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
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Book ChapterDOI
Passive Diagnosis of Hidden-Mode Switched Affine Models with Detection Guarantees via Model Invalidation
TL;DR: It is shown that model invalidation based fault detection and isolation can be reduced to the feasibility of a mixed-integer linear programming (MILP) problem, which can be solved efficiently by leveraging state-of-the-art MILP solvers.
Journal ArticleDOI
Consistency Analysis for Massively Inconsistent Datasets in Bound-to-Bound Data Collaboration
TL;DR: In this article, the authors introduce a constraint relaxation-based approach, entitled the vector consistency measure, for investigating datasets with numerous sources of inconsistency, i.e., identifying which models and observations are problematic, is essential before a dataset can be used for prediction.
Journal ArticleDOI
Multivariable identification and controller design of an integrated flight control system
TL;DR: In this paper, Liu et al. investigated the multivariable identification and controller design for the longitudinal channel of a Boeing 747 transport, where the transfer function matrix of the system is identified using the prediction error (PE) identification method with multi-ivariable ARX model.
Proceedings ArticleDOI
Robust tuning of PID controllers via uncertainty model identification
TL;DR: In this article, a tuning method for a controller of given structure is proposed, with particular emphasis on the PID form, which consists in the processing of experimental results and :'a priori' information on the plant to be controlled.
Journal ArticleDOI
Convex necessary and sufficient conditions for frequency domain model (in)validation under SLTV structured uncertainty
M.C. Mazzaro,Mario Sznaier +1 more
TL;DR: If one considers arbitrarily slowly time varying uncertainty and noise in L/sub 2/, then tractable, convex necessary and sufficient conditions for (in)validation can be obtained.
References
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Proceedings ArticleDOI
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