Closed-loop nonlinear system identification via the vector optimal parameter search algorithm: application to heart rate baroreflex control.

@article{Wang2007ClosedloopNS,
  title={Closed-loop nonlinear system identification via the vector optimal parameter search algorithm: application to heart rate baroreflex control.},
  author={Hengliang Wang and Kihwan Ju and Ki H. Chon},
  journal={Medical engineering & physics},
  year={2007},
  volume={29 4},
  pages={505-15}
}
The vector optimal parameter search (VOPS) and the constrained optimal parameter search (COPS) are recently developed algorithms for closed-loop linear system identification. We extend both algorithms to be applicable to a closed-loop nonlinear system, which is characterized by a vector nonlinear autoregressive model. Monte Carlo simulations of nonlinear closed-loop systems were performed to compare the performance of the VOPS to the widely utilized vector least squares (VLS), the COPS and the… CONTINUE READING
Highly Cited
This paper has 68 citations. REVIEW CITATIONS

From This Paper

Topics from this paper.

Citations

Publications citing this paper.
Showing 1-10 of 10 extracted citations

Assessing causality in normal and impaired short-term cardiovascular regulation via nonlinear prediction methods.

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences • 2009
View 6 Excerpts
Highly Influenced

Refined instrumental variable methods for identifying hammerstein models operating in closed loop

Proceedings of the 48h IEEE Conference on Decision and Control (CDC) held jointly with 2009 28th Chinese Control Conference • 2009

Robust estimation of Partial Directed Coherence by the vector optimal parameter search algorithm

2009 4th International IEEE/EMBS Conference on Neural Engineering • 2009
View 1 Excerpt

68 Citations

050100'10'12'14'16'18
Citations per Year
Semantic Scholar estimates that this publication has 68 citations based on the available data.

See our FAQ for additional information.

Similar Papers

Loading similar papers…