Systematic techniques for determining modelling requirements for SISO and MIMO feedback control

Daniel Rivera, Sujit V. Gaikwad

Research output: Contribution to journalArticlepeer-review

25 Scopus citations


This paper presents a fundamental methodology for assessing modelling requirements of SISO and MIMO linear control problems. The main result is the formulation of a control-relevant parameter estimation problem (CRPEP), which suitably captures the interplay that occurs between controller sophistication, speed and shape of the closed-loop response, and set-point/disturbance directions affecting the closed-loop system. The CRPEP is used to explain the apparent dilemma between emphasis on low-frequency, steady-state behaviour versus high-frequency, initial time behaviour in modelling for SISO feedback control. For multivariable systems, solutions to the CRPEP are presented using prefiltered estimation of MIMO ARX models (model reduction case) and a state-space frequency-weighted estimation method (system identification case). The superior performance of reduced order and model predictive controllers obtained from control-relevant models is demonstrated on a subset of the Shell heavy oil fractionator problem.

Original languageEnglish (US)
Pages (from-to)213-224
Number of pages12
JournalJournal of Process Control
Issue number4
StatePublished - Aug 1995


  • miltivariable control systems
  • model reduction
  • modelling
  • system identification

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Modeling and Simulation
  • Computer Science Applications
  • Industrial and Manufacturing Engineering


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