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