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Predictive Control with Dynamic Hysteresis Reference Trajectory: Application to a Structural Base-Isolation Model | ||
| Journal of Applied and Computational Mechanics | ||
| مقاله 22، دوره 7، Special Issue، شهریور 2021، صفحه 1242-1251 اصل مقاله (1.31 M) | ||
| نوع مقاله: Special Issue Paper | ||
| شناسه دیجیتال (DOI): 10.22055/jacm.2020.33934.2307 | ||
| نویسندگان | ||
| Nubia Ilia Ponce de León Puig* 1؛ José Rodellar2؛ Leonardo Acho3 | ||
| 1Departament of Mathematics, Universitat Politècnica de Catalunya-UPC, BarcelonaTech, Escola d’Enginyeria de Barcelona Est-EEBE, Spain | ||
| 2Departament of Mathematics, Universitat Politècnica de Catalunya-UPC, BarcelonaTech, Escola d’Enginyeria de Barcelona Est-EEBE, Spain | ||
| 3Departament of Mathematics, Universitat Politècnica de Catalunya-UPC, Escola Superior d'Enginyeries Industrial, Aeroespacial i Audiovisual de Terrassa ESEIAAT, Spain | ||
| چکیده | ||
| Over the last decades, in the field of control engineering, Model Predictive Control (MPC) has been successfully employed in many industrial processes. This due to, among other aspects, its capability to include constrains within the design control formulation and also its ability to perform on-line optimization. For instance, in the civil engineering field, different MPC approaches have been well developed to formulate active control algorithms able to reduce civil structural responses to earthquakes. Thus, in this paper, a customized version of a conventional Predictive Control (PC) strategy is proposed to mitigate the displacement on a base-isolated system with a nonlinear hysteresis behavior, that is excited by a seismic event. The proposal consists of including a dynamic hysteresis system into the control scheme to generate a reference trajectory that will softly drive the base-isolated structure to a rest status. The proposed control scheme is evaluated through numerical experiments, and then its performance is compared with respect to the conventional Predictive Control methodology. According to the numerical experiments, the approach here presented results more efficient than the conventional method due to the use of a suitable linear model of the structural system plus a new Driver Block with dynamic hysteresis within the Predictive Control scheme. | ||
| کلیدواژهها | ||
| Predictive Control؛ Dynamic reference trajectories؛ Hysteresis؛ Base-isolated structure | ||
| مراجع | ||
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[1] Sasa, R.V., Levine, W.S, Handbook of model predictive control, Springer, 2018.
[2] Basil, K., Cannon, M., Model predictive control, Classical, Robust and Stochastic, Springer, 2016.
[3] Sanchez, J.M., Rodellar, J., ADEX optimized adaptive controllers and systems, Springer, 2015.
[4] Rebeck, M.J., Rawlings, J.B., Model predictive control with discrete actuators: Theory and application, Automatica, 78, 2017, 258-265.
[5] Pannek, J., Grüne, L., Nonlinear Model Predictive Control, Springer, 2011.
[6] Sanchez, J.M., Rodellar, J., Adaptive predictive control: from the concepts to plant optimization, Prentice Hall, 1996.
[7] Wang, L., Model predictive control: design and implementation using Matlab, American control conference, 2009.
[8] Mehndiratta, M., Kayacan, E., Patel, S., Kayacan, E., Chowdhary, G., Learning-based fast nonlinear model predictive control for custom-made 3D printed ground and aerial robots, in Handybook of Model Predictive Control, 2019, pp. 581-605.
[9] Ostafew, C.J., Schoellig, A.P., Barfoot, T.D., Learning‐based nonlinear model predictive control to improve vision‐based mobile robot path tracking, Journal of Field Robotics, 33(1), 2016, 133-152.
[10] Zhijun, L., Yuxia, Y., Fan, K., Wei, H., Chun-Yi, S., Robust vision-based tube model predictive control of multiple mobile robots for leader–follower formation, IEEE Transactions on Industrial Electronics, 64(4), 2019, 3096-3106.
[11] Goodwin, G.C., Medioli, A.M., Murray, K., Sykes, R., Stephen, C., Applications of MPC in the area of health care, in Handbook of Model Predictive Control, Springer, 2019, pp. 529-550.
[12] Linkers, D.A., Mahfonf, M., Generalized predictive control in clinical anaesthesia, in Advances in Model-Based Predictive Control, Oxford University Press, 1994.
[13] Doyle III, Francis, J., Dassau, E., Gondhalekar, R.L., Daily periodic target-zone modulation in the model predictive control problem for artificial pancreas for type I diabetes applications, Patent 10, 507, 284, 17 Dec 2019.
