Non-linear predictive GMV control

M.J. Grimble, P. Majeckie

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

3 Citations (Scopus)


A nonlinear predictive generalized minimum variance (NPGMV) control algorithm is introduced for the control of nonlinear multivariable systems. The plant model is represented by a series combination of a nonlinear operator, which is assumed finite-gain stable, and a linear state-space model, which can include time delays and unstable modes. The main contribution is to incorporate predictive action into the recently introduced Nonlinear GMV controller by defining a multi-step cost index and using a minimum-variance form of the usual GPC cost function. The solution is very different to traditional nonlinear model predictive control, providing a solution which is similar to fixed model based controllers. This does not provide the same constrained optimization features but it does give a controller which is very simple to implement.
Original languageEnglish
Title of host publicationAmerican Control Conference, 2008
Number of pages5
ISBN (Print)9781424420780
Publication statusPublished - Jun 2008
Event2008 American Control Conference - Seattle, United States
Duration: 11 Jun 200813 Jun 2008


Conference2008 American Control Conference
Country/TerritoryUnited States


  • delays
  • multivariable control systems
  • nonlinear control systems
  • optimisation
  • predictive control


Dive into the research topics of 'Non-linear predictive GMV control'. Together they form a unique fingerprint.

Cite this