A novel approach to estimation of structured uncertainties is proposed for a class of nonlinear systems based on algebraic geometry tools. The notion of Polynomial Partition of Unity (PPU) is introduced and it constitutes a key feature of the proposed estimation technique, whose main advantage is the potentiality of being executed offline. Provided that the system dynamics satisfy some PPU and gradient properties, and collecting a sufficient number of measurements at different time steps, the values of unknown parameters are proved to be included in the finite set of common solutions to a family of polynomial equations. An optimization method based on multiple-models is then proposed to further refine the estimation. The case-study of sensorless permanent magnet synchronous motors is presented as a support to theoretical developments.

Uncertain parameter estimation for a class of nonlinear systems using a polynomial representation of outputs

CRISTOFARO, ANDREA
2016-01-01

Abstract

A novel approach to estimation of structured uncertainties is proposed for a class of nonlinear systems based on algebraic geometry tools. The notion of Polynomial Partition of Unity (PPU) is introduced and it constitutes a key feature of the proposed estimation technique, whose main advantage is the potentiality of being executed offline. Provided that the system dynamics satisfy some PPU and gradient properties, and collecting a sufficient number of measurements at different time steps, the values of unknown parameters are proved to be included in the finite set of common solutions to a family of polynomial equations. An optimization method based on multiple-models is then proposed to further refine the estimation. The case-study of sensorless permanent magnet synchronous motors is presented as a support to theoretical developments.
2016
262
File in questo prodotto:
File Dimensione Formato  
Journal of the Franklin Institute, 2016 vol. 353 pp. 4652–4666.pdf

solo gestori di archivio

Tipologia: Versione Editoriale
Licenza: NON PUBBLICO - Accesso privato/ristretto
Dimensione 365.05 kB
Formato Adobe PDF
365.05 kB Adobe PDF   Visualizza/Apri   Richiedi una copia

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11581/395335
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 3
  • ???jsp.display-item.citation.isi??? 2
social impact