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         "id"   : "https://puma.ub.uni-stuttgart.de/bibtex/248571bf42f9b3e1b94b541f568cd4f0f/isw-bibliothek",         
         "tags" : [
            "compensation","drive","error","feed","isw","learning","machine","tool"
         ],
         
         "intraHash" : "48571bf42f9b3e1b94b541f568cd4f0f",
         "interHash" : "fc115f1ff8efe474a50ffb3153d44a85",
         "label" : "Learning Compensation of the State-Dependent Transmission Errors in Rack-and-Pinion Drives",
         "user" : "isw-bibliothek",
         "description" : "",
         "date" : "2024-07-26 11:59:23",
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         "pub-type": "inproceedings",
         "booktitle": "2024 European Control Conference (ECC)",
         "year": "2024", 
         "url": "", 
         
         "author": [ 
            "Lukas Steinle","Valentin Leipe","Armin Lechler","Alexander Veri"
         ],
         "authors": [
         	
            	{"first" : "Lukas",	"last" : "Steinle"},
            	{"first" : "Valentin",	"last" : "Leipe"},
            	{"first" : "Armin",	"last" : "Lechler"},
            	{"first" : "Alexander",	"last" : "Veri"}
         ],
         "pages": "2441-2447","abstract": "Rack-and-pinion drives are commonly used in large machine tools to provide linear motion of heavy loads over long travel distances. A key concern in this context is the achievable path accuracy, which is limited by assembly and manufacturing tolerances of the gearing components in conjunction with load-dependent deformation and the inherent backlash of the system. To address this issue, this paper presents a method for robust modeling of the individual and state-dependent transmission errors of a drive utilizing a two-stage machine learning approach. Based on this, the position control is extended to include an error compensation, which suppresses the modeled deviations in the mechanical system including the position-dependent backlash. The achievable increase in path accuracy as well as the robustness of the approach are evaluated and quantified by an experimental validation on a system with industry standard components.",
         "doi" : "10.23919/ECC64448.2024.10591213",
         
         "bibtexKey": "10591213"

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         "id"   : "https://puma.ub.uni-stuttgart.de/bibtex/2f698e236a380faddfb8f96d98b28f5bc/inue",         
         "tags" : [
            "myown","network;over-the-air;software-defined","software-defined","from:sdnr","transmissions;open-source","(artificial","systems;block-based","module;transmitter","transmission;receiver","implementations;deep","computing;two-step","nets;radio","intelligence);neural","libraries;continuous","learning;communications","learning;end-to-end","rate;over-the-air","synchronization;frame","error","transmissions;receiver","deep","neural","software","synchronization","data","learning;modulation;neural","learning","libraries;software","radio","implementations;off-the-shelf","networks;NNs;block","procedure;end-to-end","radio;synchronisation;telecommunication","radios;Training;Receivers;Communication","networks;Hardware;Transmitters;Synchronization;Autoencoder;communication;deep","receivers;software","systems;Artificial"
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         "interHash" : "a0e38e6df23c2f25303e9abd1d9fd60d",
         "label" : "Deep Learning Based Communication Over the Air",
         "user" : "inue",
         "description" : "",
         "date" : "2020-03-20 15:07:06",
         "changeDate" : "2020-03-20 14:07:06",
         "count" : 3,
         "pub-type": "article",
         "journal": "IEEE Journal of Selected Topics in Signal Processing",
         "year": "2018", 
         "url": "", 
         
         "author": [ 
            "S. Dörner","S. Cammerer","J. Hoydis","S. ten Brink"
         ],
         "authors": [
         	
            	{"first" : "S.",	"last" : "Dörner"},
            	{"first" : "S.",	"last" : "Cammerer"},
            	{"first" : "J.",	"last" : "Hoydis"},
            	{"first" : "S.",	"last" : "ten Brink"}
         ],
         "volume": "12","number": "1","pages": "132-143",
         "issn" : "1941-0484",
         
         "doi" : "10.1109/JSTSP.2017.2784180",
         
         "bibtexKey": "learning_to_communicate"

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