0506011 20241106135735.920190701235959.9 85071604481 000490488301065 10.23919/ECC.2019.8795702 6 s. C cav_un_epca*0506010978-3-907144-01-51374-1379NaplesEuropean Union Control Association (EUCA)2019 Predictive Control Anisotropic Control Motion Control Stochastic Disturbances cav_un_auth*0101064 50 Belda Květoslav UTIA-B Adaptivní systémy Department of Adaptive Systems AS AS Department of Adaptive Systems Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0376533 50 Tchaikovsky M. RU http://library.utia.cas.cz/separaty/2019/AS/belda-0506011.pdf cav_un_auth*0376535 TN01000024 GA TA ČR CZ The paper deals with the design and comparison of model-based predictive control and anisotropic control formulated for the motion control of industrial robots-manipulators. Stochastic disturbances, usually occurring and entering a control process, are taken into account in the design to attenuate their undesirable influences. The explanation refers a specific online control parameter tuning for predictive control and introduces a single-pass offline optimization for anisotropic control. The aim is to point out features of the proposed advanced approaches in transition situations. cav_un_auth*0376534 European Control Conference 2019 /17./ 20190625 20190628 Naples IT BC 20000 20200 20204 2020 2 4 A sml 4as 20241106135735.9 PR RVO:67985556 http://hdl.handle.net/11104/0297321 cav_un_auth*0376536 The Institute of Control Sciences V.A. Trapeznikov, Russian Academy of Sciences RU S Copyright Form 20190308 Copyright Form 2 Article Engineering Electrical Electronic 2019 Soubory v repozitáři: belda-0506011-CopyrightForm.pdf 85071604481 SCOPUS PUBMED 000490488301065 WOS cav_un_epca*0506010 Proceedings of the 17th European Control Conference 978-3-907144-01-5 1374 1379 Naples European Union Control Association (EUCA) 2019