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
Robust Active Vibration Isolation: A Multivariable Data-Driven Approach
TL;DR: In this paper, a framework for high performance robust vibration isolation by explicitly addressing multivariable flexible dynamical behavior is proposed, and a new data-driven uncertainty modeling procedure is used that results in a non-conservative model error bound.
Proceedings ArticleDOI
Uncertainty Modeling and Robust Control of LTI Systems Based on Integral Quadratic Constraints
TL;DR: In this paper, a joint method for nominal model error modeling and robust control for linear time-invariant (LTI) systems is presented based on experimental data, where the goal is to design a controller that attain robust quadratic performance and stability of the closed loop, and simultaneously construct an uncertainty model that is not invalidated by measurement data.
Journal ArticleDOI
Controllers for amplitude limited model error models
TL;DR: Systems where information about model accuracy is contained in a model error model are considered, and the resulting implications for controller design are investigated in both the continuous and the discrete time case.
Set-membership Estimation, Analysis, and Experimental Design for Biological Systems
TL;DR: V Deutsche Kurzfassung VII as discussed by the authors has published a survey of the state-of-the-art research work in the area of data-sharing and data sharing.
Proceedings ArticleDOI
Integrated uncertainty model identification and robust control synthesis for linear time-invariant systems
Gábor Rödönyi,József Bokor +1 more
TL;DR: Given a nominal model, an integrated uncertainty model identification and mu-synthesis algorithm is presented for linear time-invariant (LTI) systems and integrates nominal model invalidation, uncertainty model construction and control synthesis to achieve robust performance.
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.