[Auernig, J.W. and Troger, H. (1987). Time optimal control of overhead cranes with hoisting of the load, Automatica 23(4): 437-447.10.1016/0005-1098(87)90073-2]Search in Google Scholar
[Bańka, S., Dworak, P. and Jaroszewski, K. (2013). Linear adaptive structure for control of a nonlinear MIMO dynamic plant, International Journal of Applied Mathematics and Computer Science 23(1): 47-63, DOI: 10.2478/amcs-2013-0005.10.2478/amcs-2013-0005]Search in Google Scholar
[Benhidjeb, A. and Gissinger, G.L. (1995). Fuzzy control of an overhead crane performance comparison with classic control, Control Engineering Practice 3(12): 1687-1696.10.1016/0967-0661(95)00181-S]Search in Google Scholar
[Chang, C.-Y. (2006). The switching algorithm for the control of overhead crane, Neural Computing and Applications 15(3-4): 350-358.10.1007/s00521-006-0036-z]Search in Google Scholar
[Chang, C.-Y. (2007). Adaptive fuzzy controller of the overhead crane with nonlinear disturbances, IEEE Transactions on Industrial Informatics 3(2): 164-172.10.1109/TII.2007.898433]Search in Google Scholar
[Chapellat, H., Keel, L.H. and Bhattacharyya, S.P. (1994). External robustness properties of multilinear interval systems, Automatica 30(6): 1037-1042.10.1016/0005-1098(94)90198-8]Search in Google Scholar
[Dahleh, M., Tesi, A. and Vicino, A. (1993). An overview of extremal properties for robust control of interval plants, Automatica 29(3): 707-721.10.1016/0005-1098(93)90065-2]Search in Google Scholar
[De Jong, K.A., Spears, W.M. and Gordon, D.F. (1993). Using genetic algorithms for concept learning, Machine Learning 13(2-3): 161-188.10.1007/BF00993042]Search in Google Scholar
[Fang, Y., Ma, B., Wang, P. and Zhang, X. (2012). A motion planning-based adaptive control method for an underactuated crane system, IEEE Transactions on Control Systems Technology 20(1): 241-248.10.1109/TCST.2011.2107910]Search in Google Scholar
[Filipic, B., Urbancic, T. and Krizman, V. (1999). A combined machine learning and genetic algorithm approach to controller design, Engineering Applications of Artificial Intelligence 12(4): 401-409.10.1016/S0952-1976(99)00019-6]Search in Google Scholar
[Hsu, C.-C., Chang, S.-C. and Yu, C.-Y. (2007). Tolerance design of robust controllers for uncertain interval systems based on evolutionary algorithms, IET Control Theory and Applications 1(1): 244-252.10.1049/iet-cta:20050300]Search in Google Scholar
[Hyla, P. (2012). The crane control systems: A survey, Proceedings of the 17th IFAC International Conference on Methods and Models in Automation and Robotics MMAR, Mi˛edzyzdroje, Poland, pp. 505-509.]Search in Google Scholar
[Kang, Z., Fujii, S., Zhou, C. and Ogata, K. (1999). Adaptive control of a planar gantry crane by the switching of controllers, Transactions of Society of Instrument and Control Engineers 35(2): 253-261.10.9746/sicetr1965.35.253]Search in Google Scholar
[Karajgikar, A., Vaughan, J. and Singhose, W. (2011). Double-pendulum crane operator performance comparing pd-feedback control and input shaping, Proceedings of the ECCOMAS Thematic Conference on Advances in Compuational Multibody Dynamics, Brussels, Belgium, pp. 1-14.]Search in Google Scholar
[Kharitonov, V.L. (1978). Asymptotic stability of an equilibrium position of a family of systems of linear differential equations, Differential’nye Uravneniya 14(11): 2086-2088.]Search in Google Scholar
[Kijima, Y., Ohtsubo, R., Yamada, S. and Fujikawa, H. (1995). An optimization of fuzzy controller and it’s application to overhead crane, Proceedings of the IEEE IECON 21st International Conference on Industrial Electronics, Control, and Instrumentation, Tokyo, Japan, pp. 1508-1513.]Search in Google Scholar
[Kimiaghalam, B., Homaifar, A., Bikdash, M. and Dozier, G. (1999). Genetic algorithms solution for unconstrained optimal crane control, Proceedings of the IEEE Congress on Evolutionary Computation, Washington, DC, USA, pp. 2124-2130.]Search in Google Scholar
