Fault-Tolerant Tracking Control for Takagi–Sugeno Fuzzy Systems Under Actuator and Sensor Faults

Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1196)


The paper deals with the design of an active fault-tolerant control scheme, which is based on the actuator and sensor fault estimator. Thus, the paper starts with the development of such a fault estimation scheme capable of estimating these faults simultaneously. It is assumed that the estimator should have a desired \(H_\infty \) performance. Subsequently, a new fault-tolerant control law is proposed, which is based on a parallel digital twin of the system. Thus, the goal is to control the system in such a way as to follow the states of the references digital twin irrespective of the faults. Finally, the effectiveness of the proposed approach is verified with the laboratory three-tank system. In particular, the performance of the system is tested against a set of simultaneous actuator and sensor faults, respectively.


Fault detection and diagnosis Robust fault estimation Takagi-Sugeno fuzzy system Fault-tolerant tracking control 



The work was supported by the National Science Centre, Poland under Grant: UMO-2017/27/B/ST7/00620.


  1. 1.
    Ahmad, M., Ali, A., Choudhry, M.A.: Fixed-structure \({H}_\infty \) controller design for two-rotor aerodynamical system (tras). Arabian Journal for Science and Engineering 41(9), 3619–3630 (2016)CrossRefGoogle Scholar
  2. 2.
    Aouaouda, S., Chadli, M., Righi, I.: Active ftc approach design for ts fuzzy systems under actuator saturation. In: 2019 6th International Conference on Control, Decision and Information Technologies (CoDIT), pp. 483–488. IEEE (2019)Google Scholar
  3. 3.
    Blanke, M., Kinnaert, M., Lunze, J., Staroswiecki, M.: Diagnosis andFault-Tolerant Control.Springer-Verlag, Berlin, Heidelberg, New York (2003)Google Scholar
  4. 4.
    Blanke, M., Schröder, J., Kinnaert, M., Lunze, J., Staroswiecki, M.:Diagnosis and Fault-Tolerant Control.Springer (2006)Google Scholar
  5. 5.
    Ding, B.: Dynamic output feedback predictive control for nonlinear systems represented by a Takagi-Sugeno model. Fuzzy Systems, IEEE Transactions on 19(5), 831–843 (2011)CrossRefGoogle Scholar
  6. 6.
    Edwards, C., Lombaerts, T., Smaili, H.: Fault Tolerant Flight Control: A Benchmark Challenge. Lecture Notes in Control and Information Sciences. Springer (2010)Google Scholar
  7. 7.
    Kommuri, S.K., Defoort, M., Karimi, H.R., Veluvolu, K.C.: A robust observer-based sensor fault-tolerant control for pmsm in electric vehicles. IEEE Transactions on Industrial Electronics 63(12), 7671–7681 (2016)CrossRefGoogle Scholar
  8. 8.
    Lan, J., Patton, R.J.: A decoupling approach to integrated fault-tolerant control for linear systems with unmatched non-differentiable faults. Automatica 89, 290–299 (2018)MathSciNetCrossRefGoogle Scholar
  9. 9.
    Li, Y., Tong, S.: Adaptive neural networks decentralized ftc design for nonstrict-feedback nonlinear interconnected large-scale systems against actuator faults. IEEE transactions on neural networks and learning systems 28(11), 2541–2554 (2016)MathSciNetCrossRefGoogle Scholar
  10. 10.
    López-Estrada, F.R., Ponsart, J.C., Astorga-Zaragoza, C.M., Camas-Anzueto, J.L., Theilliol, D.: Robust sensor fault estimation for descriptor-lpv systems with unmeasurable gain scheduling functions: Application to an anaerobic bioreactor. International Journal of Applied Mathematics and Computer Science 25(2), 233–244 (2015)MathSciNetCrossRefGoogle Scholar
  11. 11.
    Maalej, S., Kruszewski, A., Belkoura, L.: Stabilization of takagi-sugeno models with non-measured premises: Input-to-state stability approach. Fuzzy Sets and Systems 329, 108–126 (2017)MathSciNetCrossRefGoogle Scholar
  12. 12.
