Introduce the student to the fundamentals of system identification applied to sampled systems (ARX and ARMAX model, ordinary least squares, recursive least squares, bayesian filtering). Introduce the student to sensor fusion. To familiarize the student with the use of the MatLab identification toolbox
Curriculum
teacher profile teaching materials
- Physical laws in engineering and science
- Stochastic processes
- Models for filtering, prediction and control: Input-output models for time series and dynamical systems (AR, ARMA, ARX, ARMAX)
Identification
- Black-box identification (Least Squares and Maximum likelihood methods)
- Model complexity selection
- Cross-validation, FPE (Final Prediction Error), AIC (Akaike Information Criterion) or MDL (Minimum Description Length) techniques
- Recursive identification methods (RLS,ELS,RML). Adaptation via forgetting factor techniques
Bayesian filtering
- The state estimation problem. Filtering, prediction and smoothing.
- Kalman filter, steady-state filter Extended Kalman filter
- Unscented transformation, Unscented Kalman filter
- Grid-based filtering
- Particle filtering
Distributed filtering
- Information filter
- Extended Information filter
Programme
Dynamical models of stationary processes and prediction- Physical laws in engineering and science
- Stochastic processes
- Models for filtering, prediction and control: Input-output models for time series and dynamical systems (AR, ARMA, ARX, ARMAX)
Identification
- Black-box identification (Least Squares and Maximum likelihood methods)
- Model complexity selection
- Cross-validation, FPE (Final Prediction Error), AIC (Akaike Information Criterion) or MDL (Minimum Description Length) techniques
- Recursive identification methods (RLS,ELS,RML). Adaptation via forgetting factor techniques
Bayesian filtering
- The state estimation problem. Filtering, prediction and smoothing.
- Kalman filter, steady-state filter Extended Kalman filter
- Unscented transformation, Unscented Kalman filter
- Grid-based filtering
- Particle filtering
Distributed filtering
- Information filter
- Extended Information filter
Core Documentation
Sergio Bittanti, "Model Identification and Data Analysis", John Wiley and Sons LtdType of delivery of the course
TraditionalType of evaluation
Written test, oral test. teacher profile teaching materials
- Physical laws in engineering and science
- Stochastic processes
- Models for filtering, prediction and control: Input-output models for time series and dynamical systems (AR, ARMA, ARX, ARMAX)
Identification
- Black-box identification (Least Squares and Maximum likelihood methods)
- Model complexity selection
- Cross-validation, FPE (Final Prediction Error), AIC (Akaike Information Criterion) or MDL (Minimum Description Length) techniques
- Recursive identification methods (RLS,ELS,RML). Adaptation via forgetting factor techniques
Bayesian filtering
- The state estimation problem. Filtering, prediction and smoothing.
- Kalman filter, steady-state filter Extended Kalman filter
- Unscented transformation, Unscented Kalman filter
- Grid-based filtering
- Particle filtering
Distributed filtering
- Information filter
- Extended Information filter
Programme
Dynamical models of stationary processes and prediction- Physical laws in engineering and science
- Stochastic processes
- Models for filtering, prediction and control: Input-output models for time series and dynamical systems (AR, ARMA, ARX, ARMAX)
Identification
- Black-box identification (Least Squares and Maximum likelihood methods)
- Model complexity selection
- Cross-validation, FPE (Final Prediction Error), AIC (Akaike Information Criterion) or MDL (Minimum Description Length) techniques
- Recursive identification methods (RLS,ELS,RML). Adaptation via forgetting factor techniques
Bayesian filtering
- The state estimation problem. Filtering, prediction and smoothing.
- Kalman filter, steady-state filter Extended Kalman filter
- Unscented transformation, Unscented Kalman filter
- Grid-based filtering
- Particle filtering
Distributed filtering
- Information filter
- Extended Information filter
Core Documentation
Sergio Bittanti, "Model Identification and Data Analysis", John Wiley and Sons LtdType of delivery of the course
TraditionalType of evaluation
Written test, oral test.