Sorry, you need to enable JavaScript to visit this website.

  • 7:33 PM, Monday, 18 Oct 2021


Course Postgraduate
Semester Electives
Subject Code AVC869
Subject Title System Identification and Parameter Estimation

Syllabus

Introduction, discrete systems, basic signal theory , Open‐loop LTI SISO systems, time domain, frequency domain
Least Squares Estimation, Covariance in Stationary, Ergodic Processes, White Noise, Detection of Periodicity and Transmission Delays, ARMA Processes.

Non‐parametric identification: correlations and spectral analysis, Subspace identification, Identification with “Prediction Error”‐methods: prediction, model structure, approximate models, order selection, validation, ARX and ARMAX Input Models, Ourput Error Model, Box‐Jenkins Model

Non‐linear model equations, Linearity in the parameters, Identifiability of parameters, Error propagation, MIMO‐systems, Identification in the frequency domain, Identification of closed loop systems, Non‐linear optimization

Text Books

Same as Reference

References
  1. Karl Johan Åström, Lectures on system identification ‐ Part 3, Department of Automatic Control, .Lund Institute of Technology, 1975
  2. T. Söderström and P. Stoica, System Identification, Prentice Hall, 1989.
  3. L Ljung, System identification – Theory for the user, Pearson Education, 1998.
  4. Jerry M. Mendel, Lessons in Digital Estimation Theory, Prentice Hall, 1987.
  5. Steven M. Kay, Fundamentals of Statistical Signal Processing, Prentice Hall, 2013.