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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...
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Published in: | IEEE industrial electronics magazine 2007-06, Vol.54 (3), p.1352-1364 |
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container_title | IEEE industrial electronics magazine |
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creator | Orlowska-Kowalska, T. Szabat, K. |
description | 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 |
doi_str_mv | 10.1109/TIE.2007.892637 |
format | article |
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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</description><identifier>ISSN: 0278-0046</identifier><identifier>ISSN: 1932-4529</identifier><identifier>EISSN: 1557-9948</identifier><identifier>DOI: 10.1109/TIE.2007.892637</identifier><identifier>CODEN: ITIED6</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>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</subject><ispartof>IEEE industrial electronics magazine, 2007-06, Vol.54 (3), p.1352-1364</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. 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The simulation results are confirmed by laboratory experiments</description><subject>Computer simulation</subject><subject>Control systems</subject><subject>Control theory</subject><subject>Estimators</subject><subject>Feedback</subject><subject>Laboratories</subject><subject>Mechanical variables control</subject><subject>Neural networks</subject><subject>Neural networks (NNs)</subject><subject>Neurofeedback</subject><subject>Open loop systems</subject><subject>State estimation</subject><subject>state variable estimation</subject><subject>Testing</subject><subject>Torque</subject><subject>Torque control</subject><subject>torsional vibration</subject><subject>two-mass system</subject><subject>Vibration control</subject><issn>0278-0046</issn><issn>1932-4529</issn><issn>1557-9948</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2007</creationdate><recordtype>article</recordtype><recordid>eNqF0TtPwzAUBWALgUQpzAwsFgNMKdfxMyOCApV4DBQkJstJbkQgrYudUvXfkyqIgQGmK1nfsXx9CDlkMGIMsrPpZDxKAfTIZKnieosMmJQ6yTJhtskAUm0SAKF2yV6MbwBMSCYH5OUel8E1yT22Kx_e6fli0dSFa2s_p5UP9A6LVzfvThr67ELt8gYjHce2nvXGV9TR6condy5GehnqT6SP69jibJ_sVK6JePA9h-Tpajy9uEluH64nF-e3SSFE1iaVQS4LoVCVOS9lyXWRgjHoZIE813lephnkZcm5SivDtOYKUJeYpiZnUAk-JKf9vYvgP5YYWzurY4FN4-bol9FmwBUHw7J_pTGgpJGcdfLkT8mFEKA1dPD4F3zzyzDv9rVGdcRItXnhWY-K4GMMWNlF6P4vrC0Du-nOdt3ZTXe2765LHPWJGhF_tGDCgJD8C4f8lAU</recordid><startdate>20070601</startdate><enddate>20070601</enddate><creator>Orlowska-Kowalska, T.</creator><creator>Szabat, K.</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SP</scope><scope>8FD</scope><scope>L7M</scope><scope>F28</scope><scope>FR3</scope></search><sort><creationdate>20070601</creationdate><title>Neural-Network Application for Mechanical Variables Estimation of a Two-Mass Drive System</title><author>Orlowska-Kowalska, T. ; Szabat, K.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c449t-f8e35c46e6db3d5d37c2088ea5ce3b7bbd290bdd3362f8177360e7de228b10f43</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2007</creationdate><topic>Computer simulation</topic><topic>Control systems</topic><topic>Control theory</topic><topic>Estimators</topic><topic>Feedback</topic><topic>Laboratories</topic><topic>Mechanical variables control</topic><topic>Neural networks</topic><topic>Neural networks (NNs)</topic><topic>Neurofeedback</topic><topic>Open loop systems</topic><topic>State estimation</topic><topic>state variable estimation</topic><topic>Testing</topic><topic>Torque</topic><topic>Torque control</topic><topic>torsional vibration</topic><topic>two-mass system</topic><topic>Vibration control</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Orlowska-Kowalska, T.</creatorcontrib><creatorcontrib>Szabat, K.</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) Online</collection><collection>IEEE Xplore Digital Library</collection><collection>CrossRef</collection><collection>Electronics & Communications Abstracts</collection><collection>Technology Research Database</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><collection>Engineering Research Database</collection><jtitle>IEEE industrial electronics magazine</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Orlowska-Kowalska, T.</au><au>Szabat, K.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Neural-Network Application for Mechanical Variables Estimation of a Two-Mass Drive System</atitle><jtitle>IEEE industrial electronics magazine</jtitle><stitle>TIE</stitle><date>2007-06-01</date><risdate>2007</risdate><volume>54</volume><issue>3</issue><spage>1352</spage><epage>1364</epage><pages>1352-1364</pages><issn>0278-0046</issn><issn>1932-4529</issn><eissn>1557-9948</eissn><coden>ITIED6</coden><abstract>This paper deals with the application of neural networks (NNs) to the mechanical state estimation of the drive system with elastic joint. 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issn | 0278-0046 1932-4529 1557-9948 |
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source | IEEE Electronic Library (IEL) Journals |
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 |
title | Neural-Network Application for Mechanical Variables Estimation of a Two-Mass Drive System |
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