On joint optimal experiment design for identifying partition and local model parameters of Takagi-Sugeno models

Kroll, Andreas; Dürrbaum, Axel

doi:10.1016/j.ifacol.2015.12.333

Cited by 6 publications

(3 citation statements)

References 11 publications

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“…The main drawback of both works is that this method demands prior knowledge of the target system. In Himmelsbach and Kroll 18 and Kroll and Du¨rrbaum, 22 a scalar measure of FIM was used to determine the optimum experimental design to identify TS (Takagi-Sugeno) fuzzy models. These works are limited due to the choice of FIM measure, which impacts the computational cost.…”

Section: Motivation and Literature Reviewmentioning

confidence: 99%

An optimized excitation signal design for identification of PWA model and application to automotive throttles

Ren

2022

Measurement and Control

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In the automotive application for Electronic Control Units (ECU), dynamic models with high-precision to simulate mechatronic actuators are required for various analysis and design tasks like Hardware-in-the-Loop (HiL) simulation. It is known that the modeling of systems with significant friction effects is not accessible. The piecewise-affine (PWA) model has recently attracted considerable interest due to its high approximation capability for modeling systems with friction. Because the model quality depends intensely on the test signal design, a model-free optimized excitation signal design for identifying PWA models is presented in this paper. The presented method is demonstrated with an automotive throttle, and a PWA model is identified with a four-step identification approach. The result shows that the optimization method can achieve a better model quality, which is sufficient for the HiL simulation.

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Section: Motivation and Literature Reviewmentioning

confidence: 99%

An optimized excitation signal design for identification of PWA model and application to automotive throttles

Ren

2022

Measurement and Control

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“…The minimization of a measure on the FIM is an OED approach and is the focus of this contribution. Kroll and Du ¨rrbaum [13] and Du ¨rrbaum and Kroll [14] are motivations for this work. In Kroll and Du ¨rrbaum [13], the FIM is used to determine the optimum experiment design for the estimation of the parameters of a static TS model.…”

Section: Literature Overviewmentioning

confidence: 99%

“…Kroll and Du ¨rrbaum [13] and Du ¨rrbaum and Kroll [14] are motivations for this work. In Kroll and Du ¨rrbaum [13], the FIM is used to determine the optimum experiment design for the estimation of the parameters of a static TS model. Only the determinant is used as a scalar measure on the FIM.…”

Section: Literature Overviewmentioning

confidence: 99%

On Optimal Test Signal Design and Parameter Identification Schemes for Dynamic Takagi-Sugeno Fuzzy Models Using the Fisher Information Matrix

Himmelsbach

Kroll

2021

Int. J. Fuzzy Syst.

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This paper is concerned with the analysis of optimization procedures for optimal experiment design for locally affine Takagi-Sugeno (TS) fuzzy models based on the Fisher Information Matrix (FIM). The FIM is used to estimate the covariance matrix of a parameter estimate. It depends on the model parameters as well as the regression variables. Due to the dependency on the model parameters good initial models are required. Since the FIM is a matrix, a scalar measure of the FIM is optimized. Different measures and optimization goals are investigated in three case studies.

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On considering the output in space-filling test signal designs for the identification of dynamic Takagi-Sugeno models

Gringard

Kroll

2020

IFAC-PapersOnLine

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On joint optimal experiment design for identifying partition and local model parameters of Takagi-Sugeno models

Cited by 6 publications

References 11 publications

An optimized excitation signal design for identification of PWA model and application to automotive throttles

An optimized excitation signal design for identification of PWA model and application to automotive throttles

On Optimal Test Signal Design and Parameter Identification Schemes for Dynamic Takagi-Sugeno Fuzzy Models Using the Fisher Information Matrix

On considering the output in space-filling test signal designs for the identification of dynamic Takagi-Sugeno models

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