Interval state estimation for linear time-varying (LTV) discrete-time systems subject to component faults and uncertainties

• Autorzy: Khan Awais , Xie Wei , Zhang Langwen , Ihsanullah

Identyfikatory

DOI

10.24425/acs.2019.129383

• Języki publikacji: EN

Abstrakty

EN

This paper deals with the design of an interval state estimator for linear time-varying (LTV) discrete-time systems subject to component faults and uncertainties. These component faults and uncertainties are assumed to be unknown but bounded without giving any other information, whose effect can be approximated using these bounds. In the first part of this work, an interval state estimator for such systems is designed to deal with these component faults and uncertainties. The result is then extended to find an interval state estimator for a noncooperative LTV discrete-time system subject to component faults and uncertainties by similarity transformation of coordinates. The proposed interval state estimator guaranteed bounds on the observed states that are consistent with the system states. The observer convergence is also ensured. The designed method is simple and easy to be implemented. Two numerical examples are given to show the effectiveness of the proposed method.

Słowa kluczowe

EN

component faults; interval state estimator; linear time-varying systems; noncooperative systems

• Wydawca: Polish Academy of Sciences, Committee of Automatic Control and Robotics
• Czasopismo: Archives of Control Sciences
• Rocznik: 2019
• Tom: Vol. 29, No. 2
• Strony: 289--305
• Opis fizyczny: Bibliogr. 31 poz., wykr., wzory

Twórcy

autor

Khan Awais

• College of Automation Science and Technology, South China University of Technology, Guangzhou 510641, People’s Republic of China

autor

Xie Wei

• College of Automation Science and Technology, South China University of Technology, Guangzhou 510641, People’s Republic of China
• Guangdong Provincial Key Laboratory of Technique and Equipment for Macromolecular Advanced Manufacturing, South China University of Technology, Guangzhou 510641, People’s Republic of China

autor

Zhang Langwen

• College of Automation Science and Technology, South China University of Technology, Guangzhou 510641, People’s Republic of China

autor

Ihsanullah

• College of Automation Science and Technology, South China University of Technology, Guangzhou 510641, People’s Republic of China

Bibliografia

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Uwagi

EN

1. This work was supported by YangFan Innovative and Entepreneurial Research Team Projectof Guangdong Province under the grant 2016YT03G125, National Nature Science Foundation of China under the grant 61803161, Natural Science Foundation of Guangdong Province under the grant 2017A030313385 & 2018A030310371, Science and Technology Planning Project of Guangdong Province under the grant 2017B090914001, 2017A040403064, 2017B090901040, 2017B030306017 & 2017A040405023, Innovative Research Team Project of Jiangmen under the grant 2017TD03 and the scholarship from China Scholarship Council (CSC) under the grant CSC No. 2016GXZ344.

PL

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).