Non-linear predictive generalised minimum variance state-dependent control

Grimble, Michael and Majecki, Pawel (2015) Non-linear predictive generalised minimum variance state-dependent control. IET Control Theory and Applications. pp. 2438-2450. ISSN 1751-8644 (https://doi.org/10.1049/iet-cta.2015.0356)

[thumbnail of Grimble-Majecki-IET-CTA-2015-Non-linear-predictive-generalised-minimum-variance-state]
Preview
Text. Filename: Grimble_Majecki_IET_CTA_2015_Non_linear_predictive_generalised_minimum_variance_state.pdf
Accepted Author Manuscript

Download (552kB)| Preview

Abstract

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.