[Kimiaghalan, B., Homaifar, A., Bikdash, M. and Sayyarrodsari, B. (2002). Genetic algorithm based gain scheduling, Proceedings of the Congress on Evolutionary Computation, Greensboro, NC, USA, pp. 540-545.]Search in Google Scholar
[Kluska, J. (2006). Transformation lemma on analytical modeling via Takagi-Sugeno fuzzy system and its applications, 8th International Conference on Artificial Intelligence and Soft Computing (ICAISC 2006), Zakopane, Poland, pp. 230-239.]Search in Google Scholar
[Kluska, J. (2009). Analytical Methods in Fuzzy Modeling and Control, Studies in Fuzziness and Soft Computing, Vol. 241, Springer-Verlag, Berlin/Heidelberg.]Search in Google Scholar
[Lee, C.-H., Lee, Y.-H. and Teng, C.-C. (2002). A novel robust PID controllers design by fuzzy neural network, Proceedings of the American Control Conference, Anchorage, AK, USA, pp. 1561-1566.]Search in Google Scholar
[Li, X. and Yu, W. (2012). Anti-swing control for an overhead crane with fuzzy compensation, Intelligent Automation and Soft Computing 18(1): 1-11.10.1080/10798587.2012.10643223]Search in Google Scholar
[Liu, D., Yi, J. and Tan, M. (2002). Proposal of GA-based two-stage fuzzy control of overhead crane, Proceedings of the IEEE Conference on Computers, Communications, Control and Power Engineering, Beijing, China, pp. 1721-1724.]Search in Google Scholar
[Liu, D., Yi, J., Zhao, D. and Wang, W. (2005). Adaptive sliding mode fuzzy control for a two-dimensional overhead crane, Mechatronics 15(5): 505-522.10.1016/j.mechatronics.2004.11.004]Search in Google Scholar
[Mahfouf, M., Kee, C.H., Abbod, M.F. and Linkens, D.A. (2000). Fuzzy logic-based anti-sway control design for overhead cranes, Neural Computing and Applications 9(1): 38-43.10.1007/s005210070033]Search in Google Scholar
[Mallan, S., Milanese, M. and Taragna, M. (1997). Robust analysis and design of control systems using interval arithmetic, Automatica 33(7): 1363-1372.10.1016/S0005-1098(97)00028-9]Search in Google Scholar
[McNichols, H. and Fadali, M.S. (2003). Selecting operating points for discrete-time gain scheduling, Computers and Electrical Engineering 29(2): 289-301.10.1016/S0045-7906(01)00031-3]Search in Google Scholar
[Mendez, J.A., Acosta, L., Moreno, L., Torres, S. and Marichal, G.N. (1999). An application of a neural self-tuning controller to an overhead crane, Neural Computing and Applications 8(2): 143-150.10.1007/s005210050016]Search in Google Scholar
[Michalewicz, Z. and Janikow, C.Z. (1991). Handling constraints in genetic algorithm, Proceedings of the 4th International Conference on Genetic Algorithms, San Diego, CA, USA, pp. 151-157.]Search in Google Scholar
[Moon, M.S., VanLandingham, H.F. and Beliveau, Y.J. (1996).]Search in Google Scholar
[Fuzzy time optimal control of crane load, Proceedings of the 35th Conference on Decision and Control, Kobe, Japan, pp. 1127-1132.]Search in Google Scholar
[Moore, R. (1966). Interval Analysis, Prentice-Hall, Englewood Cliffs, NJ.]Search in Google Scholar
[Moustafa, K. A. F. (2001). Reference trajectory tracking of overhead cranes, Journal of Dynamic Systems, Measurement, and Control 123(1): 139-141.10.1115/1.1343462]Search in Google Scholar
[Nakazono, K., Ohnisihit, K. and Kinjot, H. (2007). Load swing suppression in jib crane systems using a genetic algorithm-trained neuro-controller, Proceedings of the International Conference on Mechatronics, Kumamoto, Japan, pp. 1-4. ]Search in Google Scholar
[Oh, S.-K., Pedrycz, W., Rho, S.-B. and Ahn, T.-C. (2004). Parameter estimation of fuzzy controller and its application to inverted pendulum, Engineering Applications of Artificial Intelligence 17(1): 37-60.10.1016/j.engappai.2003.12.003]Search in Google Scholar
