Non-linear predictive generalised minimum variance state-dependent control

Michael Grimble, Pawel Majecki

Research output: Contribution to journalArticlepeer-review

8 Citations (Scopus)
68 Downloads (Pure)


A non-linear predictive generalised minimum variance control algorithm is introduced for the control of nonlinear discrete-time state-dependent multivariable systems. The process model includes two different types of subsystems to provide a variety of means of modelling the system and inferential control of certain outputs is available. A state dependent output model is driven from an unstructured non-linear input subsystem which can include explicit transport delays. A multi-step predictive control cost function is to be minimised involving weighted error, and either absolute or incremental control signal costing terms. Different patterns of a reduced number of future controls can be used to limit the computational demands.
Original languageEnglish
Pages (from-to)2438-2450
Number of pages13
JournalIET Control Theory and Applications
Publication statusPublished - 29 Oct 2015


  • delays
  • discrete time systems
  • multivariable control systems
  • signal costing


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