An enhanced identification test monitoring procedure for MIMO systems relying on uncertainty estimates

César A. Martín, Daniel Rivera, Eric B. Hekler

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

2 Scopus citations

Abstract

An important practical consideration in system identification is the judicious use of information for input signal design. Typically, only limited process knowledge is available a priori; hence the input design parameters are not always optimally selected. The quality of the data substantially improves if input design parameters can be refined during experimental execution. The purpose of this paper is to present an enhanced identification test monitoring procedure for multivariable systems that incorporates these ideas to achieve experiments with the shortest possible duration and that are adequately informative for identification purposes. This is enabled by 'on-the-go' manipulation of amplitude, duration, and/or frequency content of the input signals. The decision to continue, modify, or halt the experiment is achieved by a stopping criterion based on a robust control metric that is developed in the paper. These computations are performed using an orthogonal-in-frequency spectral input design, and relying on a computational method that estimates transfer functions (and associated uncertainties) taking into account the system noise and transient behavior. Results are evaluated through a simulation study using a chemical process system under diverse realistic noise structures.

Original languageEnglish (US)
Title of host publication2016 IEEE 55th Conference on Decision and Control, CDC 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2091-2096
Number of pages6
ISBN (Electronic)9781509018376
DOIs
StatePublished - Dec 27 2016
Event55th IEEE Conference on Decision and Control, CDC 2016 - Las Vegas, United States
Duration: Dec 12 2016Dec 14 2016

Other

Other55th IEEE Conference on Decision and Control, CDC 2016
CountryUnited States
CityLas Vegas
Period12/12/1612/14/16

ASJC Scopus subject areas

  • Artificial Intelligence
  • Decision Sciences (miscellaneous)
  • Control and Optimization

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    Martín, C. A., Rivera, D., & Hekler, E. B. (2016). An enhanced identification test monitoring procedure for MIMO systems relying on uncertainty estimates. In 2016 IEEE 55th Conference on Decision and Control, CDC 2016 (pp. 2091-2096). [7798572] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CDC.2016.7798572