# Examples

## Contents

## LTI model identification

- Example 1: Fourth-order LTI model with coloured process noise in closed loop
- Example 2: Fourth-order LTI model without process noise in closed loop
- Example 3: High-order LTI model of acoustical duct
- Example 4: LTI model of a Coleman tranformed wind turbine system
- Example 5: LTI model of a Coleman tranformed wind turbine system with batches of data
- Example 6: Uncertainty bounds on estimation using first-order variance for PBSIDopt
- Example 7: Uncertainty bounds on estimation using Monte-Carlo simulations
- Example 8: Uncertainty bounds on estimation using Bootstrap simulations
- Example 9: PBSIDopt identification of Smart Rotor with periodic effects

## Recursive-LTI model identification

- Example 10: Fast-varying Recursive LTI model in open loop
- Example 11: Slow-varying Recursive LTI model in open loop
- Example 12: Fast-varying Recursive LTI model in closed loop
- Example 13: Slow-varying Recursive LTI model in closed loop

## Hammerstein/Wiener model identification

## LPV model discretization

- Example 17: Discretization of continuous LPV model of F-16
- Example 18: Discretization of continuous LPV model of wing flutter

## LPV model identification

- Example 19: Second-order LPV model of flapping dynamics
- Example 19b: Stabilizing the predictor form of the LPV model of the flapping dynamics
- Example 19c: Using sparse estimation in the identification of a second-order LPV model
- Example 20: Fourth-order MIMO LPV model

## Periodic-LPV model identification

- Example 21: Second-order Periodic-LPV model of flapping dynamics
- Example 22: Third-order SIMO Periodic-LPV model
- Example 23: Periodic-LPV model of a wind turbine system

## Tensor Nuclear Norm identification

- Example 24: Identification using tensor nuclear norms of a second and fourth order LPV model