Identificación experimental de la fricción en las transmisiones accionadas por cable

Vista sencilla de ítem
dc.contributor.advisorGómez-Mendoza, Juan Bernardo
dc.contributor.authorTorres Charry, Giovanni
dc.contributor.researchgroupComputación Aplicada Suave y Dura (Shac)spa
dc.date.accessioned2022-02-15T14:06:31Z
dc.date.available2022-02-15T14:06:31Z
dc.date.issued2022
dc.descriptionilustraciones, gráficos, tablas.spa
dc.description.abstractEn esta tesis se propone un modelo de fricción empírico para transmisiones tipo polea-cable que incluye en su formulación, además de la velocidad, el efecto de la carga externa y la relación de transmisión. Los experimentos para determinar el comportamiento de la fricción se desarrollaron en un banco de pruebas diseñado y construido como parte del proyecto. El banco de pruebas desarrollado permite el cambio de los elementos de la transmisión y la aplicación de carga externa; de esta manera es posible evaluar el comportamiento de la fricción en la transmisión para diferentes valores de velocidad, tipo de enhebre del cable, dimensiones de las poleas y carga externa. Los resultados experimentales obtenidos evidencian la influencia de la carga en el comportamiento de la fricción, se presume que este comportamiento está gobernado principalmente por la fricción en los rodamientos. Como una primera aproximación para la representación de la fricción en la transmisión se utiliza el modelo LuGre, se encuentra que este modelo no representa adecuadamente el comportamiento de la fricción cuando se aplican cargas externas por lo que se propone un nuevo modelo de fricción; este modelo incluye en su formulación el efecto de la carga externa y de la relación de transmisión. Los resultados obtenidos en la validación del modelo propuesto muestran mejores resultados que los obtenidos con el modelo LuGre. Para velocidades inferiores a 30 rad/s y cargas altas, el porcentaje de error de la identificación con el modelo propuesto llega ser hasta cuatro veces inferior al obtenido utilizando el modelo LuGre. Las principales contribuciones de este trabajo son, el desarrollo de un banco de pruebas adaptable, el establecimiento de una linea base para el comportamiento de la fricción en transmisiones tipo polea-cable y la propuesta de un modelo empírico de fricción para este tipo de transmisiones (Texto tomado de la fuente).spa
dc.description.abstractThis thesis proposes an empirical friction model for cable-pulley type transmissions that includes in its formulation, in addition to speed, the effect of external load and transmission ratio. The experiments to determine the friction behavior were carried out on a test bench designed and built as part of the project. The developed test bench allows the change of the transmission elements and the application of external load; in this way, it is possible to evaluate the friction behavior in the transmission for different speed values, types of cable thread, pulley dimensions, and external load. The experimental results obtained show the influence of the load on the friction behavior, it is presumed that this behavior is governed mainly by the friction in the bearings. As a first approximation for the representation of friction in the transmission, the LuGre model is used. It is found that this model does not adequately represent the behavior of friction when external loads are applied, therefore a new friction model is proposed; this model includes in its formulation the effect of the external load and the transmission ratio. The results obtained in the validation of the proposed model show better results than those obtained with the LuGre model. For speeds lower than 30 rad/s and high loads, the percentage of identification error with the proposed model is up to four times lower than that obtained using the LuGre model. The main contributions of this work are the development of an adaptable test bench, the establishment of a baseline for the behavior of friction in cable-pulley type transmissions, and the proposal of an empirical friction model for this type of transmission.eng
dc.description.curricularareaDepartamento de Ingeniería Eléctrica, Electrónica y Computaciónspa
dc.description.degreelevelDoctoradospa
dc.description.degreenameDoctor en Ingeniería - Ingeniería Automáticaspa
dc.format.extentxx, 123 páginasspa
dc.format.mimetypeapplication/pdfspa
dc.identifier.instnameUniversidad Nacional de Colombiaspa
dc.identifier.reponameRepositorio Institucional Universidad Nacional de Colombiaspa
dc.identifier.repourlhttps://repositorio.unal.edu.co/spa
dc.identifier.urihttps://repositorio.unal.edu.co/handle/unal/80984
dc.language.isospaspa
