- Tytuł:
- Disturbance modeling and state estimation for offset-free predictive control with state-space process models
- Autorzy:
- Tatjewski, P.
- Powiązania:
- https://bibliotekanauki.pl/articles/330146.pdf
- Data publikacji:
- 2014
- Wydawca:
- Uniwersytet Zielonogórski. Oficyna Wydawnicza
- Tematy:
-
model predictive control
state space model
disturbance rejection
state observer
Kalman filter
sterowanie predykcyjne
model przestrzeni stanów
eliminacja zakłóceń
obserwator stanu
filtr Kalmana - Opis:
- 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.
- Źródło:
-
International Journal of Applied Mathematics and Computer Science; 2014, 24, 2; 313-323
1641-876X
2083-8492 - Pojawia się w:
- International Journal of Applied Mathematics and Computer Science
- Dostawca treści:
- Biblioteka Nauki