VVZ API is not affiliated with ETH Zurich. Data might be outdated or incorrect. Please view the official ETHZ Vorlesungsverzeichnis for binding information.

227-0689-00L 4 Credits DR , MSC , WBZ D-ITET , D-MATH , D-INFK , D-MAVT
You're viewing possible stale or outdated data. Please check the latest semester for more up-to-date information.

System Identification

Lecturers & Examiners: Prof. em. Dr. Roy Smith
VVZ CR n/a

Last Updated: 2026-02-05 16:02:00

Abstract

Theory and techniques for the identification of dynamic models from experimentally obtained system input-output data.

Objective

To provide a series of practical techniques for the development of dynamical models from experimental data, with the emphasis being on the development of models suitable for feedback control design purposes. To provide sufficient theory to enable the practitioner to understand the trade-offs between model accuracy, data quality and data quantity.

Content

Introduction to modeling: Black-box and grey-box models; Parametric and non-parametric models; ARX, ARMAX (etc.) models. Predictive, open-loop, black-box identification methods. Time and frequency domain methods. Subspace identification methods. Optimal experimental design, Cramer-Rao bounds, input signal design. Parametric identification methods. On-line and batch approaches. Closed-loop identification strategies. Trade-off between controller performance and information available for identification.

Resources

Literature

"System Identification; Theory for the User" Lennart Ljung, Prentice Hall (2nd Ed), 1999. Additional papers will be available via the course Moodle.

General Information

Language
English
Levels
DR , MSC , WBZ
Frequency
Yearly recurring

Examination

Type
graded semester performance

Course Components

Type Title Time & Place Hours
lecture System Identification
  • Wed 10:15-12:00 (HG D 1.1)
2 h weekly
exercise System Identification
  • Wed 12:15-13:00 (ETZ D 61.1)
  • Wed 12:15-13:00 (HG D 1.1)
1 h weekly

Offered In