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Coursecode: wb2301
Coursename: Systeemidentification and
Parameter Estimation
ECTS credit points: 7 |
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Faculty
of Mechanical
Engineering and Marine Technology |
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Lecturer(s):
Van der Helm, Prof.dr.
F.C.T. |
Tel.:
015-27 85616 |
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Catalog
data:
Non-parametric system identification based on estimators of spectral
densities. Application to open-loop and closed-loop systems. Parameter
estimation for linear and non-linear systems. |
Course year:
MSc 1st year
Semester: 2A / 2B
Hours p/w: 2
Other hours:
-
Assessment: see remarks
Assessment period: on
appointment |
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Prerequisites:
wb2206 |
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Follow-up: |
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Uitgebreide
beschrijving van het onderwerp:
- Analysis of unknown dynamic
systems in the time-domain and the frequency domain
- Application to relation
between transferfunctions and spectral densities in open-loop and
closed-loop systems.
- Modelling of systems: Choice
of model structure and –parametrisation
- Linear and non-linear model
structures
- Parameter estimation by
optimization
- Optimization techniques:
Gradient methods, random-search methods, genetic
algorithms
- Experimental validation of
models: Coherence, Variance-Accounted-For (VAF)
- Special non-linear model
structures: Expert systems, neural networks, fuzzy models.
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Course material
(available through Blackboard website):
Dictaat Signaalanalyse,
Van Lunteren / Dankelman (in Dutch)
Dictaat Systeemidentification
A
Overheads
Demonstration programs in Matlab |
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Literature
references:
- Jenkins G.M. and Watts D.G.
(1968). Spectral analysis and its applications. Holden Day, San
Francisco.
- Priestly M.B. (1981).
Spectral analysis and time series. Academic Press, London. ISBN
0-12-564922-3.
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Remarks:
In this course many small
assignments will be required. The course will be finished with a larger
assigment, in the data processing of experimental data. Oral exam will be
taken based on a written report of the final assigment. |
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Goal:
The course is aimed at
research methods to analyse unknown, dynamic systems based on recorded
signals. After the course you will be able to appy non-parametric
techniques in open-loop and closed-loop systems, to make an adequate
choice of model structures and parameters, and estimate the parameters
based on optimization methods. |
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Computer
use:
Practical assignments on a PC with a number of available programs in
MATLAB/SIMULINK |
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Final
Assignment:
At the end of the course, a choice can be made out of three final
assignments, for which recorded signals are available. The available
demonstration programs have to be adapted in order to estimate a proper
transfer function, and proper model parameters. |
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Design
content:
n.a.. |
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Percentage of
Design:
0%
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