dc.publisherUniversidad Nacional de Colombiaspa
dc.publisher.branchUniversidad Nacional de Colombia - Sede Manizalesspa
dc.publisher.departmentDepartamento de Ingeniería Eléctrica y Electrónicaspa
dc.publisher.facultyFacultad de Ingeniería y Arquitecturaspa
dc.publisher.placeManizales, Colombiaspa
dc.publisher.programManizales - Ingeniería y Arquitectura - Doctorado en Ingeniería - Automáticaspa
dc.relation.referencesJ. Fryman and B. Matthias, “Safety of Industrial Robots : From Conventional to Collaborative Applications.,” in 7th German Conference on Robotics, 2012, pp. 1–5spa
dc.relation.referencesV. Villani, F. Pini, F. Leali, and C. Secchi, “Survey on human–robot collaboration in industrial settings: Safety, intuitive interfaces and applications,” Mechatronics, vol. 55, no. February, pp. 248–266, 2018, doi: 10.1016/j.mechatronics.2018.02.009.spa
dc.relation.referencesW. T. Townsend and J. A. Guertin, “Teleoperator slave - WAM design methodology,” Ind. Robot An Int. J., vol. 26, no. 3, pp. 167–177, 1999, doi: 10.1108/01439919910266820.spa
dc.relation.referencesB. Rooks, “The harmonious robot,” Ind. Robot An Int. J., vol. 33, no. 2, pp. 125–130, Mar. 2006, doi: 10.1108/01439910610651446.spa
dc.relation.referencesA. Pervez and J. Ryu, “Safe physical human robot interaction-past, present and future,” J. Mech. Sci. Technol., vol. 22, no. 3, pp. 469–483, Mar. 2008, doi: 10.1007/s12206-007-1109-3.spa
dc.relation.referencesH. Xiong and X. Diao, “A review of cable-driven rehabilitation devices,” Disabil. Rehabil. Assist. Technol., vol. 15, no. 8, pp. 885–897, 2020, doi: 10.1080/17483107.2019.1629110.spa
dc.relation.referencesM. A. Gull, S. Bai, and T. Bak, “A review on design of upper limb exoskeletons,” Robotics, vol. 9, no. 1, pp. 1–35, 2020, doi: 10.3390/robotics9010016.spa
dc.relation.referencesM. Shoaib, E. Asadi, J. Cheong, and A. Bab-Hadiashar, “Cable Driven Rehabilitation Robots: Comparison of Applications and Control Strategies,” IEEE Access, vol. 9, pp. 110396–110420, Aug. 2021, [Online]. Available: http://arxiv.org/abs/2108.02379.spa
dc.relation.referencesB. Armstrong-Hélouvry, P. Dupont, and C. C. De Wit, “A survey of models, analysis tools and compensation methods for the control of machines with friction,” Automatica, vol. 30, no. 7, pp. 1083–1138, 1994, doi: 10.1016/0005-1098(94)90209-7spa
dc.relation.referencesA. Bonsignore, G. Ferretti, and G. Magnani, “Analytical Formulation of the Classical Friction Model for Motion Analysis and Simulation,” Math. Comput. Model. Dyn. Syst., vol. 5, no. 1, pp. 43–55, 1999spa
dc.relation.referencesP. Dupont, C. Street, V. Hayward, and B. Armstrong, “Single State Elasto-Plastic Models for Friction Compensation ∗,” IEEE Trans. Automat. Contr., vol. 47, no. 5, pp. 787–792, 1999.spa
dc.relation.referencesJ. Swevers, F. Al-Bender, C. G. Ganseman, and T. Projogo, “An integrated friction model structure with improved presliding behavior for accurate friction compensation,” IEEE Trans. Automat. Contr., vol. 45, no. 4, pp. 675–686, Apr. 2000, doi: 10.1109/9.847103.spa
dc.relation.referencesR. H. a. Hensen, M. J. G. J. G. van de Molengraft, and M. Steinbuch, “Frequency domain identification of dynamic friction model parameters,” IEEE Trans. Control Syst. Technol., vol. 10, no. 2, pp. 191–196, 2002, doi: 10.1109/87.987064spa
dc.relation.referencesP. Dupont, V. Hayward, B. Armstrong, and F. Altpeter, “Single state elastoplastic friction models,” IEEE Trans. Automat. Contr., vol. 47, no. 5, pp. 787–792, 2002, doi: 10.1109/TAC.2002.1000274spa
dc.relation.referencesV. Lampaert, J. Swevers, and F. Al-bender, “Experimental Comparison of Different Low-Velocity Tracking,” 10th Mediterr. Conf. Control Autom., 2002spa
dc.relation.referencesV. Lampaert et al., “Measurement and identification of pre-sliding friction dynamics,” Nonlinear Dyn., pp. 0–20, 2003.spa
dc.relation.referencesF. Al-Bender, V. Lampaert, and J. Swevers, “Modeling of dry sliding friction dynamics: From heuristic models to physically motivated models and back,” Chaos, vol. 14, no. 2, pp. 446–460, 2004, doi: 10.1063/1.1741752.spa
dc.relation.referencesD. Kostić, B. de Jager, M. Steinbuch, and R. Hensen, “Modeling and identification for high-performance robot control: An RRR-robotic arm case study,” IEEE Transactions on Control Systems Technology, vol. 12, no. 6. pp. 904–919, 2004, doi: 10.1109/TCST.2004.833641.spa
dc.relation.referencesE. R. D. P. and E. B. C. Francisco J. T. Vargas, “Identification and friction compensation for an industrial robot using two degrees of freedom controllers,” ICARCV 2004 8th Control. Autom. Robot. Vis. Conf. 2004., vol. 2, no. December, pp. 6–9, 2004, doi: 10.1109/ICARCV.2004.1469006.spa