    Márquez, R., Guerra, T.M., Bernal, M., Kruszewski, A.: Asymptotically necessary and sufficient conditions for takagi-sugeno models using generalized non-quadratic parameter-dependent controller design. Fuzzy Sets and Systems 306, 48–62 (2017)MathSciNetCrossRefGoogle Scholar
  13. 13.
    de Oca, S.M., Rotondo, D., Nejjari, F., Puig, V.: Fault estimation and virtual sensor ftc approach for lpv systems. In: 2011 50th IEEE Conference on Decision and Control and European Control Conference, pp. 2251–2256. IEEE (2011)Google Scholar
  14. 14.
    Pazera, M., Buciakowski, M., Witczak, M.: Robust multiple sensor fault-tolerant control for dynamic non-linear systems: Application to the aerodynamical twin-rotor system. International Journal of Applied Mathematics and Computer Science 28(2), 297–308 (2018)MathSciNetCrossRefGoogle Scholar
  15. 15.
    Pazera, M., Witczak, M.: Towards robust simultaneous actuator and sensor fault estimation for a class of nonlinear systems: Design and comparison. IEEE Access 7, 97143–97158 (2019)CrossRefGoogle Scholar
  16. 16.
    Rotondo, D., Witczak, M., Puig, V., Nejjari, F., Pazera, M.: Robust unknown input observer for state and fault estimation in discrete-time takagi-sugeno systems. International Journal of Systems Science Vol. 47(iss. 14), 1–16 (2016)Google Scholar
  17. 17.
    Sun, K., Sui, S., Tong, S.: Optimal adaptive fuzzy ftc design for strict-feedback nonlinear uncertain systems with actuator faults. Fuzzy Sets and Systems 316, 20–34 (2017)MathSciNetCrossRefGoogle Scholar
  18. 18.
    Tabbache, B., Rizoug, N., Benbouzid, M.E.H., Kheloui, A.: A control reconfiguration strategy for post-sensor ftc in induction motor-based evs. IEEE transactions on vehicular technology 62(3), 965–971 (2012)CrossRefGoogle Scholar
  19. 19.
    Takagi, T., Sugeno, M.: Fuzzy identification of systems and its application to modeling and control. IEEE Transactions on Systems, Man and Cybernetics 15(1), 116–132 (1985)CrossRefGoogle Scholar
  20. 20.
    Wang, T., Qiu, J., Gao, H.: Adaptive neural control of stochastic nonlinear time-delay systems with multiple constraints. IEEE Transactions on Systems, Man, and Cybernetics: Systems 47(8), 1875–1883 (2016)CrossRefGoogle Scholar
  21. 21.
    Witczak, M.: Modelling and Estimation Strategies for Fault Diagnosis of Non-linear Systems. Springer-Verlag, Berlin (2007)zbMATHGoogle Scholar
  22. 22.
    Witczak, M.: Fault Diagnosis and Fault-Tolerant Control Strategies for Non-linear Systems. Springer-Verlag, Berlin-Heidelberg (2014)CrossRefGoogle Scholar
  23. 23.
    Witczak, M.: Fault diagnosis and fault-tolerant control strategies fornon-linear systems.Lecture Notes in Electrical Engineering 266 (2014)Google Scholar
  24. 24.
    Witczak, M., Buciakowski, M., Aubrun, C.: Predictive actuator fault-tolerant control under ellipsoidal bounding. International Journal of Adaptive Control and Signal Processing 30(2), 375–392 (2016)MathSciNetCrossRefGoogle Scholar
  25. 25.
    Wu, H.N., Feng, S., Liu, Z.Y., Guo, L.: Disturbance observer based robust mixed \({H}_2\) / \({H}_\infty \) fuzzy tracking control for hypersonic vehicles. Fuzzy Sets and Systems 306, 118–136 (2017)MathSciNetCrossRefGoogle Scholar
  26. 26.
    Xiao, B., Hu, Q., Zhang, Y.: Adaptive sliding mode fault tolerant attitude tracking control for flexible spacecraft under actuator saturation. IEEE Transactions on Control Systems Technology 20(6), 1605–1612 (2011)CrossRefGoogle Scholar
  27. 27.
    Zhang, Y., Jiang, J.: Bibliographical review on reconfigurable fault-tolerant control systems. Annual reviews in control 32(2), 229–252 (2008)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Institute of Control and Computation EngineeringUniversity of Zielona GóraZielona GóraPoland
  2. 2.Tuxtla Gutiérrez Institute of Technology, National Technological Institute of Mexico, TURIX-Dynamics Diagnosis and Control GroupTuxtla GutierrezMexico

Personalised recommendations