Sensorless anti-swing control of automatic gantry crane using Dynamic Recurrent Neural Network-based soft sensor

International Journal of Intelligent Systems Technologies and Applications

Volumn 6, Issue 1-2, 2009, Pages 112-127

  Solihinand, Mahmud Iwan ^a   Wahyudi, ^a  

^a INTERNATIONAL ISLAMIC UNIVERSITY MALAYSIA   (Malaysia)

Author keywords

anti swing control; DRNN; Dynamic Recurrent Neural Network; gantry crane; sensorless; soft sensor

Indexed keywords

EID: 80053088285     PISSN: 17408865     EISSN: 17408873     Source Type: Journal    
DOI: 10.1504/IJISTA.2009.022691     Document Type: Article

References (32)

1. Altafini, C., Frezza, R. and Galic, J. (2000) ‘Observing the load dynamic of an overhead crane with minimal sensor equipment’, Paper presented in the Proceedings of the 2000 IEEE International Conference on Robotics and Automation, San Francisco.
2. Auernig, J.W. and Troger, H. (1987) ‘Time optimal control of overhead cranes with hoisting of the load’, Automatica, Vol. 23, pp.437–447.
3. Becerra, V.M., Calado, J.M.F., Silva, P.M. and Garces, F. (2002) ‘System identification using dynamic neural network: training and initialization aspects’, The IFAC 15th World Congress. Barcelona: IFAC.
4. Delgado, A., Kambhampati, C. and Warwick, K. (1995a) ‘Dynamic recurrent neural network for system identification and control’, IEE Proceedings on Control Theory Applications, Vol. 142.
5. Delgado, A., Kambhampati, C. and Warwick, K. (1995b) ‘Identification of nonlinear system with a dynamic recurrent neural networks’, Artfical Neural Networks, Conference Publicatio, IEE.
6. Erdogmus, D., Genc, A.U.2002) ‘Neural network perspective to extended Luenberger observers’, Journal Measurement and Control, Vol. 35, pp. 10–16 (London: Institute of Measurement and Control).
7. Fuller, E.J., Yerramalla, K.S. and Cukic, B. (2006) ‘Stability properties of neural network’, in Taylor, B.J. (Ed.), Methods and Procedures for the Verification and Validation of Artificial Neural Networks. USA: Springer.
8. Garces, F., Becerra, V.M., Kambhampati, C. and Warwick, K. (2003) Strategies for Feedback Linearisation: a Dynamic Neural Network Approach. London: Springer-Verlag.
9. Ge, S.S. and Wang, C. (2004) ‘Adaptive neural control of uncertain MIMO nonlinear systems’, IEEE Trans-actions on Neural Networks, Vol. 15, pp.674–692.
10. Ge, S.S., Lee, T.H. and Harris, C.J. (1998) Adaptive Neural Network Control of Robotic Manipulators. London, UK: World Scientific.
11. Ge, S.S., Hang, C.C. and Zhang, T. (1999) ‘Adaptive neural network control of nonlinear systems by state and output feedback’, IEEE Transactions on Systems, Man and Cybernetics – Part B: Cybernetics, Vol. 29, pp.818–828.
12. Gonzalez, G.D., Redard, I.P., Barrera, R. and Fernandez, M. (1994) ‘Issues in soft-sensor applications in industrial plants’, Paper presented in the Proceedings of the IEEE International Symposium on Industrial Electronics, pp.380–385.
13. Gupta, S. and Bhowal, P. (2004) ‘Simplified open loop anti-sway technique’, Paper presented in the Proceedings of the IEEE India Annual Conference (INDICON), pp.225–228.
14. Gupta, P. and Sinha, N. (1999) ‘An improved approach for nonlinear system identification using neural networks’, Journal of the Franklin Institute, Vol. 336, pp.721–734.
15. Ham, F.M. and Kostanic, I. (2001) Principle of Neuro Computing for Science and Engineering (pp.484–491). New York: McGraw-Hill.
16. Kim, Y.S., Yoshihara, H., Fujioka, N., Kasahara, H., Shim, H. and Sul, S.K. (2003) ‘A new vision sensorless anti-sway control system for container cranes’, Industry Applications Conference, Vol. 1, pp.262–269.
17. Lee, H.H. and Cho, S.K. (2001) ‘A new fuzzy-logic anti-swing control for industrial threedimensional overhead cranes’ Paper presented in the Proceedings of the IEEE International Conference on Robotics and Automation, pp.56–61.
18. Lee, J.J., Nam, G.G., Lee, B.K. and Lee, J.M. (2004) ‘Measurement of 3D spreader position for automatic landing system’, Paper presented in the Proceedings of the 30th Annual Conference of IEEE Industrial Electronics Society.
19. Liu, D., Yi, J. and Zhoa, D. (2005) ‘Adaptive sliding mode fuzzy control for two-dimensional overhead crane, Mechatronics, pp.505–522.
20. Ljung, L. (1999) System Identification: Theory for the User (2nd ed.). New Jersey, NJ: Prentice Hall.
21. Manson, G.A. (1982) ‘Time-optimal control of and overhead crane model’, Optimal Control Applications and Methods, Vol. 3, pp.115–120.
22. Nalley, M.J. and Trabia, M.B. (2000) ‘Control of overhead cranes using a fuzzy logic controller’, Journal of Intelligent Fuzzy System, Vol. 8, pp.1–18.
23. Narendra, K.S. and Parthasarathy, K. (1990) ‘Identification and control of dynamical systems using neural networks’, IEEE Transactions on Neural Networks, Vol. 1, pp.4–27.
24. Omar, H.M. (2003) ‘Control of gantry and tower cranes’, PhD Dissertation, Virginia Polytechnic Institute and State University. Blacksburg, Virginia. Available at: http://scholar.lib.vt.edu/theses/available/etd-01262003–204800/unrestricted/Thesis.pdf.
25. Osumi, H., Miura, A. and Eiraku, S. (2005) ‘Positioning of wire suspension system using CCD cameras’, Paper presented in the Proceedings of the IEEE International Conference on Intelligent Robots and Systems (IROS).
26. Park, B.J., Hong, K.S. and Huh, C.D. (2000) ‘Time-efficient input shaping control of container crane systems’, Paper presented in the Proceedings of the IEEE International Conference on Control Application, pp.80–85.
27. Perfetti, R. (1993) ‘Asymptotic stability of equilibrium points in dynamical neural networks’, IEE Proceedings-G, Vol. 140, pp.401–405.
28. Singhose, W.E., Porter, L.J. and Seering, W.P. (1997) ‘Input shaped control of a planar gantry crane with hoisting’, Paper presented in the Proceedings of the American Control Conference, pp.97–100.
29. Stefani, R.T. and Shahian, B. (2002) Design of Feedback Control Systems. New York: Oxford University Press.
30. Wahyudi and Jalani, J. (2005) ‘Design and implementation of fuzzy logic controller for an intelligent gantry crane system’, Paper presented in the Proceedings of the 2nd International Conference on Mechatronics, pp.345–351.
31. Zhang, H. and Quan, Y. (2001) ‘Modeling, identification and control of a class of nonlinear system’, IEEE Transactions on Fuzzy Systems, Vol. 9, pp.349–354.
32. Zhenhai, G. (2003) ‘Soft sensor application in vehicle yaw rate measurement based on Kalman filter and vehicle dynamics’, Paper presented in the Proceedings of the IEEE Intelligent Transportation Systems.