Creator:
Contributor:
Makowski, Ryszard - ed. ; Zarzycki, Jan - ed.
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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
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DOI:
Pages:
Source:
AMCS, volume 24, number 2 (2014) ; click here to follow the link