Zastosowanie inteligentnych metod obliczeniowych w systemach sterowania i nadzorowania suwnic

• Autorzy: Smoczek J. , Szpytko J.

Warianty tytułu

EN

Inteligent crane control and supervising systems

• Języki publikacji: PL

Abstrakty

PL

Rozwój zautomatyzowanych systemów transportu technologicznego zdeterminowany jest rosnącymi oczekiwaniami i wymaganiami stawianymi już nie tylko systemom sterowania, ale też systemom diagnostycznym i nadzorowania stanu eksploatacyjnego urządzeń. Wymaga to implementacji w tych układach coraz bardziej wyrafinowanych metod, w tym technik opartych na tak zwanej sztucznej inteligencji. Artykuł przedstawia przegląd wybranych rozwiązań dotyczących systemów sterowania suwnic, planowania i harmonogramowania operacji transportowych oraz oceny gotowości urządzeń transportowych, opartych na logice rozmytej, sztucznych sieciach neuronowych oraz algorytmach ewolucyjnych.

EN

Optimization of manufacturing cycle, defined as obtaining maximum effectiveness together with assurance of expected quality of product, is the main aim of automation of manufacturing and material handling process. The growing requirements for automated material handling systems leads to implement soft computing methods to the control, supervisory, monitoring and diagnostic systems. The paper is a survey of chosen methods of crane control systems, crane movement scheduling, as well as system equipments health monitoring based on the fuzzy logic, artificial neural network and evolutionary algorithms.

Słowa kluczowe

PL

transport bliski; suwnice; sterowanie inteligentne

EN

inteligent crane control; supervising systems

• Wydawca: Sieć Badawcza Łukasiewicz - Poznański Instytut Technologiczny
• Czasopismo: Logistyka
• Rocznik: 2011
• Tom: nr 6
• Opis fizyczny: Pełny tekst na CD, Bibliogr. 38 poz., rys.

Twórcy

autor

Smoczek J.

autor

Szpytko J.

• Akademia Górniczo-Hutnicza, Wydział Inżynierii Mechanicznej i Robotyki, 30-059 Kraków, al. Mickiewicza 30,