dc.relation.referencesM. R. Kermani, R. V. Patel, and M. Moallem, “Friction identification in robotic manipulators: case studies,” Proc. 2005 IEEE Conf. Control Appl. 2005. CCA 2005., pp. 1170–1175, 2005, doi: 10.1109/CCA.2005.1507289spa
dc.relation.referencesD. D. Rizos and S. D. Fassois, “Friction identification based upon the LuGre and Maxwell slip models,” IFAC Proc. Vol., vol. 16, no. 1, pp. 548–553, 2005, doi: 10.1109/TCST.2008.921809spa
dc.relation.referencesI. Nilkhamhang and A. Sano, “Adaptive friction compensation using the GMS model with polynomial stribeck function,” Proc. IEEE Int. Conf. Control Appl., pp. 1085–1090, 2006, doi: 10.1109/CACSD-CCA-ISIC.2006.4776795spa
dc.relation.referencesJ. Swevers, W. Verdonck, J. De Schutter, and J. De Schutter, “Dynamic Model Identification for Industrial Robots,” IEEE Control Syst. Mag., vol. 27, no. 5, pp. 51–68, 2007, doi: 10.1109/MCS.2007.904659spa
dc.relation.referencesM. R. Kermani, R. V. Patel, and M. Moallem, “Friction identification and compensation in robotic manipulators,” IEEE Trans. Instrum. Meas., vol. 56, no. 6, pp. 2346–2353, 2007, doi: 10.1109/TIM.2007.907957spa
dc.relation.referencesW. Susanto, R. Babuška, F. Liefhebber, and T. van der Weiden, “Adaptive Friction Compensation: Application to a Robotic Manipulator,” IFAC Proc. Vol., vol. 41, no. 2, pp. 2020–2024, 2008, doi: 10.3182/20080706-5-KR-1001.00343.spa
dc.relation.referencesV. Van Geffen, “A study of friction models and friction Compensation,” A study Frict. Model. Frict. Compens., pp. 1–24, 2009, [Online]. Available: http://www.mate.tue.nl/mate/pdfs/11194.pdfspa
dc.relation.referencesM. Indri, I. Lazzero, A. Antoniazza, and A. M. Bottero, “Friction modeling and identification for industrial manipulators,” in 2013 IEEE 18th Conference on Emerging Technologies & Factory Automation (ETFA), Sep. 2013, pp. 1–8, doi: 10.1109/ETFA.2013.6647958.spa
dc.relation.referencesX. Song, H. Liu, K. Althoefer, T. Nanayakkara, and L. D. Seneviratne, “Efficient break-away friction ratio and slip prediction based on haptic surface exploration,” IEEE Trans. Robot., vol. 30, no. 1, pp. 203–219, 2014, doi: 10.1109/TRO.2013.2279630.spa
dc.relation.referencesM. Boegli, T. De Laet, J. De Schutter, and J. Swevers, “A smoothed GMS friction model suited for gradient-based friction state and parameter estimation,” IEEE/ASME Trans. Mechatronics, vol. 19, no. 5, pp. 1593–1602, 2014, doi: 10.1109/TMECH.2013.2288944.spa
dc.relation.referencesA. C. Bittencourt, E. Wernholt, S. Sander-Tavallaey, and T. Brogårdh, “An extended friction model to capture load and temperature effects in robot joints,” in 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems, Oct. 2010, pp. 6161–6167, doi: 10.1109/IROS.2010.5650358.spa
dc.relation.referencesP. Hamon, M. Gautier, P. Garrec, and a. Janot, “Dynamic identification of robot with a load-dependent joint friction model,” 2010 IEEE Conf. Robot. Autom. Mechatronics, RAM 2010, pp. 129–135, 2010, doi: 10.1109/RAMECH.2010.5513201.spa
dc.relation.referencesA. C. Bittencourt and S. Gunnarsson, “Static Friction in a Robot Joint—Modeling and Identification of Load and Temperature Effects,” J. Dyn. Syst. Meas. Control, vol. 134, no. 5, p. 051013, 2012, doi: 10.1115/1.4006589spa
dc.relation.referencesA. C. Bittencourt and P. Axelsson, “Modeling and experiment design for identification of wear in a robot joint under load and temperature uncertainties based on friction data,” IEEE/ASME Trans. Mechatronics, vol. 19, no. 5, pp. 1694–1706, 2014, doi: 10.1109/TMECH.2013.2293001spa
dc.relation.referencesZ. P. Rico, A. Lecchini-Visintini, and R. Q. Quiroga, “Dynamic model of a 7-DOF whole arm manipulator and validation from experimental data,” in ICINCO 2012 - Proceedings of the 9th International Conference on Informatics in Control, Automation and Robotics, 2012, vol. 2, pp. 217–222, doi: 10.5220/0004013002170222spa
dc.relation.referencesH. Olsson, K. K. J. J. Åström, C. Canudas de Wit, M. Gäfvert, and P. Lischinsky, “Friction Models and Friction Compensation,” Eur. J. Control, vol. 4, no. 3, pp. 176–195, 1998, doi: 10.1016/S0947-3580(98)70113-Xspa
dc.relation.referencesE. Berger, “Friction modeling for dynamic system simulation,” Appl. Mech. Rev., vol. 55, no. 6, p. 535, 2002, doi: 10.1115/1.1501080spa
dc.relation.referencesF. Al-Bender and J. Swevers, “Characterization of friction force dynamics,” IEEE Control Syst. Mag., vol. 28, no. 6, pp. 64–81, 2008, doi: 10.1109/MCS.2008.929279spa
dc.relation.referencesS. Buechner, S. Zschaeck, A. Amthor, C. Ament, and M. Eichhorn, “Dynamic friction modeling and identification for high precision mechatronic systems,” IECON 2012 - 38th Annu. Conf. IEEE Ind. Electron. Soc., pp. 2263–2268, 2012, doi: 10.1109/IECON.2012.6388884.spa
