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Operator-based robust non-linear control for gantry crane system with soft measurement of swing angle

Published Online:May 3, 2012pp 86-96https://doi.org/10.1504/IJMIC.2012.046699

Abstract

In this paper, a robust non-linear control scheme is proposed for a gantry crane system with estimation of swing angle by using operator-based robust right coprime factorisation approach. By analysing properties of the crane system, it shows that displacement distance and swing angle are the two main goals. But, there exists only one input force. Also, in real gantry crane system, it is difficult to measure the swing angle. As a result, real-time estimation of the swing angle is presented by using data-based SVM model, where a generalised Gaussian function is adopted as the kernel function. The difference between the estimation and real value leads some uncertainties. Then, operator-based robust right coprime factorisation approach is presented for the non-linear system with uncertainties. Meanwhile, an optimal tracking controller is designed to ensure the tracking performance. Finally, experimental results are given to show the effectiveness of the proposed scheme.

Keywords

robust non-linear control, right coprime factorisation, crane control, support vector machine, SVM, generalised Gaussian distribution

References

  • 1. M.A. Ahmad, R.M.T. Raja Ismail, M.S. Ramli, N.M. Abdul Ghani, M.A. Zawawi, '‘Optimal tracking with sway suppression control for a gantry crane system’' European Journal of Scientific Research (2009) Google Scholar
  • 2. G. Chen, Z. Han, '‘Robust right coprime factorization and robust stabilization of nonlinear feedback control systems’' IEEE Trans. Autom. Control (1998) Google Scholar
  • 3. G. Corriga, A. Giua, G. Usai, '‘An implicit gain-scheduling controller for cranes’' IEEE Trans. Control Systems Technology (1998) Google Scholar
  • 4. N. Cristianini, J. Shawe-Talor, An Introduction to Support Vector Machines and other Kernel-based Learning Methods (2005) Google Scholar
  • 5. R.J.P. De Figueiredo, G. Chen, Nonlinear Feedback Control System: An Operator Theory Approach (1993) Google Scholar
  • 6. M. Deng, A. Inoue, '‘Networked non-linear control for an aluminum plate thermal process with time-delays’' International Journal of Systems Science (2008) Google Scholar
  • 7. M. Deng, S. Bi, A. Inoue, '‘Robust nonlinear control and tracking design for multi-input multi-output nonlinear perturbed plants’' IET Control Theory & Applications (2009a) Google Scholar
  • 8. M. Deng, L. Jiang, A. Inoue, '‘Mobile robot path planning by SVM and Lyapunov function compensation’' Measurement and Control: The Journal of the Institute of Measurement and Control (2009b) Google Scholar
  • 9. M. Deng, A. Inoue, K. Edahiro, '‘Fault detection in a thermal process control system with input constraints using a robust right coprime factorization approach’' Proc. IMechE Part I: J. Systems and Control Engineering (2007) Google Scholar
  • 10. M. Deng, A. Inoue, K. Ishikawa, '‘Operator-based nonlinear feedback control design using robust right coprime factorization’' IEEE Trans. on Autom. Control (2006) Google Scholar
  • 11. M. Deng, A. Inoue, Q. Zhu, '‘An integrated study procedure on real time estimation of time varying multijoint human arm viscoelasticity’' Transactions of the Institute of Measurement and Control (2011a) Google Scholar
  • 12. M. Deng, S. Wen, A. Inoue, '‘Sensorless anti-swing robust nonlinear control for travelling crane system using SVR with generalized Gaussian function and robust right coprime factorization’' Transactions of the Institute of Systems, Control and Information Engineers (2011b) Google Scholar
  • 13. M. Deng, C. Jiang, A. Inoue, '‘Robust stability of nonlinear system with modified Prandtl-Ishlinskii hysteresis model’' International Journal of Modelling, Identification and Control (2010) Google Scholar
  • 14. Z. Kang, S. Fujii, C. Zhou, K. Ogata, '‘Adaptive control of a planar gantry crane by the switching of controllers’' Trans. of the Society of Instrument and Control Engineers (1999) Google Scholar
  • 15. F. Liang, C. Liu, N. Wang, '‘A robust sequential Bayesian method for identification of differentially expressed genes’' Statistica Sinica (2007) Google Scholar
  • 16. A.B.D. Paice, J.B. Moore, R. Horowitz, '‘Nonlinear feedback systems stability via coprime factorization analysis’' J. Math. Syst., Estimat. Control (1992) Google Scholar
  • 17. O. Sawodny, H. Aschemann, S. Lahres, '‘An automated gantry crane as a large workspcae robot’' Control Engineering Practice (2002) Google Scholar
  • 18. B. Scholkopf, C.J.C. Burges, A.J. Smola, Advances in Kernel Methods-Support Vector Learning (1999) Google Scholar
  • 19. M.I. Solihin, '‘Sensorless anti-swing control of automatic gantry crane using dynamic recurrent neural network-based soft sensor’' International Journal of Intelligent Systems Technologies and Applications (2009) Google Scholar
  • 20. P. Tomei, '‘Adaptive PD Controller for robot manipulator’' IEEE Tran. on Automatic Control (1992) Google Scholar
  • 21. R. Toxqui, W. Yu, X. Li, '‘Anti-swing control for overhead crane with neural compensation’' in Proc. International Joint Conference on Neural Networks (2006) Google Scholar
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