Non-stationary stochastic embedding for transfer function estimation

Automatica

Volumn 38, Issue 1, 2002, Pages 47-62

  Goodwin, Graham C ^a   Braslavsky, Julio H ^b   Seron, María M ^c  

^a UNIVERSITY OF NEWCASTLE   (Australia)

^b UNIVERSIDAD NACIONAL DE QUILMES   (Argentina)

^c UNIVERSIDAD NACIONAL DE ROSARIO   (Argentina)

Author keywords

Error estimation; Least squares estimation; Process identification; Random walk processes; Stochastic modelling; System identification

Indexed keywords

COMPUTER SIMULATION; ERROR ANALYSIS; FREQUENCY DOMAIN ANALYSIS; IDENTIFICATION (CONTROL SYSTEMS); LEAST SQUARES APPROXIMATIONS; MATHEMATICAL MODELS; RANDOM PROCESSES; TRANSFER FUNCTIONS;

ERROR QUANTIFICATION;

STOCHASTIC CONTROL SYSTEMS;

EID: 0036027462     PISSN: 00051098     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0005-1098(01)00186-8     Document Type: Article

References (32)

1. Controller validation for stability and performance based on a frequency domain uncertainty region obtained by stochastic embedding
2. Controller validation tools for stability and performance based on an uncertainty region designed from an identified model
3. Robustness analysis tools for an uncertainty set obtained by prediction error identification
4. Randomized algorithms for probabilistic robustness with real and complex structured uncertainty
5. Quantification of uncertainty in transfer function estimation: A mixed probabilistic-worst-case approach
6. Multivariable feedback design: Concepts for a classical/modern synthesis
7. Non-stationary stochastic embedding for transfer function estimation
8. Quantifying the error in estimated transfer functions with application to model order selection
9. A stochastic embedding approach for quantifying uncertainty in the estimation of restricted complexity models
10. Robust model predictive control via sensitivity augmentation
11. Bias-variance tradeoff issues in robust controller design using statistical confidence bounds
12. A new global optimization method for electronic circuit design
13. Nonparametric frequency response function estimators based on nonlinear averaging techniques
14. A versatile model of a function of unknown and time varying form
15. A new method of locating the maximum point of an arbitrary multipeak curve in the presence of noise
16. Model validation and model error modelling
17. The role of model validation for assessing the size of the unmodelled dynamics
18. Estimation of model quality
19. A unifying construction of orthonormal bases for system identification
20. Comparing different approaches to model error modelling in robust identification
21. Model error concepts in identification for control
22. Design and analysis of computer experiments
23. Design of broadband excitation signals
24. Identification with generalized orthonormal basis functions. Statistical analysis and error bounds
25. System identification using Laguerre models