NDLI: Embedded Model Control urges disturbance modelling and rejection

Content Provider	IEEE Xplore Digital Library
Author	Canuto, E. Acuna-Bravo, W. Molano-Jimenez, A. Ospina, J. Perez-Montenegro, C.
Copyright Year	2011
Description	Author affiliation: Politecnico di Torino, Dipartimento di Automatica e Informatica, Corso Duca degli Abruzzi 24, 10129, Italy (Canuto, E.; Acuna-Bravo, W.; Molano-Jimenez, A.; Ospina, J.; Perez-Montenegro, C.)
Abstract	Robust control design is devoted to guarantee closed-loop stability of a model-based control law in presence of parametric uncertainties. The control law is usually a static feedback law which is derived from a model. Under this view stability can only be guarantee by introducing some ignorance coefficients and restricting the feedback control effort with respect to the model-based design. Embedded Model Control shows that under certain conditions, the model-based control law must and can be kept intact under uncertainty, if the controllable dynamics is complemented by a suitable disturbance dynamics capable of real-time encoding the different uncertainties affecting the ‘embedded model’, i.e. the model which is both the design source and the core of the control unit. To be real-time updated the disturbance state is driven by an unpredictable input vector, called noise, which can be only estimated from the model error. The uncertainty-based design concerns the noise estimator, as the model error conveys into the embedded model uncertainty components which are command-dependent and thus prone to destabilize the plant. Separation of the components in the low and high frequency domain by the noise estimator itself allows to recover and guarantee stability. A simple example will help to understand the key assets of the methodology.
Starting Page	6267
Ending Page	6273
File Size	221222
Page Count	7
File Format	PDF
ISBN	9781457706776
ISSN	21612927
e-ISBN	9789881725592
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-07-22
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Chinese Assoc of Automati
Subject Keyword	Rejection Adaptation models Uncertainty Noise Model error Noise estimator Disturbance Stability analysis Mathematical model Kalman filters Equations Embedded Model Control
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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