dc.relation.referencesL. Márton and B. Lantos, “Modeling, identification, and compensation of stick-slip friction,” IEEE Trans. Ind. Electron., vol. 54, no. 1, pp. 511–521, 2007, doi: 10.1109/TIE.2006.888804.spa
dc.relation.referencesC. Canudas de Wit, P. Noel, a. Aubin, and B. Brogliato, “Adaptive Friction Compensation in Robot Manipulators: Low Velocities,” Int. J. Rob. Res., vol. 10, no. 3, pp. 189–199, 1991, doi: 10.1177/027836499101000301.spa
dc.relation.referencesB. Bona and M. Indri, “Friction compensation in robotics: An overview,” Proc. 44th IEEE Conf. Decis. Control. Eur. Control Conf. CDC-ECC ’05, vol. 2005, pp. 4360–4367, 2005, doi: 10.1109/CDC.2005.1582848.spa
dc.relation.referencesA. C. Bittencourt, E. Wernholt, S. Sander-Tavallaey, and T. Brogårdh, “An extended friction model to capture load and temperature effects in robot joints,” IEEE/RSJ 2010 Int. Conf. Intell. Robot. Syst. IROS 2010 - Conf. Proc., pp. 6161–6167, 2010, doi: 10.1109/IROS.2010.5650358.spa
dc.relation.referencesP. Hamon, a Janot, and S. a Haption, “Dynamic Identification of Robot with a Load- Dependent Joint Friction Model,” Int. Conf. Robot. Autom. Mechatronics, pp. 129–135, 2010spa
dc.relation.referencesP. Hamon, M. Gautier, and P. Garrec, “New dry friction model with load- and velocity-dependence and dynamic identification of multi-dof robots,” Proc. - IEEE Int. Conf. Robot. Autom., pp. 1077–1084, 2011, doi: 10.1109/ICRA.2011.5980126.spa
dc.relation.referencesF. Al-Bender, V. Lampaert, and J. Swevers, “Modeling of dry sliding friction dynamics: From heuristic models to physically motivated models and back,” Chaos, vol. 14, no. 2, pp. 446–460, 2004, doi: 10.1063/1.1741752.spa
dc.relation.referencesP. Dahl, “A solid friction model,” Aerosp. Corp. El Segundo, CA, vol. 158, p. Tech. Rep. TOR-01 58(3 107-1 8)-1, 1968, doi: TOR-0158(3107-18)-1spa
dc.relation.referencesR. Kikuuwe, N. Takesue, A. Sano, H. Mochiyama, and H. Fujimoto, “Fixed-step friction simulation: From classical coulomb model to modern continuous models,” 2005 IEEE/RSJ Int. Conf. Intell. Robot. Syst. IROS, no. 1, pp. 3910–3917, 2005, doi: 10.1109/IROS.2005.1545579.spa
dc.relation.referencesK. J. Åström and C. Canudas-de-wit, “Revisting the LuGre Friction Model,” IEEE Control Syst. Mag., no. December, pp. 101–114, 2008, doi: 10.1109/MCS.2008.929425.spa
dc.relation.referencesC. C. De Wit et al., “A new model for control of systems with friction,” IEEE Trans. Automat. Contr., vol. 40, no. 3, pp. 419–425, 1995, doi: 10.1109/9.376053.spa
dc.relation.referencesB. Armstrong, “Friction: experimental determination, modeling and compensation,” Proceedings. 1988 IEEE Int. Conf. Robot. Autom., pp. 1422–1427, 1988, doi: 10.1109/ROBOT.1988.12266.spa
dc.relation.referencesX. Zhang, Q. Jia, H. Sun, and M. Chu, “Adaptive control of manipulator flexible-joint with friction compensation using LuGre model,” 2008 3rd IEEE Conf. Ind. Electron. Appl. ICIEA 2008, pp. 1234–1239, 2008, doi: 10.1109/ICIEA.2008.4582716.spa
dc.relation.referencesB. Zhong, L. Sun, L. Chen, and Z. Wang, “The dynamics study of the stick-slip driving system based on LuGre dynamic friction model,” 2011 IEEE Int. Conf. Mechatronics Autom. ICMA 2011, pp. 584–589, 2011, doi: 10.1109/ICMA.2011.5985726.spa
dc.relation.referencesA. C. Bittencourt and S. Gunnarsson, “Static Friction in a Robot Joint—Modeling and Identification of Load and Temperature Effects,” J. Dyn. Syst. Meas. Control, vol. 134, no. 5, p. 51013, 2012, doi: 10.1115/1.4006589spa
dc.relation.referencesM. S. Madi, K. Khayati, and P. Bigras, “Parameter estimation for the LuGre friction model using interval analysis and set inversion,” Syst. Man Cybern. 2004 IEEE Int. Conf., vol. 1, pp. 428–433 vol.1, 2004, doi: 10.1109/ICSMC.2004.1398335spa
dc.relation.referencesS. Sobczyk and a Eduardo, “A continuous approximation of the lugre friction model,” ABCM Symp. Ser. Mechatronics, vol. 4, pp. 218–228, 2010.spa
dc.relation.referencesN. Barabanov and R. Ortega, “Necessary and sufficient conditions for passivity of the LuGre friction model,” IEEE Trans. Automat. Contr., vol. 45, no. 4, pp. 830–832, 2000, doi: 10.1109/9.847131.spa
dc.relation.referencesZ. Wenjing, “Parameter Identification of LuGre Friction Model in Servo Sys- tem Based on Improved Particle Swarm Optimization Algorithm,” Proc. 26th Chinese Control Conf., pp. 135–139, 2007, doi: 10.1109/CHICC.2006.4346908spa
dc.relation.referencesD. Liu, “Parameter identification for LuGre friction model using genetic algorithms,” Proc. Fifth Int. Conf. Mach. Learn. Cybern., no. August, pp. 13–16, 2006, doi: 10.1109/ICMLC.2006.258506.spa
