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http://yadda.icm.edu.pl:80/baztech/element/bwmeta1.element.baztech-aeb5f10e-c482-4aff-a372-6a95c4af5664

Czasopismo

Journal of KONES

Tytuł artykułu

Robust predictive control of an overhead crane

Autorzy Smoczek, J.  Szpytko, J. 
Treść / Zawartość
Warianty tytułu
Języki publikacji EN
Abstrakty
EN The predictive control scheme is developed for an overhead crane using the generalized predictive procedure applied for the discrete time linear parameter-varying model of a crane dynamic. The robust control technique is developed with respect to the constraints of sway angle of a payload and control input signal. The two predictive strategies are presented and compared experimentally. In the first predictive control scheme, the online estimation of the parameters of a crane dynamic model is performed using the recursive least square algorithm. The second approach is a sensorless anti-sway control strategy. The sway angle feedback signal is estimated by a linear parameter-varying model of an unactuated pendulum system with the parameters interpolated using a quasi-linear fuzzy model designed through utilizing the P1-TS fuzzy theory. The fuzzy interpolator is applied to approximate the parameters of a crane discrete-time dynamic model within the range of scheduling variables changes: the rope length and mass of a payload. The experiments carried out on a laboratory scaled overhead crane confirmed effectiveness and feasibility of the proposed solutions. The implementation of control systems was performed using the PAC system with RX3i controller. The series of experiments carried out for different operating points proved robustness of the control approaches presented in the article.
Słowa kluczowe
EN overhead crane   predictive control   linear parameter varying model   recursive estimation   fuzzy interpolation  
Wydawca Institute of Aviation
Czasopismo Journal of KONES
Rocznik 2017
Tom Vol. 24, No. 2
Strony 231--238
Opis fizyczny Bibliogr. 22 poz., rys.
Twórcy
autor Smoczek, J.
  • AGH University of Science and Technology Faculty of Mechanical Engineering and Robotics Adama Mickiewicza Av. 30, PL 30-059 Krakow, Poland tel.: +48 12 6173104, +48 12 6173103 , smoczek@agh.edu.pl
autor Szpytko, J.
  • AGH University of Science and Technology Faculty of Mechanical Engineering and Robotics Adama Mickiewicza Av. 30, PL 30-059 Krakow, Poland tel.: +48 12 6173104, +48 12 6173103 , szpytko@agh.edu.pl
Bibliografia
[1] Abdel-Rahman, E. M., Nayfeh, A. H., Masoud, Z. N., Dynamics and control of cranes: A review, Journal of Vibration and Control, Vol. 9 (7), pp. 863-908, 2003.
[2] Arnold, E., Sawodny, O., Neupert, J., Schneider, K., Anti-sway system for boom cranes based on a model predictive control approach, Proceedings of IEEE Int. Conference on Mechatronics and Automation, Niagara Falls, Canada, pp. 1533-1538, 2005.
[3] Camacho, E. F., Constrained generalized predictive control, IEEE Transactions on Automatic Control, Vol. 38 (2), pp. 327-332, 1993.
[4] Clarke, D. W., Mohtadi, C., Tuffs, P. S., Generalized predictive control – Part I. The basic algorithm, Automatica, Vol. 23 (2), pp. 137-148, 1987.
[5] Gaska, D., Pypno, C., Strength and elastic stability of cranes in aspect of new and old design standards, Mechanika, Vol. 3, pp. 226-231, 2011.
[6] Gaska, D., Margielewicz,J., Haniszewski, T., Matyja, T., Konieczny, L., Chrost, P., Numerical identification of the overhead traveling crane’s dynamic factor caused by lifting the load off the ground, Journal of Measurements in Engineering, Vol. 3 (1), pp. 34-35, 2015.
[7] Haniszewski, T., Modeling the dynamics of cargo lifting process by overhead crane for dynamic overload factor estimation,Journal of Vibroengineering, Vol. 19 (1), pp. 75-86, 2017.
[8] Hyla, P., Szpytko, J., Vision method for rope angle swing measurement for overhead travelling crane – validation approach, Activities of Transport Telematics: Communications in Computer and Information Science, Vol. 395, pp. 370-377, 2013.
[9] Hyla, P., Szpytko, J., Crane payload position measurement vision-based system dedicated for anti-sway solutions, Telematics – Support for Transport: Communications in Computer and Information Science, Vol. 471, pp. 404-413, 2014.
[10] Kalmari, J., Backman, J., Visala, A., Nonlinear model predictive control of hydraulic forestry crane with automatic sway damping, Computers and Electronics in Agriculture, Vol. 109, pp. 36-45, 2014.
[11] Kapernick, B., Graichen, K., Model predictive control of an overhead crane using constraint substitution, Proceedings of American Control Conference, Washington, DC, USA, pp. 3973--3978, 2013.
[12] Kluska, J., Analytical methods in fuzzy modelling and control, Studies in Fuzziness and Soft Computing, Vol. 241, Springer, Heidelberg, 2009.
[13] Kluska, J., Hajduk, Z., Hardware implementation of P1-TS fuzzy rule-based systems on FPGA, Lecture Notes in Artificial Intelligence 7894, pp. 282-293, 2013.
[14] Kłosiński, J., Janusz, J., Nycz, R., The impact of the FLC controller’s setting on the precision of the positioning of a payload transferred by a mobile crane, Acta Mechanica et Automatica, Vol. 8 (4), pp. 181-184, 2014.
[15] Ramli, L., Mohamed, Z., Abdullahi, A. M., Jaafar, H. I., Lazim, I. M., Control strategies for crane systems: A comprehensive review, Mechanical Systems and Signal Processing, Vol. 95,pp. 1-23, 2017.
[16] Smoczek, J., P1-TS fuzzy scheduling control system design using local pole placement and interval analysis, Bulletin of the Polish Academy of Sciences – Technical Sciences 62 (3), pp. 455-464, 2014.
[17] Su, S. W., Nguyen, H., Jarman, R., Zhu, J., Lowe, D., McLean, P., Huang, S., Nguyen, N. T.,Nicholson, R., Weng, K., Model predictive control of gantry crane with input nonlinearity compensation, World Academy of Science, Engineering and Technology, Vol. 3 (2), pp. 899--903, 2009.
[18] Tomczyk, J., Cink, J., Kosucki, A., Dynamics of an overhead crane under a wind disturbance condition, Automation in Construction, Vol. 42, pp. 100-111, 2014.
[19] Trąbka A., The impact of the support system’s kinematic structure on selected kinematic and dynamic quantities of an experimental crane, Acta Mechanica et Automatica, Vol. 8 (4), pp. 189-193, 2014.
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[21] Wu, Z., Xia, X., Optimal motion planning for overhead cranes, IET Control Theory and Applications, Vol. 8 (17), pp. 1833-1842, 2014.
[22] Zavari, K., Pipeleers, G., Swevers, J., Scheduled controller design: illustration on an overhead crane, IEEE Transactions on Industrial Electronics, Vol. 61 (7), pp. 3713-3718, 2014.
Uwagi
PL Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017).
Kolekcja BazTech
Identyfikator YADDA bwmeta1.element.baztech-aeb5f10e-c482-4aff-a372-6a95c4af5664
Identyfikatory
DOI 10.5604/01.3001.0010.2940