4 ECTS credits
110 h study time
Offer 1 with catalog number 4019830ENR for all students in the 2nd semester at a (E) Master - advanced level.
Content under construction. For more detailed information please consult the course sheet of the equivalent English course ID009085 or contact the faculty secretariat.
Engineers and scientists built models to understand, describe, predict and control the behaviour of the environment. In order to create these models it is necessary to combine the mathematical models with (noisy) measurements. In this course general methods are given in order to obtain good measurements, and to use these data to build a model.
Measurement techniques
- Spectral measurements.
- Spectral analysis (FFT based + scanning tech. for radio frequencies(RF))
- Network analysis for linear time-invariant systems. (FFT based + RFs)
Analog specification of measurement hardware
- Signal conditioning
- Specification of analog front-ends for digital measurement kernels.
- Interference problems.
Stochastic characterisation of measurement problems.
- Used stochastic framework
- Time domain measurements
- Frequency domain measurements
Computer controlled measurement systems
- Overview of interfacing systems
- Overview of existing standards.
- Case study : IEEE-488
- Why do we need identification methods?
- The 'ideal' estimator
- A systematic approach of the identification problem
- Estimation in the presence of errors on the input and output data.
- Model selection and validation
- Numerical optimization methods
- Recursive identification
- Kalman filtering
The lessons are given in English.
Dutch speaking students can always put their questions during the lessons and labo's in Dutch. The oral exams will be in Dutch for those students, and in English for the others. Lecture notes are partly in Dutch and partly in English are available.
Complementary study material:
P. Eykhoff, System Identification, London, John Wiley and Sons, 1974.
G.C. Goodwin and R.L. Payne, Dynamic System Identification. New York, Academic Press, 977.
L. Ljung, System Idnetification : theory for the user. Englewood Cliffs, Prentice-Hall, 1987.
J. P. Norton, An Introduction to Identification. London, Academic Press, 1986.
J. Schoukens and R. Pintelon, Identification of Linear Systems : A practical guideline for acuurate modeling. London, Pergamon Press 1991.
T. Soderstrom and P. Stoica, System Identification, Englewood Cliffs, Prentice-Hall, 1998.
The Fast Fourier Transform ( Oran E Brigham - Addison Wesley )
System Identification. A frequency domain approach. Pintelon and Schoukens. IEEE press, John Wiley, 2001.
Solving interference problems in electronics ( Morrisson - Wiley )
+ IEEE 488.2 Standard. (IEEE Press)
-aims and objectives :
Under construction. For more detailed information please consult the course sheet of the equivalent English course ID009085 or contact the faculty secretariat.
The final grade is composed based on the following categories:
Oral Exam determines 100% of the final mark.
Within the Oral Exam category, the following assignments need to be completed:
Oral examination on the theory and lab. Emphasis is on the understanding of the material, just reproducing is not enough
Important note: absence at one or more parts of the exam results in an "absence" evaluation for the whole course.
This offer is part of the following study plans:
Master of Chemical and Materials Engineering: Profile Process Technology (only offered in Dutch)
Master of Chemical and Materials Engineering: PR Profile Materials (only offered in Dutch)
Master of Electronics and Information Technology Engineering: Standaard traject (only offered in Dutch)