Abstract
The article presents mathematical models and the control algorithm of robotic welding complexes of arc welding in the conditions of unstable conditions. A procedure for identifying unstable states for a mathematical model has been developed using the example of the Lorenz and Nose-Hoover attractors. An algorithm is proposed to prevent the system from transitioning to unstable states by implementing action plans.
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References
Guillo, M., Dubourg, L.: Impact & improvement of tool deviation in friction stir welding: weld quality & real-time compensation on an industrial robot. Robot. Comput.-Integr. Manuf. 39, 22–31 (2016)
Shultz, E.F., Cole, E.G., Smith, C.B., Zinn, M.R., Ferrier, N.J., Pfefferkorn, F.E.: Effect of compliance and travel angle on friction stir welding with gaps. J. Manuf. Sci. Eng. Trans. ASME 132(4), 0410101–0410109 (2010)
Wu, J., Zhang, R., Yang, G.: Design and experiment verification of a new heavy friction-stir-weld robot for large-scale complex surface structures. Ind. Robot 42(4), 332–338 (2015)
Dinham, M., Fang, G.: Autonomous weld seam identification and localisation using eye-in-hand stereo vision for robotic arc welding. Robot. Comput.-Integr. Manuf. 29(5), 288–301 (2013)
Shen, H.Y., Wu, J., Lin, T., Chen, S.B.: Arc welding robot system with seam tracking and weld pool control based on passive vision. Int. J. Manuf. Technol. 39(7–8), 669–678 (2008)
Miller, M., Mi, B., Kita, A., Ume, I.C.: Development of automated real-time data acquisition system for robotic weld quality monitoring. Mechatronics 12(9–10), 1259–1269 (2002)
Ryberg, A., Ericsson, M., Christiansson, A.K., Eriksson, K., Nilsson, J., Larsson, M.: Stereo vision for path correction in off-line programmed robot welding. In: Proceedings of the IEEE International Conference on Industrial Technology, pp. 1700–1705 (2010)
Micallef, K., Fang, G., Dinham, M.: Automatic seam detection and path planning in robotic welding. Lecture Notes in Electrical Engineering, LNEE, vol. 88, pp. 23–32 (2011)
Agapakis, J.E., Katz, J.M., Friedman, J.M., Epstein, G.N.: Vision-aided robotic welding. An approach and a flexible implementation. Int. J. Robot. Res. 9(5), 17–34 (1990)
Ahmad, S., Luo, S.: Coordinated motion control of multiple robotic devices for welding and redundancy coordination through constrained optimization in Cartesian space. IEEE Trans. Robot. Autom. 5(4), 409–417 (1989)
Liu, Y.K., Zhang, Y.M.: Toward welding robot with human knowledge: a remotely-controlled approach. IEEE Trans. Autom. Sci. Eng. 12(2), 769–774 (2015)
Kim, K.Y., Kim, D.W., Nnaji, B.O.: Robot arc welding task sequencing using genetic algorithms. IIE Trans. (Inst. Ind. Eng.) 34(10), 865–880 (2002)
Stenberg, T., Barsoum, Z., Åstrand, E., Öberg, A.E., Schneider, C., Hedegård, J.: Quality control and assurance in fabrication of welded structures subjected to fatigue loading. Weld. World 61(5), 1003–1015 (2017)
Sumesh, A., Rameshkumar, K., Raja, A., Mohandas, K., Santhakumari, A., Shyambabu, R.: Establishing correlation between current and voltage signatures of the arc and weld defects in GMAW process. Arab. J. Sci. Eng. 42(11), 4649–4665 (2017)
Ericsson, M., Nylén, P.: A look at the optimization of robot welding speed based on process modeling. Weld. J. (Miami, Fla) 86(8), 238 (2007)
Leonardo, B.Q., Steffens, C.R., da Silva Filho, S.C., Mór, J.L., Hüttner, V., do Amaral Leivas, E., Da Rosa, V.S., da Costa Botelho, S.S.: Vision-based system for welding groove measurements for robotic welding applications. In: Proceedings - IEEE International Conference on Robotics and Automation, vol. 2016-June, pp. 5650–5655 (2016)
Fominykh, D.S., Kushnikov, V.A., Rezchikov, A.F.: Prevention unstable conditions in the welding process via robotic technological complexes. In: MATEC Web of Conferences, vol. 224, p. 01045 (2018)
Hoover, W.G.: Remark on some simple chaotic flows. Phys. Rev. E 51, 759–760 (1995)
Moon, F.C.: Chaotic Vibrations. Wiley, New York (1987). 309 pp.
Andrievsky, B., Fradkov, A.: Autom. Remote Control 4, 5 (2003)
Tikhonova, O.M., Kushnikov, V.A., Fominykh, D.S. with co-authors: Mathematical model for prediction of efficiency indicators of educational activity in high school. In: Proceedings of International Conference on Information Technologies in Business and Industry, Tomsk Polytechnic University, Journal of Physics Conference Series, vol. 1015, no. UNSP 032143, Tomsk (2018)
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Fominykh, D. et al. (2021). The Task of Controlling Robotic Technological Complexes of Arc Welding in Unstable States. In: Dolinina, O., et al. Recent Research in Control Engineering and Decision Making. ICIT 2020. Studies in Systems, Decision and Control, vol 337. Springer, Cham. https://doi.org/10.1007/978-3-030-65283-8_1
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DOI: https://doi.org/10.1007/978-3-030-65283-8_1
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