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Tytuł artykułu

Fault-tolerant tracking control for a non-linear twin-rotor system under ellipsoidal bounding

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
A novel fault-tolerant tracking control scheme based on an adaptive robust observer for non-linear systems is proposed. Additionally, it is presumed that the non-linear system may be faulty, i.e., affected by actuator and sensor faults along with the disturbances, simultaneously. Accordingly, the stability of the robust observer as well as the fault-tolerant tracking controller is achieved by using the ℋ∞ approach. Furthermore, unknown actuator and sensor faults and states are bounded by the uncertainty intervals for estimation quality assessment as well as reliable fault diagnosis. This means that narrow intervals accompany better estimation quality. Thus, to cope with the above difficulty, it is assumed that the disturbances are over-bounded by an ellipsoid. Consequently, the performance and correctness of the proposed fault-tolerant tracking control scheme are verified by using a non-linear twin-rotor aerodynamical laboratory system.
Rocznik
Strony
171--183
Opis fizyczny
Bibliogr. 38 poz., rys., tab., wykr.
Twórcy
  • Institute of Control and Computation Engineering University of Zielona Góra, Szafrana 2, 65-516 Zielona Góra, Poland
  • Institute of Control and Computation Engineering University of Zielona Góra, Szafrana 2, 65-516 Zielona Góra, Poland
  • Institute of Control and Computation Engineering University of Zielona Góra, Szafrana 2, 65-516 Zielona Góra, Poland
  • Institute of Control and Computation Engineering University of Zielona Góra, Szafrana 2, 65-516 Zielona Góra, Poland
Bibliografia
  • [1] Abbaspour, A., Yen, K.K., Forouzannezhad, P. and Sargolzaei, A. (2018). A neural adaptive approach for active fault-tolerant control design in UAV, IEEE Transactions on Systems, Man, and Cybernetics: Systems 50(9): 3401–3411.
  • [2] Altan, A. and Hacıoğlu, R. (2020). Model predictive control of three-axis gimbal system mounted on UAV for real-time target tracking under external disturbances, Mechanical Systems and Signal Processing 138(2020): 106548.
  • [3] Azzoug, Y., Sahraoui, M., Pusca, R., Ameid, T., Romary, R. and Cardoso, A.J.M. (2021). Current sensors fault detection and tolerant control strategy for three-phase induction motor drives, Electrical Engineering 103(2): 881–898.
  • [4] Camci, F., Medjaher, K., Atamuradov, V. and Berdinyazov, A. (2019). Integrated maintenance and mission planning using remaining useful life information, Engineering Optimization 51(10): 1794–1809.
  • [5] Chen, F., Gong, J. and Li, Y. (2019). Adaptive diagnosis and compensation for hypersonic flight vehicle with multisensor faults, International Journal of Robust and Nonlinear Control 29(17): 6145–6163.
  • [6] Chung, W. and Son, H. (2020). Fault-tolerant control of multirotor UAVs by control variable elimination, IEEE/ASME Transactions on Mechatronics 25(5): 2513–2522.
  • [7] Habibi, H., Howard, I. and Simani, S. (2019). Reliability improvement of wind turbine power generation using model-based fault detection and fault tolerant control: A review, Renewable Energy 135(2019): 877–896.
  • [8] Hamadi, H., Lussier, B., Fantoni, I., Francis, C. and Shraim, H. (2020). Comparative study of self tuning, adaptive and multiplexing FTC strategies for successive failures in an octorotor UAV, Robotics and Autonomous Systems 133(2020): 103602.
  • [9] Hamdi, H., Rodrigues, M., Rabaoui, B. and Benhadj Braiek, N. (2021). A fault estimation and fault-tolerant control based sliding mode observer for LPV descriptor systems with time delay, International Journal of Applied Mathematics and Computer Science 31(2): 247–258, DOI: 10.34768/amcs-2021-0017.
  • [10] Hu, K., Li, W. and Cheng, Z. (2021). Fuzzy adaptive fault diagnosis and compensation for variable structure hypersonic vehicle with multiple faults, PLOS ONE 16(8): e0256200.
  • [11] INTECO (2007). Two Rotor Aerodynamical System: User’s Manual, INTECO, Kraków.
  • [12] Kukurowski, N., Pazera, M. and Witczak, M. (2021). Fault-tolerant tracking control and remaining useful life estimation for Takagi–Sugeno fuzzy system, 2021 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), Luxembourg, pp. 687–693.
  • [13] Li, L., Luo, H., Ding, S.X., Yang, Y. and Peng, K. (2019). Performance-based fault detection and fault-tolerant control for automatic control systems, Automatica 99(2019): 308–316.
  • [14] Liu, F., Tang, H., Luo, J., Bai, L. and Pu, H. (2021). Fault-tolerant control of active compensation toward actuator faults: An autonomous underwater vehicle example, Applied Ocean Research 110(2021): 102597.
  • [15] Manohar, M. and Das, S. (2020). Notice of removal: Current sensor fault-tolerant control of induction motor driven electric vehicle using flux-linkage observer, 2020 IEEE Transportation Electrification Conference & Expo (ITEC), Chicago, USA, pp. 884–889.
  • [16] Mrugalski, M. (2014). Advanced Neural Network-based Computational Schemes for Robust Fault Diagnosis, Springer, Berlin.