dc.relation.referencesX. Wang, S. Lin, and S. Wang, “Dynamic Friction Parameter Identification Method with LuGre Model for Direct-Drive Rotary Torque Motor,” Math. Probl. Eng., vol. 2016, 2016, doi: 10.1155/2016/6929457spa
dc.relation.referencesX. Hongbiao, Q. Zurong, and L. Xingfei, “Simulation and experimental research of non-linear friction compensation for high-precision ball screw drive system,” ICEMI 2009 - Proc. 9th Int. Conf. Electron. Meas. Instruments, pp. 3604–3609, 2009, doi: 10.1109/ICEMI.2009.5274257.spa
dc.relation.referencesR. Dhaouadi, F. H. Ghorbel, and P. S. Gandhi, “A New Dynamic Model of Hysteresis in Harmonic Drives,” IEEE Trans. Ind. Electron., vol. 50, no. 6, pp. 1165–1171, 2003, doi: 10.1109/TIE.2003.819661spa
dc.relation.referencesL. Freidovich, a. Robertsson, a. Shiriaev, and R. Johansson, “Friction compensation based on LuGre model,” Proc. 45th IEEE Conf. Decis. Control, no. 6, pp. 9–12, 2006, doi: 10.1109/CDC.2006.376780.spa
dc.relation.referencesG. Palli and C. Melchiorri, “Modelling and control of robotic joints based on sliding pairs,” 2013 IEEE/ASME Int. Conf. Adv. Intell. Mechatronics Mechatronics Hum. Wellbeing, AIM 2013, pp. 1743–1748, 2013, doi: 10.1109/AIM.2013.6584349.spa
dc.relation.referencesX. Song, H. Liu, K. Althoefer, T. Nanayakkara, and L. D. Seneviratne, “Efficient break-away friction ratio and slip prediction based on haptic surface exploration,” IEEE Trans. Robot., vol. 30, no. 1, pp. 203–219, 2014, doi: 10.1109/TRO.2013.2279630.spa
dc.relation.referencesJ. Swevers, F. Al-Bender, C. G. Ganseman, and T. Projogo, “An integrated friction model structure with improved presliding behavior for accurate friction compensation,” IEEE Trans. Automat. Contr., vol. 45, no. 4, pp. 675–686, Apr. 2000, doi: 10.1109/9.847103.spa
dc.relation.referencesG. Ferretti, G. Magnani, and P. Rocco, “Single and multistate integral friction models,” IEEE Trans. Automat. Contr., vol. 49, no. 12, pp. 2292–2297, 2004, doi: 10.1109/TAC.2004.839234.spa
dc.relation.referencesS. Bograd, P. Reuss, a. Schmidt, L. Gaul, and M. Mayer, “Modeling the dynamics of mechanical joints,” Mech. Syst. Signal Process., vol. 25, no. 8, pp. 2801–2826, 2011, doi: 10.1016/j.ymssp.2011.01.010spa
dc.relation.referencesP. Dupont, B. Armstrong, and V. Hayward, “Elasto-plastic friction model: contact compliance and stiction,” Proc. 2000 Am. Control Conf. ACC (IEEE Cat. No.00CH36334), vol. 2, no. June, pp. 1072–1077, 2000, doi: 10.1109/ACC.2000.876665.spa
dc.relation.referencesF. Al-Bender, V. Lampaert, and J. Swevers, “The generalized Maxwell-slip model: A novel model for friction simulation and compensation,” IEEE Trans. Automat. Contr., vol. 50, no. 11, pp. 1883–1887, 2005, doi: 10.1109/TAC.2005.858676.spa
dc.relation.referencesM. W. van der Kooij, “Model based friction compensation for an electromechanical Stewart platform actuator,” Delft University of Technology, 2011.spa
dc.relation.referencesR. Isermann and M. Münchhof, Identification of Dynamic Systems. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011spa
dc.relation.referencesC. CHEN, “Friction modeling and experimental identification of a mitsubishi PA10-6CE robot manipulator,” University of Florida, 2013.spa
dc.relation.referencesM. Ruderman, “Discrete-time series identification of sliding dynamic friction in industrial robotic joints,” IEEE Int. Conf. Intell. Robot. Syst., pp. 5809–5814, 2013, doi: 10.1109/IROS.2013.6697197.spa
dc.relation.referencesM. N. Nevmerzhitskiy, A. V Vara, and K. V Zmeu, “Technique for Friction Model Identification in an Industrial Robot Joint Using KUKA KR10,” 2018 Int. Multi-Conference Ind. Eng. Mod. Technol., no. 02, pp. 1–5, 2018.spa
dc.relation.referencesP. Hamon, M. Gautier, and P. Garrec, “New Dry Friction Model with Load- and Velocity-Dependence and Dynamic Identification of Multi-DOF Robots,” pp. 1077–1084, 2015.spa
dc.relation.referencesJ. Swevers, F. Al-Bender, C. G. Ganseman, and T. Projogo, “An integrated friction model structure with improved presliding behavior for accurate friction compensation,” IEEE Trans. Automat. Contr., vol. 45, no. 4, pp. 675–686, Apr. 2000, doi: 10.1109/9.847103.spa
dc.relation.referencesL. Simoni et al., “On the use of a temperature based friction model for a virtual force sensor in industrial robot manipulators,” IEEE Int. Conf. Emerg. Technol. Fact. Autom. ETFA, pp. 1–6, 2018, doi: 10.1109/ETFA.2017.8247655.spa
dc.relation.referencesM. Iwatani and R. Kikuuwe, “An identification procedure for rate-dependency of friction in robotic joints with limited motion ranges,” Mechatronics, vol. 36, pp. 36–44, 2016, doi: 10.1016/j.mechatronics.2016.04.002.spa
