Abstract
This paper presents an artificial neural networks application for a flexible process modeling. A flexible planar single-link manipulator robot is considered. The dynamic behavior of this process is described using Lagrange equations and finite elements method. The artificial neural networks are all variations on the parallel distributed processing (PDP) idea. The architecture of each network is based on very similar building blocks which perform the processing. Therefore, two feed-forward and recurrent neural networks are developed and trained using back-propagation algorithm to identify the dynamics of the flexible process. Simulation results of the system responses are given and discussed in terms of level of error reduction. Finally, a conclusion encloses the paper.
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References
Abe, S.: Neural Networks and Fuzzy Systems, Theory and Applications. Kluwer Academic Publishers, USA (1997)
Hecht-Nielsen, R.: Neurocomputing. Addison-Wesley, Reading (1989)
Hertz, A., Krogh, A.S., Palmer, R.G.: Introduction to the Theory of Neural Computation. Addison-Wesley, Redwood City (1991)
Narendra, K.W., Parthasarathy, K.: Identification and Control of Dynamical Systems using Neural Networks. IEEE Transactions on Neural Networks, 4–27 (1990)
Omidvar, O., Elliott, D.L.: Neural Systems for Control. Academic Press (1997)
Usoro, P.B., Nadira, R., Mahil, S.S.: A Finite Element/Lagrange Approach to Modeling Lightweight Flexible Manipulators. Transactions of the ASME 108, 198–205 (1986)
Simon, H.: Neural Networks. Macmillan College Publishing (1994)
Zurada, J.: Introduction to Artificial Neural System. West Publishing Company (1992)
Fu, L.: Neural Network in Computer Intelligence. McGraw Hill Book Company (1994)
Bickford, W.: Mechanics of Solids. Richard D. Irwin, Inc. (1992)
Kuo, C.F., Kuo, C.Y.: Modeling and simulation of nonlinear dynamics in a flexible robot arm. Active Control of Noise and Vibration ASM 38, 149–156 (1992)
Meirovitch, L.: Elements of Vibration Analysis, International Student Edition, 4th Printing. McGraw-Hill International Book Company (1982)
Wang, F.Y., Gao, Y.: Advanced Studies of Flexible Robotic Manipulators. Modeling, Design, Control and Applications. Series in Intelligent Control and Intelligent Automation, vol. 4. World Scientific Publishing (2003)
Roy Pota, H.: Finite-element/Lagrange Modeling and Control of a Flexible Robot Arm. In: 11th IFAC World Congress, Tallinn, Estonia, USSR, vol. 9, pp. 239–243 (1990)
Hashemi, S.M., Borneman, S.R., Alighanbari, H.: Vibration of Cracked Composite Beams: A Dynamic Finite Element. International Review of Aerospace Engineering (IREASE) 1(1), 110–121 (2008)
Mansour, T., Konno, A., Uchiyama, M.: MPID Control Tuning for a Flexible Manipulator Using a Neural Network. Journal of Robotics and Mechatronics 22(1), 82–90 (2010)
Abe, A.: Trajectory planning for flexible Cartesian robot manipulator by using artificial neural network: numerical simulation and experimental verification. Robotica 29(05), 797–804 (2011)
Mahamood, R.M., Pedro, J.O.: Hybrid PD-PID with Iterative Learning Control for Two-Link Flexible Manipulator. In: Proceedings of the World Congress on Engineering and Computer Science, San Francisco, USA, vol. II (October 2011)
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Boucetta, R., Abdelkrim, M.N. (2012). Neural Network Modeling of a Flexible Manipulator Robot. In: Cortesi, A., Chaki, N., Saeed, K., Wierzchoń, S. (eds) Computer Information Systems and Industrial Management. CISIM 2012. Lecture Notes in Computer Science, vol 7564. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33260-9_34
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DOI: https://doi.org/10.1007/978-3-642-33260-9_34
Publisher Name: Springer, Berlin, Heidelberg
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