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2014 | 24 | 2 | 313-323
Tytuł artykułu

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

Autorzy
Treść / Zawartość
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
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 2×2 example process problem.
Rocznik
Tom
24
Numer
2
Strony
313-323
Opis fizyczny
Daty
wydano
2014
otrzymano
2013-09-27
poprawiono
2014-01-08
Twórcy
  • Institute of Control and Computation Engineering, Warsaw University of Technology, ul. Nowowiejska 15/19, 00-665 Warsaw, Poland
Bibliografia
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  • Tatjewski, P. (2011). Disturbance modeling and state estimation for predictive control with different state-space process models, Preprints of the 18th IFAC World Congress, Milan, Italy, pp. 5326-5331.
  • Tatjewski, P. (2012). Modeling deterministic disturbances and state filtering in model predictive control with state-space models, in M. Busłowicz and K. Malinowski (Eds.), Advances in Control Theory and Automation, OWPB, Białystok, pp. 263-274.
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Typ dokumentu
Bibliografia
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