dc.relation.referencesT. D. Tuttle and W. P. Seering, “A nonlinear model of a harmonic drive gear transmission,” IEEE Trans. Robot. Autom., vol. 12, no. 3, pp. 368–374, 1996, doi: 10.1109/70.499819.spa
dc.relation.referencesH. D. Taghirad and P. R. Bélanger, “Modelling and Parameter Identification of Harmonic Drive Systems,” J. Dyn. Syst. Meas. Control, vol. 120, pp. 439–444, 1998, doi: 10.1115/1.2801484spa
dc.relation.referencesP. S. S. Gandhi, F. H. H. Ghorbel, and J. Dabney, “Modeling, identification, and compensation of friction in harmonic drives,” Proc. 41st IEEE Conf. Decis. Control. 2002., vol. 1, no. December, 2002, doi: 10.1109/CDC.2002.1184485.spa
dc.relation.referencesWenjie Chen, Kyoungchul Kong, and M. Tomizuka, “Dual-Stage Adaptive Friction Compensation for Precise Load Side Position Tracking of Indirect Drive Mechanisms,” IEEE Trans. Control Syst. Technol., vol. 23, no. 1, pp. 164–175, Jan. 2015, doi: 10.1109/TCST.2014.2317776.spa
dc.relation.referencesJ. Baur, S. Dendorfer, J. Pfaff, C. Schutz, T. Buschmann, and H. Ulbrich, “Experimental friction identification in robot drives,” in 2014 IEEE International Conference on Robotics and Automation (ICRA), May 2014, pp. 6006–6011, doi: 10.1109/ICRA.2014.6907744.spa
dc.relation.referencesY. Lu and D. Fan, “Transmission backlash of precise cable drive system,” Proc. Inst. Mech. Eng. Part C J. Mech. Eng. Sci., vol. 227, no. 10, pp. 2256–2267, Oct. 2013, doi: 10.1177/0954406212473887.spa
dc.relation.referencesO. Baser and E. Ilhan Konukseven, “Theoretical and experimental determination of capstan drive slip error,” Mech. Mach. Theory, vol. 45, no. 6, pp. 815–827, 2010, doi: 10.1016/j.mechmachtheory.2009.10.013.spa
dc.relation.referencesJ. Werkmeister and A. Slocum, “Theoretical and experimental determination of capstan drive stiffness,” Precis. Eng., vol. 31, no. 1, pp. 55–67, 2007, doi: 10.1016/j.precisioneng.2006.03.001spa
dc.relation.referencesX. Xie, C. Qi, L. Zhang, and D. Fan, “Analytical and experimental research on transmission backlash in precise cable drive for an electro-optical targeting system,” Adv. Mech. Eng., vol. 11, no. 7, p. 168781401986605, Jul. 2019, doi: 10.1177/1687814019866059.spa
dc.relation.referencesJ. Hwangbo, V. Tsounis, H. Kolvenbach, and M. Hutter, “Cable-Driven Actuation for Highly Dynamic Robotic Systems,” in 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Oct. 2018, pp. 8543–8550, doi: 10.1109/IROS.2018.8593569spa
dc.relation.referencesP. Hamon, M. Gautier, and P. Garrec, “New dry friction model with load- and velocity-dependence and dynamic identification of multi-dof robots,” Proc. - IEEE Int. Conf. Robot. Autom., pp. 1077–1084, 2011, doi: 10.1109/ICRA.2011.5980126.spa
dc.relation.referencesL. Ding, H. Wu, Y. Yao, and Y. Yang, “Dynamic model identification for 6-DOF industrial robots,” J. Robot., vol. 2015, no. 5, pp. 51–68, 2015, doi: 10.1155/2015/471478.spa
dc.relation.referencesA. C. Bittencourt, E. Wernholt, S. Sander-Tavallaey, and T. Brogårdh, “An extended friction model to capture load and temperature effects in robot joints,” in 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems, Oct. 2010, pp. 6161–6167, doi: 10.1109/IROS.2010.5650358spa
dc.relation.referencesA. C. Bittencourt and P. Axelsson, “Modeling and Experiment Design for Identification of Wear in a Robot Joint Under Load and Temperature Uncertainties Based on Friction Data,” IEEE/ASME Trans. Mechatronics, vol. 19, no. 5, pp. 1694–1706, Oct. 2014, doi: 10.1109/TMECH.2013.2293001.spa
dc.relation.referencesW. Susanto, R. Babuška, F. Liefhebber, and T. van der Weiden, “Adaptive Friction Compensation: Application to a Robotic Manipulator,” IFAC Proc. Vol., vol. 41, no. 2, pp. 2020–2024, 2008, doi: 10.3182/20080706-5-KR-1001.00343.spa
dc.relation.referencesD. Liu, “Parameter Identification for Lugre Friction Model using Genetic Algorithms,” in 2006 International Conference on Machine Learning and Cybernetics, 2006, vol. 2006, no. August, pp. 3419–3422, doi: 10.1109/ICMLC.2006.258506.spa
dc.relation.referencesX. Wang, S. Lin, and S. Wang, “Dynamic Friction Parameter Identification Method with LuGre Model for Direct-Drive Rotary Torque Motor,” Math. Probl. Eng., vol. 2016, pp. 1–8, 2016, doi: 10.1155/2016/6929457.spa
dc.relation.referencesD. Liu, “Parameter Identification for Lugre Friction Model using Genetic Algorithms,” in 2006 International Conference on Machine Learning and Cybernetics, 2006, no. August, pp. 3419–3422, doi: 10.1109/ICMLC.2006.258506.spa
