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Abstrakty
System identification is an approach for parameter detection and mathematical model determination using response signals of a dynamic system. Two degrees of freedom (2DOF) pendulum controlled by a QUBE-servo motor is a great experiment device to work with; though it is not easy to control this system due to its complex structure and multi-dimensional outputs. Hence, system identification is required for this system to analyze and evaluate its dynamic behaviors. This paper presents a methodology for identifying a 2DOF pendulum and its dynamic behaviors including noise from an encoder cable. Firstly, all parameters from both mechanical and electrical sides of the QUBE-servo motor are analyzed. Secondly, a mathematical model and identified parameters for the 2DOF pendulum are illustrated. Finally, disturbances from encoder cable of the QUBE-servo motor which introduce an unwanted oscillation or self-vibration in this system are introduced. The effect of itself on output response signals of the 2DOF QUBE-pendulum is also discussed. All identified parameters are checked and verified by a comparison between a theoretical simulation and experimental results. It is found that the disturbance from encoder cable of the 2DOF QUBE-pendulum is not negligible and should be carefully considered as a certain factor affecting response of system.
Wydawca
Czasopismo
Rocznik
Tom
Strony
435--450
Opis fizyczny
Bibliogr. 25 poz., rys., tab., wykr.
Twórcy
autor
- Faculty of Mechanical Engineering, The University of Danang – University of Science and Technology, Danang, Vietnam
autor
- Faculty of Mechanical Engineering, The University of Danang – University of Science and Technology, Danang, Vietnam
autor
- Faculty of Mechanical Engineering, The University of Danang – University of Science and Technology, Danang, Vietnam
autor
- Faculty of Mechanical Engineering, The University of Danang – University of Science and Technology, Danang, Vietnam
Bibliografia
- [1] H. Hjalmarsson. System identification of complex and structured systems. European Journal of Control, 15(3-4): 275–310, 2019. doi: 10.3166/ejc.15.275-310.
- [2] L. Ljung. System Identification: Theory for the User. 2nd edition, Pearson, 1998.
- [3] P.V. Dang, S. Chatterton, P. Pennacchi, and A. Vania. Numerical investigation of the effect of manufacturing errors in pads on the behaviour of tilting-pad journal bearings. Proceedings of the Institution of Mechanical Engineers, Part J: Journal of Engineering Tribology, 232(4):480– 500, 2018. doi: 10.1177/1350650117721118.
- [4] P.V. Dang, S. Chatterton, and P. Pennacchi. The effect of the pivot stiffness on the performances of five-pad tilting pad bearings. Lubricants, 7(7):61, 2019. doi: 10.3390/lubricants7070061.
- [5] S. Chatterton, P. Pennacchi, A. Vania, and P.V. Dang. Cooled pads for tilting-pad journal bearings. Lubricants, 7(10):92, 2019. doi: 10.3390/lubricants7100092.
- [6] S. Chatterton, P. Pennacchi, A. Vania, A. De Luca, and P.V. Dang. Tribo-design of lubricants for power loss reduction in the oil-film bearings of a process industry machine: Modelling and experimental tests. Tribology International, 130:133–145, 2019. doi: 10.1016/j.triboint.2018.09.014.
- [7] M.Q. Phan and J.A. Frueh. System identification and learning control. In: Z. Bien, J-X. Xu, editors, Iterative Learning Control, chapter 15, pages 285–310. Springer, Boston, MA, 1998. doi: 10.1007/978-1-4615-5629-9_15.
- [8] C. Shravankumar and R. Tiwari. Experimental identification of cracked rotor system parameters from the forward and backward whirl responses. Archive of Mechanical Engineering, 66(3):329– 353, 2019. doi: 10.24425/ame.2019.129679.
- [9] D.K. Roy and R. Tiwari. Development of identification procedure for the internal and external damping in a cracked rotor system undergoing forward and backward whirls. Archive of Mechanical Engineering, 66(2):229–255, 2019. doi: 10.24425/ame.2019.128446.
- [10] A. Wadi, J. Lee, and L. Romdhane. Nonlinear sliding mode control of the Furuta pendulum. 2018 11th International Symposium on Mechatronics and its Applications (ISMA), Sharjah, United Arab Emirates, 4–6 March 2018. doi: 10.1109/ISMA.2018.8330131.
