Identification Techniques

Subject Credits: 3

Subject Coefficient: 2

Evaluation method:  Continuous assessment: 40%  Final exam: 60%.

Targeted Competencies:  

System identification is a powerful technique used to build models of complex systems in various fields of engineering. Unlike traditional modeling approaches that rely heavily on physical laws governing the system, system identification is primarily based on measured input–output data and prior knowledge of the system. These elements are sufficient to construct a simplified yet accurate model that effectively captures and reproduces the real system’s behavior.

Upon successful completion of this course, the student will be able to:

1.           Understand the fundamental concepts of system identification and distinguish between physical modeling and data-driven modeling approaches.
2.            Collect and preprocess experimental data for the purpose of building accurate input–output models.
3.            Develop mathematical models (ARX, ARMAX, …) that represent dynamic systems from measured data.

Brief Content

1. Equation Error-Based Identification

2. Instrumental Variables Method

3. Prediction Error Method

4. Closed-Loop Identification

5. Practical Aspects of System Identification

6. Model Validation