveness of the proposed scheme is highlighted through simulation studies.
URI: http://eprint.iitd.ac.in/dspace/handle/2074/2297
Appears in Collections:Electrical Engineering

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