Robust nonlinear generalised minimum variance control and fault monitoring

Sung-ho Hur, Michael J. Grimble

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)
124 Downloads (Pure)


The first part of this paper extends the Nonlinear Generalised Minimum Variance (NGMV) controller to improve the robustness of its control or set-point tracking performance. This is achieved by replacing the Kalman filter included in the original NGMV controller with an observer to minimise the effect of uncertainty, which includes unknown disturbance, modelling error, and faults. The observer design also allows the NGMV controller to be utilised in fault monitoring. More specifically, the second part of this paper obtains the observer gain by solving a multi-objective optimisation problem through the application of a genetic algorithm so that the residual signal becomes sensitive to faults and insensitive to any other uncertainty. The control and fault monitoring performance of the extended NGMV controllers is tested by application to a nonlinear tank model.
Original languageEnglish
Pages (from-to)547-556
Number of pages10
JournalInternational Journal of Control, Automation and Systems
Issue number3
Early online date28 Mar 2015
Publication statusPublished - Jun 2015


  • nonlinear generalised minimum variance
  • observer
  • robust control
  • fault monitoring


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