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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Proceedings ArticleDOI
A minimum-norm model validation identification for robust control
TL;DR: A proven observer-based system identification algorithm in time domain is used to obtain a nominal model while the residual errors in the estimated outputs are used to generate bounds of structured uncertainties for each component in the frequency domain.
Journal ArticleDOI
On the Application of the Generalised Structured Singular Value to Robust FDI System Design
Jürgen Eich,Rainer Oehler +1 more
TL;DR: In this article, the generalised structured singular value has proven to be very useful for solving the model validation problem within the robust control framework, and the authors considered its application to the design of robust model-based fault diagnosis systems.
Journal ArticleDOI
Iterative design of structured uncertainty models and robust controllers based on closed-loop data
Gábor Rödönyi,Péter Gáspár +1 more
TL;DR: In this paper, a joint uncertainty modelling and robust control design method is presented for linear time-invariant (LTI) systems, where the system is given as a linear fractional transformation (LFT) with structured uncertainty blocks.
Proceedings ArticleDOI
Unfalsified adaptive spacecraft attitude control
TL;DR: In this article, the authors demonstrate how the unfalsified control method can be applied to the problem of antenna mapping control using a simplified spacecraft model and demonstrate that the large uncertainty in spacecraft dynamics falsifies the conventional PID controller design and selects a better one in the controller data bank based only on input/output signals from the plant.
Journal ArticleDOI
Model invalidation in /spl lscr//sub 1/ using frequency-domain data
Wenguo Liu,Jie Chen +1 more
TL;DR: In this article, the authors study the problem of invalidating uncertain models with an additive uncertainty and a measurement noise which fit to the given model structure and the uncertainty/noise description, as well as the experimental data used for invalidation.
References
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Proceedings ArticleDOI
Structured uncertainty in control system design
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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.