[Sadati, N. and Hooshmand, A. (2006). Design of a gain-scheduling anti-sway controller for tower cranes using fuzzy clustering techniques, Proceedings of the International Conference on Computational Intelligence for Modeling, Control and Automation, Sydney, Australia, p. 172.]Search in Google Scholar
[Sakawa, Y. and Shindo, Y. (1982). Optimal control of container cranes, Automatica 18(3): 257-266.10.1016/0005-1098(82)90086-3]Search in Google Scholar
[Singer, N., Singhose, W. and Kriikku, E. (1997). An input shaping controller enabling cranes to move without sway, Proceedings of the American Nuclear Society 7th Topical Meeting on Robotics and Remote Systems, Augusta, GA, USA, pp. 225-231.]Search in Google Scholar
[Smalko, Z. and Szpytko, J. (2009). Safety in engineering practice, Proceedings of the 17th European Safety and Reliability Conference ESREL, Valencia, Spain, pp. 1231-1237.]Search in Google Scholar
[Smith, S.F. (1980). A Learning System Based on Genetic Adaptive Algorithms, Ph.D. thesis, University of Pittsburgh, Pittsburgh, PA.]Search in Google Scholar
[Smoczek, J. and Szpytko, J. (2008). A mechatronics approach in intelligent control systems of the overhead traveling cranes prototyping, Information Technology and Control 37(2): 154-158.]Search in Google Scholar
[Smoczek, J. and Szpytko, J. (2010). Fuzzy logic approach to the gain scheduling crane control system, Proceedings of the 15th IFAC International Conference on Methods and Models in Automation and Robotics MMAR, Mi˛edzyzdroje, Poland, pp. 261-266.]Search in Google Scholar
[Smoczek, J. and Szpytko, J. (2011). Design of a fuzzy gain scheduling controller for the anti-sway crane system, Proceedings of the 26th ISPE International Conference on CAD/CAM, Robotics and Factories of the Future, CARSFOF, Kuala Lumpur, Malaysia, pp. 809-818.]Search in Google Scholar
[Solihin, M.I., Wahyudi and Legowo, A. (2010). Fuzzy-tuned antiswing control of automatic gantry crane, Journal of Vibration and Control 16(1): 127-145.10.1177/1077546309103421]Search in Google Scholar
[Sugeno, M. and Kang, G.T. (1988). Structure identification of fuzzy model, Fuzzy Sets and Systems 28(1): 15-33.10.1016/0165-0114(88)90113-3]Search in Google Scholar
[Szpytko, J. and Wozniak, D.A. (2007). To keep operational potential of transport device e-based on reliability indicators, Proceedings of the European Safety and Reliability Conference ESREL, Stavanger, Norway, pp. 2377-2384.]Search in Google Scholar
[Takagi, T. and Sugeno, M. (1985). Fuzzy identification of systems and its application to modeling and control, IEEE Transactions on Systems, Man and Cybernetics 15(1): 116-132.10.1109/TSMC.1985.6313399]Search in Google Scholar
[Trabia, M.B., Renno, J.M. and Moustafa, K.A.F. (2008). Generalized design of an anti-swing fuzzy logic controller for an overhead crane with hoist, Journal of Vibration and Control 14(3): 319-346.10.1177/1077546307080025]Search in Google Scholar
[Warmus, M. (1956). Calculus of approximations, Bulletin de l’Academie Polonaise des Sciences IV(5): 253-259.]Search in Google Scholar
[Yi, J., Yubazaki, N. and Hirota, K. (2003). Anti-swing and positioning control of overhead traveling crane, Information Sciences 155(1-2): 19-42.10.1016/S0020-0255(03)00127-0]Search in Google Scholar
[Young, R.C. (1931). The algebra of many-valued quantities, Mathematische Annalen 104(1): 260-290.10.1007/BF01457934]Search in Google Scholar
[Yu, W., Moreno-Armendariz, A. and Rodriguez, F.O. (2011). Stable adaptive compensation with fuzzy CMAC for an overhead crane, Information Sciences 181(21): 4895-4907.10.1016/j.ins.2009.06.032]Search in Google Scholar
[Zubowicz, T. and Brdy´s, M.A. (2013). Stability of softly switched multiregional dynamic output controllers with a static antiwindup filter: A discrete-time case, International Journal of AppliedMathematics and Computer Science 23(1): 65-73, DOI: 10.2478/amcs-2013-0006. 10.2478/amcs-2013-0006]Search in Google Scholar