Piecewise affine direct virtual sensors with reduced complexity

Matteo Rubagotti, Tomaso Poggi, Alberto Bemporad, Marco Storace

Research output: Contribution to journalConference article

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 languageEnglish
Article number6426755
Pages (from-to)656-661
Number of pages6
JournalProceedings of the IEEE Conference on Decision and Control
DOIs
Publication statusPublished - Dec 1 2012
Event51st IEEE Conference on Decision and Control, CDC 2012 - Maui, HI, United States
Duration: Dec 10 2012Dec 13 2012

Fingerprint

Sensor
Nonlinear dynamical systems
Curse of Dimensionality
Output
Sensors
Dynamical Model
Low Complexity
Optimality
Nonlinear Systems
Higher Order
Estimator
Unknown
Generalise
Model
Design

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Modelling and Simulation
  • Control and Optimization

Cite this

Piecewise affine direct virtual sensors with reduced complexity. / Rubagotti, Matteo; Poggi, Tomaso; Bemporad, Alberto; Storace, Marco.

In: Proceedings of the IEEE Conference on Decision and Control, 01.12.2012, p. 656-661.

Research output: Contribution to journalConference article

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