Model validation: a connection between robust control and identification
Roy S. Smith,John Doyle +1 more
TLDR
The model validation problem addressed is: given experimental data and a model with both additive noise and norm-bounded perturbations, is it possible that the model could produce the observed input-output data?Abstract:
The gap between the models used in control synthesis and those obtained from identification experiments is considered by investigating the connection between uncertain models and data. The model validation problem addressed is: given experimental data and a model with both additive noise and norm-bounded perturbations, is it possible that the model could produce the observed input-output data? This problem is studied for the standard H/sub infinity // mu framework models. A necessary condition for such a model to describe an experimental datum is obtained. For a large class of models in the robust control framework, this condition is computable as the solution of a quadratic optimization problem. >read more
Citations
More filters
Journal ArticleDOI
Bookshelf - [Book Review] - Innovations in Education and Practice
TL;DR: Three books are reviewed: Intuitive Probability and Random Processes Using Matlab by Steven Kay; Relay Feedback: Analysis, Identification and Control by Q. Wang et al.
Validityofthestandardcross-correlationtest formodelstructurevalidation
TL;DR: It is shown that for reliable results of the validation test a vector-valued test is required and that accurate noise modelling is indispensable for reliable model structure validation.
Proceedings ArticleDOI
Robust Model Validation. Part II. A Robust Semi-definite Optimization Based Solution.
Florin Dan Barband,Jan Mulder +1 more
TL;DR: In this paper, a lift-and-project based approach is proposed to find the maximal level of uncertainty for which a robust certificate exists for a property in a model with uncertainties.
Journal ArticleDOI
Identification and Validation/Update for Smallest Model Sets of Transfer Functions with Parametric Uncertainties
Validation via linear programming
T. K. Gustafsson,P. M. Makili +1 more
TL;DR: In this paper, a robust convergence result is given for a modified least sum of absolute deviations identifi- cation algorithm for bounded-input bounded-output (BIBO) stable linear discrete-time systems.
References
More filters
Analysis of feedback systems with structured uncertainties
TL;DR: In this article, a general approach for analysing linear systems with structured uncertainty based on a new generalised spectral theory for matrices is introduced, which naturally extend techniques based on singular values and eliminate their most serious difficulties.
Proceedings ArticleDOI
Structured uncertainty in control system design
TL;DR: This paper reviews control system analysis and synthesis techniques for robust performance with structured uncertainty in the form of multiple unstructured perturbations and parameter variations in the case where parameter variations are known to be real.
Journal ArticleDOI
Control oriented system identification: a worst-case/deterministic approach in H/sub infinity /
TL;DR: The authors formulate and solve two related control-oriented system identification problems for stable linear shift-invariant distributed parameter plants, each involving identification of a point sample of the plant frequency response from a noisy, finite, output time series obtained in response to an applied sinusoidal input.