A data-centric system identification approach to input signal design for Hammerstein systems

Sunil Deshpande, Daniel Rivera

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

This paper examines the design of input signals for identification of Hammerstein systems in a data-centric framework by addressing the optimal distribution of regressors. Data-centric estimation methods such as Model-on-Demand (MoD) generate local function approximations from a database of regressors at the current operating point. The data-centric input signal design formulation aims to develop sufficient support in the regressor space for the MoD estimator, while addressing time-domain constraints on the input and output signals. A numerical example is shown to highlight the benefit of proposed design over classical Pseudo Random Binary Sequence (PRBS), Multi Level Pseudo Random Sequence (MLPRS) and uniform random input designs.

Original languageEnglish (US)
Title of host publicationProceedings of the IEEE Conference on Decision and Control
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages5192-5197
Number of pages6
ISBN (Print)9781467357173
DOIs
StatePublished - 2013
Event52nd IEEE Conference on Decision and Control, CDC 2013 - Florence, Italy
Duration: Dec 10 2013Dec 13 2013

Other

Other52nd IEEE Conference on Decision and Control, CDC 2013
CountryItaly
CityFlorence
Period12/10/1312/13/13

Fingerprint

System Identification
Identification (control systems)
Pseudorandom Sequence
Binary sequences
Local Approximation
Binary Sequences
Function Approximation
Time Domain
Sufficient
Estimator
Numerical Examples
Design
Formulation
Output
Model
Demand

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Modeling and Simulation
  • Control and Optimization

Cite this

Deshpande, S., & Rivera, D. (2013). A data-centric system identification approach to input signal design for Hammerstein systems. In Proceedings of the IEEE Conference on Decision and Control (pp. 5192-5197). [6760705] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CDC.2013.6760705

A data-centric system identification approach to input signal design for Hammerstein systems. / Deshpande, Sunil; Rivera, Daniel.

Proceedings of the IEEE Conference on Decision and Control. Institute of Electrical and Electronics Engineers Inc., 2013. p. 5192-5197 6760705.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Deshpande, S & Rivera, D 2013, A data-centric system identification approach to input signal design for Hammerstein systems. in Proceedings of the IEEE Conference on Decision and Control., 6760705, Institute of Electrical and Electronics Engineers Inc., pp. 5192-5197, 52nd IEEE Conference on Decision and Control, CDC 2013, Florence, Italy, 12/10/13. https://doi.org/10.1109/CDC.2013.6760705
Deshpande S, Rivera D. A data-centric system identification approach to input signal design for Hammerstein systems. In Proceedings of the IEEE Conference on Decision and Control. Institute of Electrical and Electronics Engineers Inc. 2013. p. 5192-5197. 6760705 https://doi.org/10.1109/CDC.2013.6760705
Deshpande, Sunil ; Rivera, Daniel. / A data-centric system identification approach to input signal design for Hammerstein systems. Proceedings of the IEEE Conference on Decision and Control. Institute of Electrical and Electronics Engineers Inc., 2013. pp. 5192-5197
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