A receding-horizon regulator for nonlinear systems and a neural approximation

@article{Parisini1995ARR,
  title={A receding-horizon regulator for nonlinear systems and a neural approximation},
  author={Thomas Parisini and Riccardo Zoppoli},
  journal={Automatica},
  year={1995},
  volume={31},
  pages={1443-1451}
}
Abstiaet-A receding-horizon (RH) optimal control scheme for a discrete-time nonlinear dynamic system is presented. A nonquadratic cost function is considered, and constraints are imposed on both the state and control vectors. Two main contributions are reported. The first consists in deriving a stabilizing regulator by adding a proper terminal penalty function to the process cost. The control vector is generated by means of a feedback control law computed off line instead of computing it on… CONTINUE READING
Highly Influential
This paper has highly influenced 10 other papers. REVIEW HIGHLY INFLUENTIAL CITATIONS
Highly Cited
This paper has 187 citations. REVIEW CITATIONS
107 Extracted Citations
18 Extracted References
Similar Papers

Citing Papers

Publications influenced by this paper.
Showing 1-10 of 107 extracted citations

187 Citations

01020'97'00'04'08'12'16
Citations per Year
Semantic Scholar estimates that this publication has 187 citations based on the available data.

See our FAQ for additional information.

Referenced Papers

Publications referenced by this paper.
Showing 1-10 of 18 references

Robust receding

  • H. Michalska, D. Q. Mayne
  • 1993
Highly Influential
4 Excerpts

Receding horizon

  • D. Q. Mayne, H. Michalska
  • 1990
Highly Influential
5 Excerpts

Regularization theory , radial basis functions and networks

  • V. Cherkassky, J. H. Friedman, H. Wechsler
  • From Statistics to Neural Networks . Theory and…
  • 1994

Regularization theory, radial basis functions

  • F. Girosi
  • 1994
2 Excerpts

A neural receding

  • T. Parisini
  • Zoppoh
  • 1993

Robust receding horizon control of constrained nonlinear systems

  • T. Parisini, R. Zoppoh
  • IEEE Trans
  • 1993

A simple lemma on greedy

  • L. K. Jones
  • 1992
2 Excerpts

A simple lemma on greedy approximation in Hilbert space and convergence rates for projection pursuit regression and neural network training

  • L. K. Jones
  • Ann . Statist .
  • 1992
1 Excerpt

Similar Papers

Loading similar papers…