Peszko, Aleksander (2023) Identification of LTI system with auxiliary data from a similar system. Integration Project, Industrial Engineering and Management.
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Abstract
This report describes the dynamical system identification with limited access to the data. The goal of the research is to prove that leveraging data from a similar system can reduce the identification error by complementing the original system’s data with additional data from the auxiliary system. The identification will be performed using the regression analysis method of weighted least squares. Once the error is identified, a detailed analysis of the influencing factors will be provided. It includes altering various parameters such as process noise, number of experiments and weight parameter in order to observe the behaviour of the error and ideally reduce it. The experimental setup includes two linear time-invariant (LTI) systems, namely target and source systems that will be subjected to the identification, and based on the obtained results, I will draw conclusions and validate the theoretical assumptions.
| Item Type: | Thesis (Integration Project) |
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| Supervisor name: | Monshizadeh Naini, N. |
| Degree programme: | Industrial Engineering and Management |
| Thesis type: | Integration Project |
| Language: | English |
| Date Deposited: | 15 Feb 2023 09:46 |
| Last Modified: | 15 Feb 2023 09:46 |
| URI: | https://fse.studenttheses.ub.rug.nl/id/eprint/29255 |
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