  • [17] Nguyen, D.-T., Saussié, D. and Saydy, L. (2017). Robust self-scheduled fault-tolerant control of a quadrotor UAV, IFAC-PapersOnLine 50(1): 5761–5767.
  • [18] Patel, H.R. and Shah, V.A. (2019). A passive fault-tolerant control strategy for a non-linear system: An application to the two tank conical non-interacting level control system, Maskay 9(1): 1–8.
  • [19] Pazera, M. and Witczak, M. (2019). Towards robust simultaneous actuator and sensor fault estimation for a class of nonlinear systems: Design and comparison, IEEE Access 7: 97143–97158.
  • [20] Petritoli, E., Leccese, F. and Ciani, L. (2018). Reliability and maintenance analysis of unmanned aerial vehicles, Sensors 18(9): 3171.
  • [21] Prochazka, K.F. and Stomberg, G. (2020). Integral sliding mode based model reference FTC of an over-actuated hybrid UAV using online control allocation, 2020 American Control Conference (ACC), Denver, USA, pp. 3858–3864.
  • [22] Rodrigues, L.R., Gomes, J.P. and Alcântara, J.F. (2018). Embedding remaining useful life predictions into a modified receding horizon task assignment algorithm to solve task allocation problems, Journal of Intelligent & Robotic Systems 90(1): 133–145.
  • [23] Sadhu, V., Zonouz, S. and Pompili, D. (2020). On-board deep-learning-based unmanned aerial vehicle fault cause detection and identification, 2020 IEEE International Conference on Robotics and Automation (ICRA), Paris, France, pp. 5255–5261.
  • [24] Saied, M., Lussier, B., Fantoni, I., Shraim, H. and Francis, C. (2020). Active versus passive fault-tolerant control of a redundant multirotor UAV, Aeronautical Journal 124(1273): 385–408.
  • [25] Sun, K. and Liu, X. (2021). Path planning for an autonomous underwater vehicle in a cluttered underwater environment based on the heat method, International Journal of Applied Mathematics and Computer Science 31(2): 289–301, DOI: 10.34768/amcs-2021-0020.
  • [26] Taimoor, M., Lu, X., Maqsood, H. and Sheng, C. (2021). Adaptive rapid neural observer-based sensors fault diagnosis and reconstruction of quadrotor unmanned aerial vehicle, Aircraft Engineering and Aerospace Technology 93(5): 847–861.
  • [27] Tang, H., Chen, Y. and Zhou, A. (2021). Actuator fault-tolerant control for four-wheel-drive-by-wire electric vehicle, IEEE Transactions on Transportation Electrification 8(2): 2361–2373.
  • [28] Veremey, E.I. (2021). An approximate solution of the affine-quadratic control problem based on the concept of optimal damping, International Journal of Applied Mathematics and Computer Science 31(1): 5–15, DOI: 10.34768/amcs-2021-0001.
  • [29] Vural, S.Y., Dasdemir, J. and Hajiyev, C. (2018). Passive fault tolerant lateral controller design for an UAV, IFAC-PapersOnLine 51(30): 446–451.
  • [30] Wang, X. (2020). Active fault tolerant control for unmanned underwater vehicle with sensor faults, IEEE Transactions on Instrumentation and Measurement 69(12): 9485–9495.
  • [31] Witczak,M. (2014). Fault Diagnosis and Fault-Tolerant Control Strategies for Non-Linear Systems, Springer, Heidelberg.
  • [32] Witczak, M., Buciakowski, M. and Aubrun, C. (2016a). Predictive actuator fault-tolerant control under ellipsoidal bounding, International Journal of Adaptive Control and Signal Processing 30(2): 375–392.
  • [33] Witczak, M., Buciakowski, M. and Mrugalski, M. (2014). An H_infinity approach to fault estimation of non-linear systems: application to one-link manipulator, Methods and Models in Automation and Robotics, MMAR, Międzyzdroje, Poland, pp. 456–461.
  • [34] Witczak, M., Buciakowski, M., Puig, V., Rotondo, D. and Nejjari, F. (2016b). An LMI approach to robust fault estimation for a class of nonlinear systems, International Journal of Robust and Nonlinear Control 26(7): 1530–1548.
  • [35] Witczak, M., Mrugalski, M., Pazera, M. and Kukurowski, N. (2020). Fault diagnosis of an automated guided vehicle with torque and motion forces estimation: A case study, ISA Transactions 104(2020): 370–381.
  • [36] Yu, Z., Zhang, Y., Jiang, B., Su, C.-Y., Fu, J., Jin, Y. and Chai, T. (2021). Nussbaum-based finite-time fractional-order backstepping fault-tolerant flight control of fixed-wing UAV against input saturation with hardware-in-the-loop validation, Mechanical Systems and Signal Processing 153(2021): 107406.
  • [37] Zemouche, A. and Boutayeb, M. (2013). On LMI conditions to design observers for Lipschitz nonlinear systems, Automatica 49(2): 585–591.
  • [38] Zhang, X., Zhao, Z., Wang, Z. and Wang, X. (2021). Fault detection and identification method for quadcopter based on airframe vibration signals, Sensors 21(2): 581.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-9bf41b15-8bed-4050-bda6-7dbd2d522608
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