Application of minimum crest factor multisinusoidal signals for "plant-friendly" identification of nonlinear process systems

M. W. Braun, R. Ortiz-Mojica, Daniel Rivera

Research output: Contribution to journalArticle

40 Citations (Scopus)

Abstract

Guidelines for specifying the design parameters of minimum crest factor multisine signals generated per the approach of Guillaume et al. are presented. These guidelines are evaluated in the identification and control of nonlinear process systems. The minimum crest factor multisine signals offer some distinct advantages over both Schroeder phased multisine signals and multi-level Pseudo-Random Sequences (multi-level PRS) with respect to "plant-friendliness" considerations. These signals can be used to reduce the effects of nonlinearity in obtaining an Empirical Transfer Function Estimate (ETFE). As an example, the ETFE of a Rapid Thermal Processing (RTP) reactor simulation is presented. The effectiveness of the minimum crest factor multisine signals is also discussed and illustrated in the identification and control of a simulated continuous stirred tank reactor using "Model-on-Demand" estimation and Model Predictive Control. Since the performance of the "Model-on-Demand" estimator is highly dependent upon the quality of the identification data, the CSTR case study provides a compelling example of the usefulness of the proposed design procedure.

Original languageEnglish (US)
Pages (from-to)301-313
Number of pages13
JournalControl Engineering Practice
Volume10
Issue number3
DOIs
StatePublished - 2002

Fingerprint

Nonlinear Process
Transfer functions
Rapid thermal processing
Model predictive control
Transfer Function
Reactor
Pseudorandom Sequence
Model Predictive Control
Parameter Design
Estimate
Nonlinearity
Distinct
Estimator
Dependent
Model
Simulation
Demand

Keywords

  • Input signal design
  • Local modeling
  • Multisine signals
  • Nonlinear model identification
  • Nonlinear model predictive control

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Industrial and Manufacturing Engineering

Cite this

Application of minimum crest factor multisinusoidal signals for "plant-friendly" identification of nonlinear process systems. / Braun, M. W.; Ortiz-Mojica, R.; Rivera, Daniel.

In: Control Engineering Practice, Vol. 10, No. 3, 2002, p. 301-313.

Research output: Contribution to journalArticle

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