Offset-free state-space nonlinear predictive control for Wiener systems

Maciej Ławryńczuk , Piotr Tatjewski


This work is concerned with state space Multiple-Input Multiple-Output (MIMO) Wiener systems which consist of a linear dynamic block connected in series with a nonlinear steady-state (static) one. Model Predictive Control (MPC) algorithms with successive on-line model or trajectory linearisation for dynamic processes described by such Wiener systems are discussed. Advantages of the presented MPC algorithms are: (a) computational efficiency since quadratic optimisation problems are only solved on-line, nonlinear optimisation is not necessary, (b) very good quality of control, (c) offset-free control (no steady-state error in presence of disturbances) assured by a novel approach to disturbance modelling and state estimation, resulting in a simple design and a simple control structure. All features of the discussed algorithms are demonstrated and their performance is compared with that of the MPC algorithm with nonlinear optimisation as well as with the traditional offset-free state-space MPC approach. Previous article in issue
Author Maciej Ławryńczuk (FEIT / AK)
Maciej Ławryńczuk,,
- The Institute of Control and Computation Engineering
, Piotr Tatjewski (FEIT / AK)
Piotr Tatjewski,,
- The Institute of Control and Computation Engineering
Journal seriesInformation Sciences, ISSN 0020-0255, e-ISSN 1872-6291
Issue year2020
Publication size in sheets1.2
Keywords in EnglishProcess control Model predictive control State-space Wiener systems Offset-free control Optimisation
ASJC Classification1802 Information Systems and Management; 1702 Artificial Intelligence; 1706 Computer Science Applications; 1712 Software; 2207 Control and Systems Engineering; 2614 Theoretical Computer Science
Languageen angielski
LAwrynczuk Tatjewski IS 2020.pdf 1.82 MB
Score (nominal)200
Score sourcejournalList
ScoreMinisterial score = 200.0, 17-06-2020, ArticleFromJournal
Publication indicators WoS Citations = 0; Scopus Citations = 0; Scopus SNIP (Source Normalised Impact per Paper): 2018 = 2.636; WoS Impact Factor: 2018 = 5.524 (2) - 2018=5.305 (5)
Citation count*2 (2020-09-09)
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* presented citation count is obtained through Internet information analysis and it is close to the number calculated by the Publish or Perish system.
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