Stability analysis of the RBF-ARX model based nonlinear predictive control

@article{Peng2003StabilityAO,
  title={Stability analysis of the RBF-ARX model based nonlinear predictive control},
  author={Hong-ying Peng and Takemasa Ozaki and Kazushi Nakano and Valerie Haggan-Ozaki and Yukihiro Toyoda},
  journal={2003 European Control Conference (ECC)},
  year={2003},
  pages={3129-3134}
}
This paper gives stability analysis of the nonlinear predictive control strategy based on the off-line identified RBF-ARX model which is a pseudo-linear time-varying ARX model with system working-point dependent Gaussian RBF neural network style coefficients. The predictive controller doesn't require on-line parameter estimation; it may be applied to a class of smooth nonlinear processes whose working-point varies over a wide range. Stability analysis of the nonlinear predictive controller is… CONTINUE READING

References

Publications referenced by this paper.
Showing 1-8 of 8 references

Nonlinear predictive control based on a global model identified off-line

  • H. Peng, T. Ozaki, Y. Toyoda
  • 2002
3 Excerpts

Model-based predictive control for Hammerstein-Wiener systems

  • H.H.J. Bloemen, T.J.J. Van Den Boom, H. B. Verbruggen
  • 2001
1 Excerpt

Non-linear generalized predictive control (NLGPC) applied to muscle relaxant anaesthesia

  • M. Mahfouf, D. A. Linkens
  • 1998
1 Excerpt

Improvement of de-NOx device control performance using software sensor

  • S. Matsumura, T. Iwahara, K. Ogata, S. Fujii, M. Suzuki
  • 1997
1 Excerpt

Slowly varying discrete system

  • C. A. Desoer
  • 1970
1 Excerpt

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