Program

PROGRAM OF THE 7th SPRING SCHOOL on

Data-Driven Model Learning of Dynamic Systems

Basics of linear system identification 

Lectures on Monday 8 April (afternoon) and on Tuesday 9 April (all day)

Exercises on Wednesday 10 April (morning)

Lecturer: Xavier Bombois, CNRS Research Director, Laboratoire Ampère, Ecole Centrale de Lyon 

Theme 1: Introduction;concepts; identification cycle

Theme 2: Parametric (prediction error) identification methods: prediction criterion and model structures, linear and pseudo-linear regressions, conditions on data, statistical and asymptotic properties, model set selection and model validation

Theme 3: Non-parametric identification (ETFE)

Theme 4: Experiment design.

Closed-loop identification 

Lecture on Wednesday 10 April (14:00-15:00)

Lecturer: Xavier Bombois, CNRS Research Director, Laboratoire Ampère, Ecole Centrale de Lyon

Theme 1: Direct closed-loop method

Theme 2: indirect closed-loop methods

Gray-box and black-box state-space model learning

Lectures on Wednesday 10 April (15:00-18:00) and Thursday 11 April (morning)

Lecturer: Guillaume Mercère, Associate Professor, Laboratoire LIAS, Université de Poitiers

Theme 1: Black-box model learning: subspace state-space model identification

Theme 2: Gray-box model learning: nonlinear least-squares state-space model identification

Theme 3: From black-box to gray-box models

Dynamic Network Identification

Lectures on Thursday 11 April (afternoon) and Friday 12 April (morning)

Lecturer: Paul Van den Hof, Professor, TU Eindhoven, The Netherlands

Theme 1: Modelling and identification problems in dynamic networks

Theme 2: Network identifiability

Theme 3: Single module identification

Theme 4: SYSDYNET Matlab Toolbox