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Design of Offset–Free Predictive Control with State–Space Models: Equivalences and New Results Cover

Design of Offset–Free Predictive Control with State–Space Models: Equivalences and New Results

By: Piotr Tatjewski  
Open Access
|Dec 2025

Abstract

Design of offset-free model predictive control (MPC) with a linear state-space process model is discussed in the paper, for deterministic constant or asymptotically constant external and internal (modeling errors) disturbances. The three existing, established methods assuring offset-free control are briefly compared and relations between them are recalled. The main result of the paper is a new, more flexible but still simple formula defining unmeasured disturbance estimates in the model-based prediction error method (abbreviated as MPE). The new formulation eliminates the only deficiency of this approach, i.e., being possibly highly sensitive to noise. Equivalence of the proposed technique with the augmented process-and-disturbance model method (AM for short) is proved, indicating how to define arbitrary choice of disturbance matrices in the equivalent formulation of the AM approach. With the new formulation, the MPE method seems to be a competitive, best design choice. Theoretical results are validated and illustrated by extensive simulation results of a MIMO control problem, with unmeasured disturbances from the mentioned class and also with noises added. The capability of the proposed method to tune sensitivity to noises of the MPC control system is shown.

DOI: https://doi.org/10.61822/amcs-2025-0039 | Journal eISSN: 2083-8492 | Journal ISSN: 1641-876X
Language: English
Page range: 551 - 561
Submitted on: Feb 6, 2025
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Accepted on: Apr 14, 2025
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Published on: Dec 15, 2025
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2025 Piotr Tatjewski, published by University of Zielona Góra
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.