Piecewise affine direct virtual sensors with reduced complexity

Matteo Rubagotti; Tomaso Poggi; Alberto Bemporad; Marco Storace

doi:10.1109/CDC.2012.6426755

Piecewise affine direct virtual sensors with reduced complexity

Matteo Rubagotti, Tomaso Poggi, Alberto Bemporad, Marco Storace

Nazarbayev University

Research output: Contribution to journal › Conference article › peer-review

3 Citations (Scopus)

Abstract

In this paper, a piecewise-affine direct virtual sensor is proposed for the estimation of unmeasured outputs of nonlinear systems whose dynamical model is unknown. In order to overcome the lack of a model, the virtual sensor is designed directly from measured inputs and outputs. The proposed approach generalizes a previous contribution, allowing one to design lower-complexity estimators. Indeed, the reduced-complexity approach strongly reduces the effect of the so-called 'curse of dimensionality', and can be applied to relatively high-order systems, while enjoying all the convergence and optimality properties of the original approach.

Original language	English
Article number	6426755
Pages (from-to)	656-661
Number of pages	6
Journal	Proceedings of the IEEE Conference on Decision and Control
DOIs	https://doi.org/10.1109/CDC.2012.6426755
Publication status	Published - Dec 1 2012
Event	51st IEEE Conference on Decision and Control, CDC 2012 - Maui, HI, United States Duration: Dec 10 2012 → Dec 13 2012

ASJC Scopus subject areas

Control and Systems Engineering
Modelling and Simulation
Control and Optimization

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10.1109/CDC.2012.6426755

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abstract = "In this paper, a piecewise-affine direct virtual sensor is proposed for the estimation of unmeasured outputs of nonlinear systems whose dynamical model is unknown. In order to overcome the lack of a model, the virtual sensor is designed directly from measured inputs and outputs. The proposed approach generalizes a previous contribution, allowing one to design lower-complexity estimators. Indeed, the reduced-complexity approach strongly reduces the effect of the so-called 'curse of dimensionality', and can be applied to relatively high-order systems, while enjoying all the convergence and optimality properties of the original approach.",

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AU - Rubagotti, Matteo

AU - Poggi, Tomaso

AU - Bemporad, Alberto

AU - Storace, Marco

PY - 2012/12/1

Y1 - 2012/12/1

N2 - In this paper, a piecewise-affine direct virtual sensor is proposed for the estimation of unmeasured outputs of nonlinear systems whose dynamical model is unknown. In order to overcome the lack of a model, the virtual sensor is designed directly from measured inputs and outputs. The proposed approach generalizes a previous contribution, allowing one to design lower-complexity estimators. Indeed, the reduced-complexity approach strongly reduces the effect of the so-called 'curse of dimensionality', and can be applied to relatively high-order systems, while enjoying all the convergence and optimality properties of the original approach.

AB - In this paper, a piecewise-affine direct virtual sensor is proposed for the estimation of unmeasured outputs of nonlinear systems whose dynamical model is unknown. In order to overcome the lack of a model, the virtual sensor is designed directly from measured inputs and outputs. The proposed approach generalizes a previous contribution, allowing one to design lower-complexity estimators. Indeed, the reduced-complexity approach strongly reduces the effect of the so-called 'curse of dimensionality', and can be applied to relatively high-order systems, while enjoying all the convergence and optimality properties of the original approach.

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Piecewise affine direct virtual sensors with reduced complexity

Abstract

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