Object structure

Creator:

Tatjewski, Piotr

Contributor:

Makowski, Ryszard - ed. ; Zarzycki, Jan - ed.

Title:

Disturbance modeling and state estimation for offset-free predictive control with state-space process models

Subtitle:

.

Group publication title:

AMCS, Volume 24 (2014)

Subject and Keywords:

model predictive control ; state-space models ; disturbance rejection ; state observer ; Kalman filters

Abstract:

Disturbance modeling and design of state estimators for offset-free Model Predictive Control (MPC) with linear state-space process models is considered in the paper for deterministic constant-type external and internal disturbances (modeling errors). The application and importance of constant state disturbance prediction in the state-space MPC controller design is presented. In the case with a measured state, this leads to the control structure without disturbance state observers. ; In the case with an unmeasured state, a new, simpler MPC controller-observer structure is proposed, with observation of a pure process state only. The structure is not only simpler, but also with less restrictive applicability conditions than the conventional approach with extended process-and-disturbances state estimation. Theoretical analysis of the proposed structure is provided. The design approach is also applied to the case with an augmented state-space model in complete velocity form. The results are illustrated on a 2 x 2 example process problem.

Publisher:

Zielona Góra: Uniwersytet Zielonogórski

Date:

2014

Resource Type:

artykuł

DOI:

10.2478/amcs-2014-0023

Pages:

313-323

Source:

AMCS, volume 24, number 2 (2014) ; click here to follow the link

Language:

eng

Rights:

Biblioteka Uniwersytetu Zielonogórskiego