[14] Goodwin, G.C., Seron, M.M., Feedback and feedforward control in the context of model predictive control with application to the management of type 1 diabetes mellitus, Control Engineering Practice, 89, 2019, 228-237.
[15] Filey, D.P., Jianbo, L., Davor, D.H., Autonomous vehicle operation based on interactive model predictive control, Patent 10, 239, 529, 26 Mar 2019.
[16] Xiaoqiang, S., Yingfeng, C., Shaohua, W., Xing, X., Long C., Optimal control of intelligent vehicle longitudinal dynamics via hybrid model predictive control, Robotics and Autonomous Systems, 112, 2019, 190-200.
[17] Vazquez, S., Rodriguez, J., Rivera, M., Franquelo, L.G., Norambuena, M., Model predictive control for power converters and drives: Advances and trends, IEEE Transactions on Industrial Electronics, 64(2), 2016, 935-947.
[18] Lashab, A., Sera, D., Guerrero, J.M., A dual-discrete model predictive control-based MPPT for PV systems, IEEE Transactions on Power Electronics, 34(10), 2019, 18795226.
[19] Yinghao, S., Jiefeng, H., Zilin, L., Guerrero, J.M., A model predictive control for renewable energy based AC microgrids without any PID regulators, IEEE Transactions on Power Electronics, 33(11), 2018 , 9122-9126.
[20] Takács, G., Rohal-Ilkiv, B., Model Predictive Vibration Control, Springer, 2012.
[21] Ponce de Leon, N.I., Acho, L., Rodellar, J., Adaptive predictive control of a base-isolated hysteretic system, 21 st International Conference on System Theory, Control and Computing, Sinaia, 2017.
[22] Lyan-Ywan, L., Ging-Long, L., Predictive control of smart isolation system for precision equipment subjected to near-fault earthquakes, Engineering Structures, 30(11), 2008, 3045-3064.
[23] Rodellar, J., Barbat, A. H., Predictive control of structure, Journal of Engineering Mechanics, 113(6), 1987, 797-812.
[24] Rodellar, J., Chung L.L., Soong, T.T., Experimental digital control of structures, Journal of Engineering Mechanics, 115(6), 1989, 1245-1261.
[25] Mousavi, S.M., Ellsworth, W.L., Zhu, W., Chuang, L.Y., Beroza, G.C., Earthquake transformer—an attentive deep-learning model for simultaneous earthquake detection and phase picking, Nature, 11(1), 2020, 1-12.
[26] Bedfrod, J.R., Moreno, M., Deng, Z., Oncken, O., Schurr, B., Jhon, T., Báez J.C., Bevis, M., Months-long thousand-kilometre-scale wobbling before great subduction earthquakes, Nature, 580(7805), 2020, 628-635.
[27] Ramallo, J.C., Johnson, E.A., Spencer, B.F., Smart base isolation systems, Journal of Engineering Mechanics, 128(10), 2002, 1088-1099.
[28] Ikhouane, F., Rodellar, J., Systems with hysteresis: analysis, identification and control using the Bouc-Wen model, Wiley, 2007.
[29] Shieh-Kung, H., Chin-Hsiung L., Combination of decentralized sliding mode control and online wavelet analysis for control of equipment with isolation system, Structural Control and Health Monitoring, 26(5), 2019, 2339.
[30] Pozo, F., Ikhouane, F., Pujol, G., Rodellar, J., Adaptive backstepping control of hysteretic base-isolated structures, Journal of Vibration and Control, 12(4), 2006, 373-394.
[31] Ikhouane, F., Mañosa, V., Rodellar, J., Adaptive control of a hysteretic structural system, Automatica, 41(2), 2005, 225-231.
[32] Bittanti, S., Laub, A.J., Willems, J.C., The Ricatti Equation, Springer-Verlag, 1991.
[33] Folient, G.C., Hysteresis modeling of wood joints and structural systems, Journal of Structural Engineering, 121(6), 1995, 1013-1022.
[34] Vidal, Y., Acho, L., Pozo, F., Robust fault detection in hystereticbase-isolation systems, Mechanical Systems and Signal Processing, 29, 2012, 447-456.
[35] Tutivén, C., Vidal, Y., Acho, L., Rodellar, J., Hysteresis-based design of dynamic reference trajectories to avoid saturation in controlled wind turbines, Asian Journal of Control, 19(2), 2017, 438-449.
[36] Ponce de Leon, N.I., Acho, L., Rodellar, J., An on-line statistic algorithm to fault detection in controlled systems: a study case, in Intelligent systems, International IEEE Conference, Madeira, 2018. | ||
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