The Transactions of The Korean Institute of Electrical Engineers (전기학회논문지)

The Korean Institute of Electrical Engineers (대한전기학회)
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Neural-networks-based Disturbance Observer and Tracker Design in the Presence of Unknown Control Direction and Non-affine Nonlinearities

미지의 제어 방향성과 비어파인 비선형성을 고려한 신경망 기반 외란 관측기와 추종기 설계

  • Kim, Hyoung Oh (School of Electrical and Electronics Engineering, Chung-Ang University) ;
  • Yoo, Sung Jin (School of Electrical and Electronics Engineering, Chung-Ang University)
  • Received : 2016.11.23
  • Accepted : 2017.03.09
  • Published : 2017.04.01
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Abstract

A disturbance-observer-based adaptive neural tracker design problem is investigated for a class of perturbed uncertain non-affine nonlinear systems with unknown control direction. A nonlinear disturbance observer (NDO) design methodology using neural networks is presented to construct a tracking control scheme with the attenuation effect of an external disturbance. Compared with previous control results using NDO for nonlinear systems in non-affine form, the major contribution of this paper is to design a NDO-based adaptive tracker without the sign information of the control coefficient. The stability of the closed-loop system is analyzed in the sense of Lyapunov stability.

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References

  1. S. S. Ge, and C. Wang, "Adaptive NN control of uncertain nonlinear pure-feedback systems," Automatica, vol. 38, No. 4, pp. 671-682, 2002. https://doi.org/10.1016/S0005-1098(01)00254-0
  2. D. Wang, and J. Huang, "Adaptive neural network control for a class of uncertain nonlinear systems in pure-feedback form," Automatica, vol. 38, No. 8, pp. 1365-1372, 2002. https://doi.org/10.1016/S0005-1098(02)00034-1
  3. T. P. Zhang, S. S. Ge, "Adaptive dynamic surface control of nonlinear systems with unknown dead zone in purefeedback form," Automatica, vol. 44, No. 7, pp. 1895-1903, 2008. https://doi.org/10.1016/j.automatica.2007.11.025
  4. B. Miao, and T. Li, "A novel neural network-based adaptive control for a class of uncertain nonlinear systems in strict-feedback form," Nonlinear Dyn., vol. 79, No. 2, pp. 1005-1013, 2015. https://doi.org/10.1007/s11071-014-1717-2
  5. W. H. Chen, "Disturbance observer based control for nonlinear systems," IEEE/ASME Trans. Mechatron., vol. 9, No. 4, pp. 706-710, 2004. https://doi.org/10.1109/TMECH.2004.839034
  6. M. Chen and S. S. Ge, "Direct adaptive neural control for a class of uncertain nonaffine nonlinear systems based on disturbance observer," IEEE Trans. Cybern., vol. 43, No. 4, pp. 1213-1225, 2013. https://doi.org/10.1109/TSMCB.2012.2226577
  7. R. D. Nussbaum, "Some remarks on the conjecture in parameter adaptive control," Syst. Contr. Lett., vol. 3, pp. 243-246, 1983. https://doi.org/10.1016/0167-6911(83)90021-X
  8. C. Wang, D. J. Hill, S. S. Ge, and G. Chen, "An ISSmodular approach for adaptive neural control of purefeedback systems," Automatica, vol. 42, No. 5, pp. 723-731, 2006. https://doi.org/10.1016/j.automatica.2006.01.004
  9. S. Lang, Real analysis reading. Addison Wesley, MA, 1983.
  10. J. Park, I. W. Sandberg, "Universal approximation using radial-basis function networks," Neural Comput., vol. 3, pp. 246-257, 1991. https://doi.org/10.1162/neco.1991.3.2.246
  11. P. A. Ioannout, and P. V. Kokotovic, Adaptive systems with reduced models. New York: Springer, 1983.
  12. E. P. Ryan, A universal adaptive stabilizer for a class of nonlinear systems, Syst. Control Lett. vol. 16, pp. 209-218, 1991. https://doi.org/10.1016/0167-6911(91)90050-O
  13. Y. S. Lee, A. F. Vakakis, L. A. Bergman, and D. M. McFarland, "Suppression of limit cycle pscillations in the Van der Pol oscillator by means of passive non- linear energy sinks," Struct. Control Health Monit., vol. 13, No. 1, 2006. https://doi.org/10.1002/stc.151
  14. B. Karimi, M. B. Menhaj, and I. Saboori, "Robust adaptive control of nonaffine nonlinear systems using radial basis function neural networks," Proc., 32nd IEEE Conf., on Industrial Electronics, pp 495-500, 2006.
  15. H. O. Kim and S. J. Yoo, "Disturbance-observer-based Aadaptive neural tracking of uncertain non-affine nonlinear systems with unknown control direction" Conf. Information and Control Systems(CICS) (in Korean), pp. 146-147, 2016.