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Flatness‐based control for steam‐turbine power generation units using a disturbance observer
Author(s) -
Rigatos Gerasimos,
Zervos Nikolaos,
Siano Pierluigi,
Wira Patrice,
Abbaszadeh Masoud
Publication year - 2021
Publication title -
iet electric power applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.815
H-Index - 97
eISSN - 1751-8679
pISSN - 1751-8660
DOI - 10.1049/elp2.12077
Subject(s) - flatness (cosmology) , control theory (sociology) , steam turbine , control engineering , disturbance (geology) , turbine , engineering , computer science , control (management) , physics , mechanical engineering , geology , artificial intelligence , paleontology , cosmology , quantum mechanics
Steam‐turbine power plants still supply a significant part of the electric power consumed worldwide. The viability of steam turbine power units depends on their efficiency to a great extent and the control method applied to the them is of major importance for achieving their improved functioning. The authors propose flatness‐based control and non‐linear Kalman Filtering for power generation units comprising synchronous generators connected to steam turbines. It is shown that the dynamic model of this power system is a differentially flat one. This property signifies that all its state variables and its control inputs can be expressed as its differential functions of selected state variables, the latter standing for the flat outputs of the system. This allows for its transformation into a linear canonical form in which the design of a feedback controller and the solution of the state estimation problem becomes possible. Moreover, by introducing a Kalman Filter‐based disturbance observer it becomes possible to identify in real time the perturbation terms that affect the power system's model. Through the proposed flatness‐based controller, fast and accurate tracking of all reference setpoints is achieved by the state vector elements of the power unit. Moreover, through the proposed Kalman Filter‐based disturbances estimator, the control loop is given additional robustness against modelling errors and external perturbations.

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