dc.relation.referencesJ. Swevers, F. Al-Bender, C. G. Ganseman, and T. Projogo, “An integrated friction model structure with improved presliding behavior for accurate friction compensation,” IEEE Trans. Automat. Contr., vol. 45, no. 4, pp. 675–686, Apr. 2000, doi: 10.1109/9.847103.spa
dc.relation.referencesP. Feyel, G. Duc, and G. Sandou, “LuGre Friction Model Identification and Compensator Tuning Using A Differential Evolution Algorithm,” no. 1, pp. 85–91, 2013.spa
dc.relation.referencesD. Liu, “Research on parameter identification of friction model for servo systems based on genetic algorithms,” Mach. Learn., no. August, pp. 18–21, 2005.spa
dc.relation.referencesR. Waiboer, “Dynamic modelling, identification and simulation of industrial robots,” Universiteit Twente, 2007.spa
dc.relation.referencesP. Lischinsky, C. Canudas-de-Wit, and G. Morel, “Friction Compensation for an Industrial Hydraulic Robot,” IEEE Control Syst., vol. 19, no. 1, pp. 25–32, 1999, doi: 10.1109/37.745763.spa
dc.relation.referencesF. J. T. J. T. Vargas, E. R. D. R. De Fieri, and E. B. B. Castelan, “Identification and friction compensation for an industrial robot using two degrees of freedom controllers,” ICARCV 2004 8th Control. Autom. Robot. Vis. Conf. 2004., vol. 2, no. December, pp. 6–9, 2004, doi: 10.1109/ICARCV.2004.1469006.spa
dc.relation.referencesW. T. Townsend, “United States Patent [ 191 Patent Number : Date of Patent :,” 1995.spa
dc.relation.referencesChristiand, J. Yoon, and P. Kumar, “A novel optimal assembly algorithm for haptic interface applications of a virtual maintenance system,” J. Mech. Sci. Technol., vol. 23, no. 1, pp. 183–194, 2009, doi: 10.1007/s12206-008-0902-y.spa
dc.relation.referencesY. Wang, Y. Shen, D. Liu, S. Wei, and C. Zhu, “Key technique of assembly system in an augmented reality environment,” ICCMS 2010 - 2010 Int. Conf. Comput. Model. Simul., vol. 1, pp. 133–137, 2010, doi: 10.1109/ICCMS.2010.201.spa
dc.relation.referencesM. Karray, F. Chaari, A. F. Del Rincon, F. Viadero, and M. Haddar, “An Experimental Investigation of the Dynamic Behavior of Planetary Gear Set,” no. 2003, M. Haddar, L. Romdhane, J. Louati, and A. Ben Amara, Eds. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013, pp. 199–206.spa
dc.relation.referencesA. Fernández del Rincón, R. Cerdá, M. Iglesias, A. De-Juan, P. García, and F. Viadero, “Test Bench for the Analysis of Dynamic Behavior of Planetary Gear Transmissions,” in Lecture Notes in Mechanical Engineering, vol. 5, 2014, pp. 485–495spa
dc.relation.referencesS. S. Khodwe, U. S. Cherekar, and S. S. Prabhune, “Design and Analysis of Gear Box Test Bench to Test Shift Performance and Leakage,” Int. J. Adv. Res. Innov. Ideas Educ., vol. 1, no. 2, pp. 270–280, 2015.spa
dc.relation.referencesA. Mazumdar et al., “Synthetic Fiber Capstan Drives for Highly Efficient, Torque Controlled, Robotic Applications,” IEEE Robot. Autom. Lett., vol. 2, no. 2, pp. 554–561, Apr. 2017, doi: 10.1109/LRA.2016.2646259spa
dc.relation.referencesN. Dumitru, E. Dragut, N. Craciunoiu, and I. Geonea, “Experimental Bench for Spur Gears Efficiency Measurement,” in Mechanisms and Machine Science, vol. 57, Springer International Publishing, 2018, pp. 477–485spa
dc.relation.referencesX. Xie, C. Qi, R. Tan, and D. Fan, “Design and performance analysis of a many-to-one configuration precise cable drive mechanism with high precision and large torque,” Proc. Inst. Mech. Eng. Part C J. Mech. Eng. Sci., vol. 233, no. 16, pp. 5903–5915, Aug. 2019, doi: 10.1177/0954406219849450.spa
dc.relation.referencesY. Lu and D. Fan, “Non-intervene cable wrapping method for precise cable drive,” in 2012 International Conference on Optoelectronics and Microelectronics, Aug. 2012, no. 1, pp. 378–383, doi: 10.1109/ICoOM.2012.6316294spa
dc.relation.referencesR. A. Mitchell and S. M. Baker, “Characterizing the Creep Response of Load Cells.,” VDI Ber, no. 31, pp. 43–48, 1978.spa
dc.relation.referencesM. Spoor, “Improving Creep Performance of the Strain Gage Based Load Cell,” Mech. Probl. Meas. Force Mass, pp. 293–302, 1986, doi: 10.1007/978-94-009-4414-5_34.spa
dc.relation.referencesT. W. Bartel and S. L. Yaniv, “Creep and creep recovery response of load cells tested according to U.S. and international evaluation procedures,” J. Res. Natl. Inst. Stand. Technol., vol. 102, no. 3, pp. 349–362, 1997, doi: 10.6028/jres.102.024.spa
dc.relation.referencesMakoto Makabe and Toru Kohashi, “High accurate Creep compensation method for Load Cell,” in SICE Annual Conference 2007, Sep. 2007, pp. 29–36, doi: 10.1109/SICE.2007.4420945.spa
dc.relation.referencesM. I. Mohamed, E. H. Hasan, and G. Aggag, “Study of creep behavior of load cells,” Meas. J. Int. Meas. Confed., vol. 42, no. 7, pp. 1006–1010, 2009, doi: 10.1016/j.measurement.2009.03.001.spa