- [11] J.L.D. Madrid, E.A.G. Querubín, and P.A. Ospina-Henao. Predictive control of a Furata pendulum. 2017 IEEE 3rd Colombian Conference on Automatic Control (CCAC), Cartagena, Colombia, 18–20 October, 2017. doi: 10.1109/CCAC.2017.8276483.
- [12] I. Paredes, M. Sarzosa, M. Herrera, P. Leica, and O. Camacho. Optimal-robust controller for Furuta pendulum based on linear model. 2017 IEEE Second Ecuador Technical Chapters Meeting (ETCM), Salinas, Equador, 16–20 October, 2017. doi: 10.1109/ETCM.2017.8247510.
- [13] M. Antonio-Cruz, R. Silva-Ortigoza, J. Sandoval-Gutiérrez, C.A. Merlo-Zapata, H. Taud, C. Márquez-Sánchez, and V.M. Hernández-Guzmán. Modeling, simulation, and construction of a Furuta pendulum test-bed. 2015 International Conference on Electronics, Communications and Computers (CONIELECOMP), pages 72–79, Cholula, Mexico, 25–27 February, 2015. doi: 10.1109/CONIELECOMP.2015.7086928.
- [14] P.X. La Hera, L.B. Freidovich, A.S. Shiriaev, and U. Mettin. New approach for swinging up the Furuta pendulum: Theory and experiments. Mechatronics, 19(8):1240–1250, 2009. doi: 10.1016/j.mechatronics.2009.07.005.
- [15] K. Furuta and M. Iwase. Swing-up time analysis of pendulum. Bulletin of the Polish Academy of Sciences: Technical Sciences, 52(3):153–163, 2004.
- [16] K. Andrzejewski, M. Czyżniewski, M. Zielonka, E. Łangowski, and T. Zubowicz. A comprehensive approach to double inverted pendulum modelling. Archives of Control Sciences, 29(3):459–483, 2019. doi: 10.24425/acs.2019.130201.
- [17] M. Gäfvert, J. Svensson, and K.J. Astrom. Friction and friction compensation in the Furuta pendulum. 1999 European Control Conference (ECC), pages 3154–3159, Karlsruhe, Germany, 31 August – 3 September, 1999. doi: 10.23919/ECC.1999.7099812.
- [18] QUBE-servo Experiment for LabVIEW Users. Student book. Quanser System, 2014.
- [19] A. Kathpal and A. Singla. SimMechanics™ based modeling, simulation and real-time control of Rotary Inverted Pendulum. 2017 11th International Conference on Intelligent Systems and Control (ISCO), pages 166–172, Coimbatore, India, 5–6 January, 2017. doi: 10.1109/ISCO.2017.7855975.
- [20] D.L. Peters. Design of a higher order attachment for the Quanser Qube. 2016 American Control Conference, pages 6634–6639, Boston, USA, 6–8 July, 2016. doi: 10.1109/ACC.2016.7526715.
- [21] R.M. Reck. Validating DC motor models on the Quanser Qube Servo. In: Proceedings of the ASME 2018 Dynamic Systems and Control Conference (DSCC2018), V002T16A005, Atlanta, USA, 30 September–3 October, 2018. doi: 10.1115/DSCC2018-9158.
- [22] Y.V. Hote. Analytical design of lead compensator for Qube Servo system with inertia disk: An experimental validation. 2016 2nd International Conference on Contemporary Computing and Informatics (IC3I), pages 341–346, Noida, India, 14–17 December 2016. doi: 10.1109/IC3I.2016.7917986.
- [23] N. Krishnan. Estimation and Control of the Nonlinear Rotary Inverted Pendulum: Theory and Hardware Implementation. M.Sc. Thesis, San Diego State University, San Diego, USA, 2019.
- [24] A. Bisoi, A.K. Samantaray, and R. Bhattacharyya. Control strategies for DC motors driving rotor dynamic systems through resonance. Journal of Sound and Vibration, 411:304–327, 2017. doi: 10.1016/j.jsv.2017.09.014.
- [25] G. Bartolini, E. Punta, and T. Zolezzi. Approximability properties for second-order sliding mode control systems. IEEE Transactions on Automatic Control, 52(10):1813–1825, 2007. doi: 10.1109/TAC.2007.906179.
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-3a098c8a-ef7f-4dc4-9c2f-9daaed3c4c16