Bibliografia

• [1] Acosta L., Méndez J.A, Torres S, Moreno L., Marichal G.N.: On the design and implementation of a neuromorphic self-tuning controller. Neural Processing Letters 9, 1999, s. 229–242.
• [2] Al.-Garni A.Z., Moustafa K.A.F., Nizami J.S.S.A.K.: Optimal control of overhead cranes. Control Engineering Practice , Vol. 3, No. 9, 1995, s. 1277-1284.
• [3] Auernig J.W., Troger H.: Time optimal control of overhead cranes with hoisting of the load. Automatica, Vol.23, No. 4, 1987, s. 437-447.
• [4] Bartolini G., Pisano A., Usai E.: Second-order sliding-mode control of container cranes. Automatica 38, 2002, s. 1783-1790.
• [5] Benhidjeb A., Gissinger G.L.: Fuzzy control of an overhead crane performance comparison with classic control. Control Engineering Practice, Vol. 3, No. 12, 1995, s. 1687-1696.
• [6] Boustany F., d’Andrea-Novel B: Adaptive control of an overhead crane using dynamic feedback linearization and estimation design. Proceedings of the IEEE International Conference on Robotics and Automation, Nice, France 1992, s. 1963-1968.
• [7] Cheng C.C., Chen C.Y.: Controller design for an overhead crane system with uncertainty. Control Engineering Practice, Vol. 4, No. 5, 1996, s. 645-653.
• [8] Cho S.K., Lee H.H.: A fuzzy-logic antiswing controller for three-dimensional overhead cranes. ISA Transactions 41, 2002, s. 235-243.
• [9] Corriga G., Giua A., Usai G.: An implicit gain-scheduling controller for cranes. IEEE Transactions on Control Systems Technology, 6 (1), 1998, s. 15-20.
• [10] Filipic B., Urbancic T., Krizman V.: A combined machine learning and genetic algorithm approach to controller design. Engineering Applications of Artificial Intelligence 12 (1999), pp. 401-409.
• [11] Giua A., Seatzu C. and Usai G.: Observer-controller design for cranes via Lyapunov equivalence. Automatica, Vol. 35, No 4 , 1999, s. 669-678.
• [12] Hamalainen J.J., Marttinen A., Baharova L., Virkkunen J.: Optimal path planning for a trolley crane: fast and smooth transfer of load. IEE Proceedings D: Control Theory Applications, 142 (1), 1995, s. 51-57.
• [13] Henriksen S.J., Wang L., Goodwin G.C., Shook A.: Application of a genetic algorithm in crane movement scheduling. Proceedings of IFAC World Congress, Beijing, 1999.
• [14] Hicar M. and Ritok J.: Robust crane control. Acta Polytechnica Hungarica, Vol. 3, No. 2, 2006, s. 91-101.
• [15] Ishide T., Uchida H., Miyakawa S.: Application of a fuzzy neural network in the automation of roof crane system. Proceedings of the 9th Fuzzy System Symposium, 1993, s. 29-32.
• [16] Itoh O., Migita H., Itoh J., Irie Y.: Application of fuzzy control to automatic crane operation. Proceedings of IECON 1, 1993, s. 161-164.
• [17] Javanshir H., Seyedalizadeh Ganji S. R.: Yard crane scheduling in port container terminals using genetic algorithm. International Journal of Industrial Engineering., 6 (11), pp. 39-50, 2010.
• [18] 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. 2,1999, s. 253-261.
• [19] Kimiaghalam, B., Homaifar, A., Bikdash, M., Dozier, G.: Genetic algorithms solution for unconstrained optimal crane control, IEEE Congress on Evolutionary Computation, Washington DC, July 6-9, s. 2124-2230, 1999.
• [20] Lew J.Y. and Halder B.: Experimental study of anti-swing crane control for a varying load. Proceedings of American Control Conference, V. 2, 2003, s. 1434-1439.
• [21] Liang Y., Huang Y., Yang Y.: A quay crane dynamic scheduling problem by hybrid evolutionary algorithm for berth allocation planning. Computers & Industrial Engineering 56 (2009), pp. 1021–1028.
• [22] Mahfouf M., Kee C.H., Abbod M.F., Linkens D.A.: Fuzzy logic-based anti-sway control design for overhead cranes. Neural Computating and Applications, No. 9, 2000, s. 38-43.
• [23] Marttinen A.: Pole-placement control of a pilot gantry. Amer. Contr. Conf., ACC’89, Pittsburgh, PA, 1989.
• [24] Marttinen A., Virkkunen J., T.S. Riku: Control study with a pilot crane. IEEE Transactions on Education, Vol. 33, No. 3, 1990, s. 298-305.
• [25] Mendez J.A., Acosta L., Moreno L., Torres S., Marichal G.N.: An application of a neural self controller to an overhead crane. Neural Computing and Applications 8, 1999, s. 143-150.
• [26] 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, Kobe, Japan, 1996, s. 1127-1132.
• [27] Moreno L., Mendez J.A., Acosta L., Torres S., Hamilton A., Marichal G.N.: A selftuning neuromorphic controller: application to the crane problem. Control Engineering Practice 6, 1998, s. 1475-1483.
• [28] Nakazono K., Ohnisihit K., Kinjot H.: Load swing suppression in jib crane systems using a genetic algorithm-trained neuro-controller. Proceedings of International Conference on Mechatronics, Kumamoto Japan, 2007.
• [29] Nalley M., Trabia M.: Control of overhead crane using a fuzzy logic controller. Journal of Intelligent and Fuzzy Systems, 8 (1), 2000, s. 1-18.
• [30] Smoczek J.: Intelligent crane control systems. Publishing House of Sustainable Technologies – National Research Institute, Library of Maintenance Problems Kraków-Radom 2010.
• [31] Smoczek J., Szpytko J.: A mechatronics approach in intelligent control systems of the overhead traveling cranes prototyping. Information Technology and Control, Vol. 37, No. 2, 2008, s. 154-158.
• [32] Smoczek J., Szpytko J.: Self-learning fuzzy predictor of exploitation system operating time. Journal of KONES : powertrain and transport, 2011 vol. 18 No. 4, s. 463–469.
• [33] Smoczek J., Szpytko J.: A genetic fuzzy approach to estimate operation time of transport device. Journal of KONES : powertrain and transport, 2011 vol. 18 No. 4 s. 601–608.
• [34] Szpytko J.: Integrated decision making supporting the exploitation and control of transport devices. Uczelniane Wydawnictwa Naukowo-Dydaktyczne AGH, Kraków 2004.
• [35] Szpytko J.: Kształtowanie procesu eksploatacji środków transportu bliskiego. Wydawnictwo Instytutu Technologii Eksploatacji, Kraków-Radom 2004.
• [36] Wang Y., Chen Y., Wang K.: A Case Study of Genetic Algorithms for Quay Crane Scheduling. Studies in Computational Intelligence, 2009, Volume 214/2009, pp. 119-125.
• [37] Yi J., Yubazaki N., Hirota K.: Anti-swing fuzzy control of overhead traveling crane. Proceedings of IEEE International Conference on Fuzzy Systems, 2002, s. 1298-1303.
• [38] Yi J., Yubazaki N., Hirota K.: Anti-swing and positioning control of overhead traveling crane. Information Sciences 155, 2003, s. 19-42.