On joint optimal experiment design for identifying partition and local model parameters of Takagi-Sugeno models
A. Kroll, and A. Dürrbaum.
Proceedings of the 17th IFAC Symposium on System Identification (SysID), page 1427 -- 1432. Beijing, China, (October 2015)

Optimal Experiment Design (OED) is a well-developed concept for regression problems that are linear-in-their-parameters or for linear dynamical models. In case of nonlinear Takagi-Sugeno models either non-model-based experiment design or OED restricted to the local model parameters has been examined. This article proposes a joint design of local model and partition parameters that bases on the Fisher Information Matrix (FIM). For this purpose, a symbolic description of the joint FIM is derived. Its heterogeneous structure can make it badly conditioned, complicating computation of the determinant for D-optimal design. This problem is relaxed using determinant decomposition. A theoretical analysis and a case study show that experiment design for local model and partition parameters may significantly differ from each other.

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@inproceedings{Duerrbaum-2015-SysID,
  abstract = {Optimal Experiment Design (OED) is a well-developed concept for regression problems that are linear-in-their-parameters or for linear dynamical models. In case of nonlinear Takagi-Sugeno models either non-model-based experiment design or OED restricted to the local model parameters has been examined. This article proposes a joint design of local model and partition parameters that bases on the Fisher Information Matrix (FIM). For this purpose, a symbolic description of the joint FIM is derived. Its heterogeneous structure can make it badly conditioned, complicating computation of the determinant for D-optimal design. This problem is relaxed using determinant decomposition. A theoretical analysis and a case study show that experiment design for local model and partition parameters may significantly differ from each other.},
  added-at = {2022-03-31T09:31:59.000+0200},
  address = {Beijing, China},
  author = {Kroll, Andreas and Dürrbaum, Axel},
  biburl = {https://puma.uni-kassel.de/bibtex/2a62f4bcd0dac434df35ebba90261698d/00987301},
  booktitle = {Proceedings of the 17th IFAC Symposium on System Identification ({SysID})},
  doi = {doi:10.1016/j.ifacol.2015.12.333},
  interhash = {c8b8e8d219667b0df23b145097939fd4},
  intrahash = {a62f4bcd0dac434df35ebba90261698d},
  keywords = {Nonlinear Takagi-Sugeno design, experiment fuzzy identification, optimal system systems},
  language = {english},
  month = {October 19-21},
  mrtnote = {peer,talk:Dürrbaum,oed},
  pages = {1427 -- 1432},
  timestamp = {2022-03-31T09:42:48.000+0200},
  title = {On joint optimal experiment design for identifying partition and local model parameters of Takagi-Sugeno models},
  year = 2015
}

%0 Conference Paper
%1 Duerrbaum-2015-SysID
%A Kroll, Andreas
%A Dürrbaum, Axel
%B Proceedings of the 17th IFAC Symposium on System Identification (SysID)
%C Beijing, China
%D 2015
%K Nonlinear Takagi-Sugeno design, experiment fuzzy identification, optimal system systems
%P 1427 -- 1432
%R doi:10.1016/j.ifacol.2015.12.333
%T On joint optimal experiment design for identifying partition and local model parameters of Takagi-Sugeno models
%X Optimal Experiment Design (OED) is a well-developed concept for regression problems that are linear-in-their-parameters or for linear dynamical models. In case of nonlinear Takagi-Sugeno models either non-model-based experiment design or OED restricted to the local model parameters has been examined. This article proposes a joint design of local model and partition parameters that bases on the Fisher Information Matrix (FIM). For this purpose, a symbolic description of the joint FIM is derived. Its heterogeneous structure can make it badly conditioned, complicating computation of the determinant for D-optimal design. This problem is relaxed using determinant decomposition. A theoretical analysis and a case study show that experiment design for local model and partition parameters may significantly differ from each other.

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On joint optimal experiment design for identifying partition and local model parameters of Takagi-Sugeno models
A. Kroll, and A. Dürrbaum.
Proceedings of the 17th IFAC Symposium on System Identification (SysID), page 1427 -- 1432. Beijing, China, (October 2015)

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PUMA

On joint optimal experiment design for identifying partition and local model parameters of Takagi-Sugeno modelsA. Kroll, and A. Dürrbaum. Proceedings of the 17th IFAC Symposium on System Identification (SysID), page 1427 -- 1432. Beijing, China, (October 2015)

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Cite this publication

On joint optimal experiment design for identifying partition and local model parameters of Takagi-Sugeno models
A. Kroll, and A. Dürrbaum.
Proceedings of the 17th IFAC Symposium on System Identification (SysID), page 1427 -- 1432. Beijing, China, (October 2015)