0475621 20240111140941.620170623235959.9 85021793459 000435195200031 10.1109/TCST.2017.2709277 8 s. E cav_un_epca*02532281063-6536264 (2018)1500-1507Institute of Electrical and Electronics Engineers Control identification maximum likelihood (ML) walking robots cav_un_auth*0279330 Dolinský Kamil Teorie řízení Department of Control Theory TŘ TR UTIA-B Department of Control Theory Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0101074 Čelikovský Sergej Teorie řízení Department of Control Theory TŘ TR UTIA-B Department of Control Theory Ústav teorie informace a automatizace AV ČR, v. v. i. článek v odborném periodiku http://library.utia.cas.cz/separaty/2018/TR/dolinsky-0475621.pdf 1,13 MB cav_un_auth*0347203 GA17-04682S GA ČR CZ This brief studies the problem of parameter estimation and model identification for a class of underactuated mechanical systems modeled via the Euler–Lagrange formalism, such as underactuated walking robots. This problem is closely related with the measurement of the absolute orientation during walking. A novel identification method suited for this problem was proposed. The method takes advantage of the linear structure of the model with respect to estimated parameters. The resulting estimator is calculated iteratively and maximizes the likelihood of the data. The method was tested on both simulated and experimental data. Simulation was carried out for an underactuated walking robot with a distance meter to measure absolute orientation. Laboratory experiment was carried out on a leg of a laboratory walking robot model equipped with a three-axis accelerometer and gyroscope to measure absolute orientation. The method performs favorably in comparison with other benchmark estimation algorithms and both the simulation example and the laboratory experiment confirmed its high potential for the use in identification of underactuated robotic walkers. WOS BC 20000 20200 20205 2019 2 4 A hod 4ah 20231122142509.2 RVO:67985556 http://hdl.handle.net/11104/0272293 1 Department of Control Theory UTIA-B 20205 AUTOMATION & CONTROL SYSTEMS S 2 Article Automation Control Systems|Engineering Electrical Electronic ENGINEERING.ELECTRICAL&ELECTRONIC|AUTOMATION&CONTROLSYSTEMS 5.715 2.171 6.2 0.02228 1.538 13739 1.811 5.245 205 Q1 84.752 89.4 Q1 Q1* 1.62 Q1 89.516 2018 Soubory v repozitáři: dolinsky-0475621.pdf 85021793459 SCOPUS PUBMED 000435195200031 WOS článek v odborném periodiku 1,13 MB cav_un_epca*0253228 IEEE Transactions on Control Systems Technology 1063-6536 1558-0865 Roč. 26 č. 4 2018 1500 1507 Institute of Electrical and Electronics Engineers