dc.relation.referencesA. Ohtsuka, T. Koyama, T. Kohashi, and M. Adachi, “Digital creep compensation method for load cell in various loading patterns,” ICCAS-SICE 2009 - ICROS-SICE Int. Jt. Conf. 2009, Proc., pp. 369–373, 2009spa
dc.relation.referencesA. Ohtsuka, T. Kohashi, and M. Adachi, “Self-optimization of digital creep compensation parameter for load cell,” Proc. SICE Annu. Conf., pp. 1456–1460, 2012.spa
dc.relation.referencesCarl Stahl Sava Industries (savacable.com), “Design Guide for Cable Solutions TM,” WHITEPAPER - Carl Stahl Sava Ind., 2010.spa
dc.relation.referencesE. R. Snow, “The load/deflection behavior of pretensioned cable/pulley transmission mechanisms,” Massachusetts Institute of Technology, 1993spa
dc.relation.referencesY. Lu, D. Fan, H. Liu, and M. Hei, “Transmission capability of precise cable drive including bending rigidity,” Mech. Mach. Theory, vol. 94, pp. 132–140, 2015, doi: 10.1016/j.mechmachtheory.2015.07.004.spa
dc.relation.referencesO. Baser and E. I. Konukseven, “Theoretical and experimental determination of capstan drive slip error,” Mech. Mach. Theory, vol. 45, no. 6, pp. 815–827, 2010, doi: 10.1016/j.mechmachtheory.2009.10.013spa
dc.relation.referencesS. N. Kosari, S. Ramadurai, H. J. Chizeck, and B. Hannaford, “Control and Tension Estimation of a Cable Driven Mechanism Under Different Tensions,” in Volume 6A: 37th Mechanisms and Robotics Conference, Aug. 2013, pp. 1–9, doi: 10.1115/DETC2013-13548.spa
dc.relation.referencesM. Miyasaka, M. Haghighipanah, Y. Li, J. Matheson, A. Lewis, and B. Hannaford, “Modeling Cable-Driven Robot with Hysteresis and Cable-Pulley Network Friction,” IEEE/ASME Trans. Mechatronics, vol. 25, no. 2, pp. 1095–1104, 2020, doi: 10.1109/TMECH.2020.2973428.spa
dc.relation.referencesR. J. E. Merry, Wavelet Theory and Its Applications - A literature study. Eindhoven University of Technology, 2005.spa
dc.relation.referencesD. Giaouris et al., “Wavelet Denoising for Electric Drives,” IEEE Trans. Ind. Electron., vol. 55, no. 2, pp. 543–550, 2008, doi: 10.1109/TIE.2007.911943spa
dc.relation.referencesM. Misiti, Y. Misiti, G. Oppenheim, and J.-M. Poggi, “Wavelet Toolbox TM User ’ s Guide,” p. 700, 2015, [Online]. Available: http://www.mathworks.com/help/pdf_doc/wavelet/wavelet_ug.pdf.spa
dc.relation.referencesF. Al-Bender and J. Swevers, “Characterization of Friction Force Dynamics BEHAVIOR AND MODELING ON MICRO AND MACRO SCALES,” IEEE Control Syst. Mag., no. December, pp. 64–81, 2008.spa
dc.relation.referencesX. Hua, J. C. Puoza, P. Zhang, X. Xie, and B. Yin, “Experimental analysis of grease friction properties on sliding textured surfaces,” Lubricants, vol. 5, no. 4, pp. 1–11, 2017, doi: 10.3390/lubricants5040042.spa
dc.rights.accessrightsinfo:eu-repo/semantics/openAccessspa
dc.rights.licenseAtribución-NoComercial-SinDerivadas 4.0 Internacionalspa
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/spa
dc.subject.armarcFriction (Mechanical)eng
dc.subject.armarcTribología -- Tesis y disertaciones académicas.spa
dc.subject.ddc620 - Ingeniería y operaciones afines::629 - Otras ramas de la ingenieríaspa
dc.subject.lembFricción (Mecánica)spa
dc.subject.proposalModelo de fricciónspa
dc.subject.proposalTransmisiónspa
dc.subject.proposalPolea-cablespa
dc.subject.proposalEquipo de pruebasspa
dc.subject.proposalCreepspa
dc.subject.proposalFriction modeleng
dc.subject.proposalCable-driven transmissioneng
dc.subject.proposalTest equipmenteng
dc.titleIdentificación experimental de la fricción en las transmisiones accionadas por cablespa
dc.title.translatedExperimental identification of friction in cable-driven transmissionseng
dc.typeTrabajo de grado - Doctoradospa
dc.type.coarhttp://purl.org/coar/resource_type/c_db06spa
dc.type.coarversionhttp://purl.org/coar/version/c_ab4af688f83e57aaspa
dc.type.contentImagespa
dc.type.contentTextspa
dc.type.driverinfo:eu-repo/semantics/doctoralThesisspa
dc.type.versioninfo:eu-repo/semantics/acceptedVersionspa
dcterms.audience.professionaldevelopmentEstudiantesspa
dcterms.audience.professionaldevelopmentInvestigadoresspa
dcterms.audience.professionaldevelopmentPúblico generalspa
oaire.accessrightshttp://purl.org/coar/access_right/c_abf2spa

Archivos

Bloque original

Mostrando 1 - 1 de 1
Miniatura
Nombre:
7914507.2022.pdf
Tamaño:
6.24 MB
Formato:
Adobe Portable Document Format
Descripción:
Tesis de Doctorado en Ingeniería - Automática
Descargar

Bloque de licencias

Mostrando 1 - 1 de 1
Miniatura
Nombre:
license.txt
Tamaño:
3.98 KB
Formato:
Item-specific license agreed upon to submission
Descripción:
Descargar

Colecciones

Doctorado en Ingeniería - Automática