Hernadi, Julan
*Numerical and Experimental for Optimal Sensor Location in Lumped and Distributed Parameter System.*
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## Abstract

In estimating parameters, a small sample with high information content is preferable to a large sample but there is insufficient information. Therefore, the selecting of the optimal sensor location becomes a crucial problem in parameter estimation. The problem of determining an estimation through sampling data is a part of the inverse problems. Generally, the inverse problem has no solution in the ordinary sense because in most cases the known data have been contaminated with noises. The minimizer of the least square functional is usually taken as the solution to the inverse problem. This article demonstrates how to implement numerically the inverse problems in relation to parameter estimation when the noise set is generated independently during the experiment. The numerical simulation is applied to a distributed parameter system of the parabolic equation to find the optimal sensor locations for the parameter as well as to a model of a dynamic system to obtain the optimal time for measurements. Based on the result of the numerical experiment, it is found that different parameters in the same system could have different optimal samples.

Index Terms—optimal sensor location, optimal design, FIM, parameter estimation.

Item Type: | Artikel Dosen |
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Subjects: | Q Science > QA Mathematics Q Science > QA Mathematics > QA75 Electronic computers. Computer science |

Divisi / Prodi: | Faculty of Applied Science and Technology (Fakultas Sains Dan Teknologi Terapan) > S1-Mathematics (S1-Matematika) |

Depositing User: | Dr. Julan Hernadi |

Date Deposited: | 04 Jan 2023 02:54 |

Last Modified: | 04 Jan 2023 02:54 |

URI: | http://eprints.uad.ac.id/id/eprint/38404 |

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