Project VirtUE
Dynamic System Identification
ID3: ARX IDENTIFICATION
ID3.1 ARX models
ID3.2 ARX predictors
ID3.3 Least squares estimate of ARX models
ID3.4 Identifiability and input selection
ID3.5 Bias and consistency of least squares estimates
ID3.6 Recursive least squares
ID3.7 Weighted least squares
ID3.8 Covariance of least squares estimates
ID3.9 Distribution of estimation errors
ID3.10 Statistical properties of residuals
ID3.11 Cramér-Rao lower bound
ID3.12 Efficiency of least squares estimates
ID3.13 Kalman filtering in recursive estimation
ID3.14 Order estimation and model validation
ID3.15 Example (batch identification)
ID3.16 Example (on-line identification)
ID3.17 Multivariable ARX models and predictors
ID3.18 Parametric identification of multivariable ARX models
ID3.19 Bias and consistency of multivariable LS estimates
ID3.20 Structural identification of multivariable ARX models
ID3.21 Example - Identification of a power plant
ID3.22 State space ARX models
ID3.23 Sensitivity analysis of identified models
ID3.Q Questions
ID3.F Frequently Asked Questions
Power plants are complex multivariable systems whose modeling by traditional techniques faces difficult compromises between model complexity and accuracy. Example ID3.21, concerning the power plant of Pont-sur-Sambre (last picture), is a good example of the possibilities offered by identification in this area.
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