Neural-Network Application for Mechanical Variables Estimation of a Two-Mass Drive System

This paper deals with the application of neural networks (NNs) to the mechanical state estimation of the drive system with elastic joint. The torsional vibrations of the two-mass system are damped using the control structure with additional feedbacks from the torsional torque and the load-side speed...

Full description

Saved in:
Bibliographic Details
Published in:IEEE industrial electronics magazine 2007-06, Vol.54 (3), p.1352-1364
Main Authors: Orlowska-Kowalska, T., Szabat, K.
Format: Article
Language:English
Subjects:
Computer simulation
Control systems
Control theory
Estimators
Feedback
Laboratories
Mechanical variables control
Neural networks
Neural networks (NNs)
Neurofeedback
Open loop systems
State estimation
state variable estimation
Testing
Torque
Torque control
torsional vibration
two-mass system
Vibration control
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:This paper deals with the application of neural networks (NNs) to the mechanical state estimation of the drive system with elastic joint. The torsional vibrations of the two-mass system are damped using the control structure with additional feedbacks from the torsional torque and the load-side speed. These feedbacks signals are obtained using NN estimators. The learning procedure of the NNs is described, and the influence of the input vector size to the accuracy of the state-variable estimation is investigated. The neural estimators of the torsional torque and the load machine speed are tested with open-loop and closed-loop control structures. The simulation results are confirmed by laboratory experiments
ISSN:0278-0046
1932-4529
1557-9948
DOI:10.1109/TIE.2007.892637