Robust multi-stage model-based design of optimal experiments for nonlinear estimation

@article{Mukkula2020RobustMM,
  title={Robust multi-stage model-based design of optimal experiments for nonlinear estimation},
  author={A. R. G. Mukkula and Michal Mate{\'a}s and M. Fikar and R. Paulen},
  journal={ArXiv},
  year={2020},
  volume={abs/2011.06042}
}
We study approaches to robust model-based design of experiments in the context of maximum-likelihood estimation. These approaches provide robustification of model-based methodologies for the design of optimal experiments by accounting for the effect of the parametric uncertainty. We study the problem of robust optimal design of experiments in the framework of nonlinear least-squares parameter estimation using linearized confidence regions. We investigate several well-known robustification… Expand

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