Genetic fuzzy approach to adaptive crane control system

• Autorzy: Smoczek J.
• Języki publikacji: EN

Abstrakty

EN

In automated manufacturing processes the safety, precise and fast transfer of goods realized by automated material handling devices is required to raise efficiency and productivity of manufacturing process. Hence, in those industrial branches where cranes are extensively used the problem of an anti-sway crane control is especially important to speed-up the time of transportation operations and ensures the safe and effective transportation operations. The precise positioning of a cargo requires controlling the speed of crane motion mechanisms to reduce the sway of a payload. Moreover, the anti-sway crane control scheme involves applying the adaptive techniques owing to the nonlinearities of a system that comes especially from stochastic variation of rope length on which a payload is suspended and mass of this payload. The paper provides the design method of an adaptive control system for a planar model of crane. The control system is based on the gain scheduling control scheme created using fuzzy logic controller with Takagi-Sugeno-Kang-type fuzzy implications. The design process of a gain scheduling control system consists in selecting such a suitable set of operating points at which the linear controllers are determined that interpolation control scheme ensures the expected control quality within the known range of nonlinear system parameters changes, when those parameters vary in relation to the exogenous variables: rope length and mass of a payload. The method that is proposed in this paper to solve the problem of designing the fuzzy gain scheduling crane control system for minimum set of operating points is based on the pole placement method and genetic algorithm.

Słowa kluczowe

EN

anti-sway crane control; pole placement; fuzzy logic; genetic algorithm

• Wydawca: Łukasiewicz Research Network - Institute of Aviation ; European Science Society of Powertrain and Transport KONES Poland ; Wydawnictwo Instytutu Technicznego Wojsk Lotniczych
• Czasopismo: Journal of KONES
• Rocznik: 2012
• Tom: Vol. 19, No. 4
• Strony: 577--584
• Opis fizyczny: Bibliogr. 16 poz., rys.

Twórcy

autor

Smoczek J.

• AGH University of Science and Technology Faculty of Mechanical Engineering and Robotics Mickiewicza Av. 30, 30-059 Krakow, Poland tel.: [phone],

Bibliografia

• [1] Cho, S. K., Lee, H. H., A fuzzy-logic antiswing controller for three-dimensional overhead cranes, ISA Transactions 41, pp. 235-243, 2002.
• [2] Filipic, B., Urbancic, T., Krizman, V., A combined machine learning and genetic algorithm approach to controller design, Engineering Applications of Artificial Intelligence, Vol. 12, pp. 401-409, 1999.
• [3] Itoh, O., Migita, H., Itoh, J., Irie, Y., Application of fuzzy control to automatic crane operation, In Proceedings of IECON 1, pp. 161-164, 1993.
• [4] Kang, Z., Fujii, S., Zhou, C., Ogata, K., Adaptive control of a planar gantry crane by the switching of controllers, Transactions of Society of Instrument and Control Engineers, Vol. 35, No. 2, pp. 253-261, 1999.
• [5] Kimiaghalam, B., Homaifar, A., Bikdash, M., Dozier, G., Genetic algorithms solution for unconstrained optimal crane control, IEEE Congress on Evolutionary Computation, July 6-9, Washington DC 1999.
• [6] Kimiaghalan, B., Homaifar, A., Bikdash, M., Sayyarrodsari, B., Genetic algorithm based gain scheduling, In Proceedings of the Congress on Evolutionary Computation, pp. 540-545, 2002.
• [7] Moon, M. S., VanLandingham, H. F., Beliveau Y.J., Fuzzy time optimal control of crane load, Proceedings of the 35th Conference on Decision and Control, pp. 1127-1132, Kobe, Japan 1996.
• [8] Nakazono, K., Ohnisihit, K., Kinjot, H., Load swing suppression in jib crane systems using a genetic algorithm-trained neuro-controller, In Proceedings of International Conference on Mechatronics, Kumamoto Japan 2007.
• [9] Sadati, N., Hooshmand, A., Design of a gain-scheduling anti-sway controller for tower cranes using fuzzy clustering techniques, In Proceedings of Int. Conference on Computational Intelligence for Modeling, Control and Automation, Sydney, Australia 2006.
• [10] Smoczek, J., Szpytko, J., A mechatronics approach in intelligent control systems of the overhead travelling cranes prototyping, Information Technology and Control, Vol. 37, No. 2, pp. 154-158, 2008.
• [11] Smoczek, J., Szpytko, J., Fuzzy logic approach to the gain scheduling crane control system, In Proceedings of 15th Int. Conference on Methods and Models in Automation and Robotics, MMAR 2010, 23-26 August, pp. 261-266, Miedzyzdroje, Poland 2010.
• [12] Yi, J., Yubazaki, N., Hirota, K., Anti-swing and positioning control of overhead travelling crane, Information Sciences 155, pp. 19-42, 2003.
• [13] http://www.hetronic.co.uk.
• [14] http://www.konecranesamericas.com.
• [15] http://www.rimagroup.com.
• [16] http://www.smartcra