Speed Control of Two-Mass Elastic System by On-line Trained Neural Network based on Kalman Filter Estimation

Tomasz Pajchrowski; Dariusz Janiszewski

Scientific Information System of the Poznań University of Technology

PL EN

Main page / Publications / Speed Control of Two-Mass Elastic System by On-line Trained Neural Network based on Kalman Filter Estimation

Submit a comment

Chapter

Download BibTeX

Title

Speed Control of Two-Mass Elastic System by On-line Trained Neural Network based on Kalman Filter Estimation

Authors

Tomasz Pajchrowski (WE) ^{[ 1 ][ P ]}
Dariusz Janiszewski (WE) ^{[ 1 ][ P ]}

^{[ 1 ]} Instytut Automatyki i Inżynierii Informatycznej, Wydział Elektryczny, Politechnika Poznańska | ^{[ P ]} employee

Year of publication

2014

Chapter type

paper

Publication language

english

Abstract

EN The article presents the problem of adaptive motor control for the two mass drive system with elasticity using online trained neural speed controller, where controlled signals obtain by Kalman Filter. Structure of the controller with training algorithm and idea of KF are shortly described. For ANN training process the Resilient Back Propagation algorithm (RPROP) was chosen. Only the measurement of motor position assumed as being sufficient to the possibility of torsional vibration damping. Results, in change to drive system parameters, are presented.

Pages (from - to)

171 - 172

Book

XXIII Symposium Electromagnetic Phenomena in Nonlinear Circuits : EPNC 2014 : proceedings, Pilsen, Czech Republic, 2-4 July, 2014

Presented on

XXIII Symposium on Electromagnetic Phenomena in Nonlinear Circuits, EPNC 2014, 2-4.07.2014, Pilsen, Czech Republic

System created by Poznań University of Technology and Poznan Supercomputing and Networking Center

Log in through eKonto to add to SIS