RBFNN Based Inertia Parameters Identification of Robot Dynamics
Author(s):
Dr.P.Kanirajan, Dr.Joly, Mr.Rajesh
ISSN:
2349-6002
Cite This Article:
RBFNN Based Inertia Parameters Identification of Robot DynamicsInternational Journal of Innovative Research in Technology(www.ijirt.org) ,ISSN: 2349-6002 ,Volume 6 ,Issue 5 ,Page(s):197-200 ,October 2019 ,Available :IJIRT148713_PAPER.pdf
Keywords:
RBFNN, Inertia parameters, Weights, Robot dynamics
Abstract
In a robot dynamics the important fields are modeling and controlling of parameters.The Parameters involved in modeling must be improved to have precision control.Here for inertia parameter identification , the robotic arms dynamics were considered and its parameter were transformed in to linear equation for to have accurate model. Radial basis function neural network (RBFNN) is used for identification, in which the input and output parameters were generated just by operating the robotics arms by particular degree of freedom(DOF). Every connecting rod and its inertia parameters are used as the weights for the neural networks.Based on thr error the weight for the RBFNN were adjusted. Finally with the identification results the accurate model parameter was developed and verifies the validity based on the RBFNN.
Article Details
Unique Paper ID: 148713

Publication Volume & Issue: Volume 6, Issue 5

Page(s): 197 - 200
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Last Date 25 September 2019


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