Estimation of model quality
From MaRDI portal
Publication:1911273
DOI10.1016/0005-1098(95)00108-7zbMath0846.93021OpenAlexW2006365485MaRDI QIDQ1911273
Brett Ninness, Graham C. Goodwin
Publication date: 5 June 1996
Published in: Automatica (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/0005-1098(95)00108-7
identificationleast-squaresmodel structure selectionstochastic modellingestimation in \(\ell_ 1\)estimation in \(H_ \infty\)worst-case estimation
System identification (93B30) (H^infty)-control (93B36) Research exposition (monographs, survey articles) pertaining to systems and control theory (93-02) Identification in stochastic control theory (93E12)
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Cites Work
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- Topics in stochastic systems: modelling, estimation and adaptive control
- On covariance function tests used in system identification
- Parameter identification in the presence of non-parametric dynamic uncertainty
- Estimation theory for nonlinear models and set membership uncertainty
- A frequency-domain estimator for use in adaptive control systems
- Dynamic system identification. Experiment design and data analysis
- Identification and application of bounded-parameter models
- Maximum likelihood estimators and worst case optimal algorithms for system identification
- On the value of information in system identification-bounded noise case
- Optimal estimation theory for dynamic systems with set membership uncertainty: An overview
- Robust identification in \(H_{\infty{}}\)
- Robust convergence of two-stage nonlinear algorithms for identification in \({\mathcal H}_ \infty\)
- A class of algorithms for identification in \(\mathcal H_{\infty}\)
- Worst-case identification in Banach spaces
- Worst case system identification in \(\ell{}_ 1\): Optimal algorithms and error bounds
- Proof of the conjectures of Bernstein and Erdős concerning the optimal nodes for polynomial interpolation
- The modeling of uncertainty in control systems. Proceedings of the 1992 Santa Barbara Workshop held at the University of California, Santa Barbara, CA, USA, June 18-20, 1992
- The least squares algorithm, parametric system identification and bounded noise
- Worst-case identification in \(\ell_ 2\): Linear and nonlinear algorithms
- Information-based complexity and nonparamteric worst-case system identification
- Controller design for plants with structured uncertainty
- The sample complexity of worst-case identification of FIR linear systems
- Time domain identification for robust control
- Properties of least squares estimates in set membership identification
- Worst-case control-relevant identification
- Identification in \({\mathcal H}_ \infty\) using Pick's interpolation
- Optimal input design for worst-case system identification in \(l_ 1/l_ 2/l_ \infty\)
- Laguerre series approximation of infinite dimensional systems
- A new approach to adaptive robust control
- Optimal asymptotic identification under bounded disturbances
- Problems and results on the theory of interpolation. II
- An extremal problem in the theory of interpolation
- Adaptive control via parameter set estimation
- A stochastic embedding approach for quantifying uncertainty in the estimation of restricted complexity models
- Exact recursive polyhedral description of the feasible parameter set for bounded-error models
- Optimal algorithms theory for robust estimation and prediction
- Asymptotic variance expressions for identified black-box transfer function models
- Identification of parameter bounds for ARMAX models from records with bounded noise
- Asymptotic properties of black-box identification of transfer functions
- Robust estimation and filtering in the presence of bounded noise
- Estimation theory and uncertainty intervals evaluation in presence of unknown but bounded errors: Linear families of models and estimators
- Robust identification and Galois sequences
- Robust identification and interpolation in H∞
- System identification using Laguerre models
- Adaptive quantification of model uncertainties by rational approximation
- Control oriented system identification: a worst-case/deterministic approach in H/sub infinity /
- Some basic information on information-based complexity theory
- Perspectives on information-based complexity
- Identification with nonparametric uncertainty
- Hard frequency-domain model error bounds from least-squares like identification techniques
- Quantifying the error in estimated transfer functions with application to model order selection
- Set-membership identification of systems with parametric and nonparametric uncertainty
- Model validation: a connection between robust control and identification
- Linear and nonlinear algorithms for identification in H/sub infinity / with error bounds
- Accurate identification for control: the necessity of an iterative scheme
- A comparison of classical stochastic estimation and deterministic robust estimation
- Worst-case input-output identification
- Robust identification of strongly stabilizable systems
- On the metric complexity of casual linear systems: ε -Entropy and ε -Dimension for continuous time
- Bounded-error tracking of time-varying parameters
- On the time complexity of worst-case system identification
- A time-domain approach to model validation
- Interpolation in Normed Spaces from the Values of Linear Functionals
- On the Polynomial and Rational Projections in the Complex Plane
- On the Erdös Conjecture Concerning Minimal Norm Interpolation on the Unit Circle
- A probabilistic approach to multivariable robust filtering and open-loop control
- Algorithms for identification in H∞with unequally spaced function measurements
- The asymptotic theory of linear time-series models