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Unknown Input Observer-based Actuator and Sensor Fault Estimation Technique for Uncertain Discrete Time Takagi-Sugeno Systems

  • Control Theory and Applications
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Abstract

This paper presents an Unknown Input robust Observer (UIO) capable of simultaneously estimate both sensor fault and system states. The system is assumed to be discrete-time Takagi-Sugeno (T-S) Fuzzy with uncertainties. An augmented system is obtained from the dynamic fault model and original system. Afterward, a UIO is designed for the augmented system aiming at decoupling process disturbances. Its design is obtained by using an H∞ optimization technique and developed to maintain the observer stable, reducing the non-decoupled process disturbances effect. The proposed method is validated by two numerical examples as it is compared to a regular UIO technique and the extended Kalman filter. Results show the proposed technique presents better performance when the dynamic system is not purely nonlinear even if the same tuning parameters are chosen. Although other techniques are not able to ensure the error limitation, the proposed one is capable of it even in nonlinear systems.

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Authors and Affiliations

  1. Laboratory of Automation in Oil (LAUT) of Automation and Department of Computer Engineering and Automation (DCA), Federal University of Rio Grande do Norte (UFRN), Natal, RN, CEP 59072-970, Brazil

    Emanoel R. Q. Chaves Jr. & André L. Maitelli

  2. Potiguar University (UnP) and Graduate Program in Neuroengineering, Edmond and Lily Safra International Institute of Neuroscience, Santos Dumont Institute, Macaíba, RN, CEP 59280-000, Brazil

    André F. O. de A. Dantas

Authors
  1. Emanoel R. Q. Chaves Jr.
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  2. André F. O. de A. Dantas
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  3. André L. Maitelli
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Corresponding author

Correspondence to Emanoel R. Q. Chaves Jr..

Additional information

This work is supported by the UFRN (Federal University of Rio Grande do Norte), LAUT (Laboratory of Automation in Oil) and FUNPEC (Foundation for Research and Culture of Rio Grande do Norte).

Emanoel R. Q. Chaves Jr. received his B.S., M.Sc., and Ph.D. degrees in electrical engineering from Federal University of Rio Grande do Norte, in 2012, 2015, and 2019, respectively. Currently, he is researcher of Laboratory of Automation in Oil. His research interests include nonlinear control, robust control, and fault tolerant control.

André F. O. de A. Dantas received his Ph.D. degree in electrical and computer engineering from Federal University of Rio Grande do Norte. Currently, he is part of the Graduate Program in Process Engineering at the Potiguar University and the Graduate Program in Neuroengineering at Edmond and Lily Safra International Institute of Neuroscience/Santos Dumont Institute. His research interests include control, and system identification.

André L. Maitelli received his Ph.D. degree in electrical engineering and computing from Aeronautics Institute of Technology, São José dos Campos, Brazil. Currently, he is a full professor of Computer Engineering and Automation Department of the Federal University of Rio Grande do Norte and coordinator of Laboratory of Automation in Oil. His research interests include automatic control, neural networks, and predictive control.

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Chaves, E.R.Q., de A. Dantas, A.F.O. & Maitelli, A.L. Unknown Input Observer-based Actuator and Sensor Fault Estimation Technique for Uncertain Discrete Time Takagi-Sugeno Systems. Int. J. Control Autom. Syst. 19, 2444–2454 (2021). https://doi.org/10.1007/s12555-020-0170-x

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  • DOI: https://doi.org/10.1007/s12555-020-0170-x

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