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Veisi, Amir, Shiri, Mohsen, Delavari, Hadi. (1402). Fractional Order Sliding Mode Observer-Based Control in the Presence of Faults. پژوهشنامه مدیریت اجرایی, 1(1), 19-24. doi: 10.22080/cste.2024.5010
Amir Veisi; Mohsen Shiri; Hadi Delavari. "Fractional Order Sliding Mode Observer-Based Control in the Presence of Faults". پژوهشنامه مدیریت اجرایی, 1, 1, 1402, 19-24. doi: 10.22080/cste.2024.5010
Veisi, Amir, Shiri, Mohsen, Delavari, Hadi. (1402). 'Fractional Order Sliding Mode Observer-Based Control in the Presence of Faults', پژوهشنامه مدیریت اجرایی, 1(1), pp. 19-24. doi: 10.22080/cste.2024.5010
Veisi, Amir, Shiri, Mohsen, Delavari, Hadi. Fractional Order Sliding Mode Observer-Based Control in the Presence of Faults. پژوهشنامه مدیریت اجرایی, 1402; 1(1): 19-24. doi: 10.22080/cste.2024.5010

Fractional Order Sliding Mode Observer-Based Control in the Presence of Faults

Contributions of Science and Technology for Engineering
دوره 1، شماره 1، خرداد 2024، صفحه 19-24    اصل مقاله (1.02 M)
نوع مقاله: Original Article
شناسه دیجیتال (DOI): 10.22080/cste.2024.5010
نویسندگان
Amir Veisi1؛ Mohsen Shiri1؛ Hadi Delavari* 2
1Department of Electrical Engineering, Faculty of Engineering, Bu-Ali Sina University, Hamedan, Iran
2Department of Electrical Engineering, Hamedan University of Technology, Hamedan, Iran
تاریخ دریافت: 18 دی 1402،  تاریخ بازنگری: 12 بهمن 1402،  تاریخ پذیرش: 15 بهمن 1402 
چکیده
A successfully validated and precise system model would greatly enhance the performance of the controller, making system identification a major procedure in control system design. The inverted pendulum is a highly nonlinear and open-loop unstable system that makes control more challenging. In this paper, at first, a novel fractional order sliding mode observer (FOSMO) is designed to estimate the state space of the rotary inverted pendulum, and after that, a fractional sliding fault estimation is proposed. The proposed observer had high accuracy and speed in fault and state observation because of the advantages of fractional calculus and the sliding mode observer method. The proposed observer is compared with the classical sliding mode observer
کلیدواژه‌ها
Fault Estimation؛ Fractional Calculus؛ Sliding Mode Observer؛ Rotary Inverted Pendulum
مراجع
  • Fendzi-Donfack, E., Baduidana, M., Fotsa-Ngaffo, F., & Kenfack-Jiotsa, A. (2023). Construction of abundant solitons in a coupled nonlinear pendulum lattice through two discrete distinct techniques. Results in Physics, 52, 106783. doi:10.1016/j.rinp.2023.106783.
  • Fu, H., Jiang, J., Hu, S., Rao, J., & Theodossiades, S. (2023). A multi-stable ultra-low frequency energy harvester using a nonlinear pendulum and piezoelectric transduction for self-powered sensing. Mechanical Systems and Signal Processing, 189, 110034. doi:10.1016/j.ymssp.2022.110034.
  • Akhtaruzzaman, M., & Shafie, A. A. (2010). Modeling and control of a rotary inverted pendulum using various methods, comparative assessment and result analysis. 2010 IEEE International Conference on Mechatronics and Automation, ICMA 2010, 1342–1347. doi:10.1109/ICMA.2010.5589450.
  • Gao, Z., Cecati, C., & Ding, S. X. (2015). A survey of fault diagnosis and fault-tolerant techniques-part I: Fault diagnosis with model-based and signal-based approaches. IEEE Transactions on Industrial Electronics, 62(6), 3757–3767. doi:10.1109/TIE.2015.2417501.
  • Gueddi, I., Nasri, O., Benothman, K., & Dague, P. (2017). Fault Detection and Isolation of spacecraft thrusters using an extended principal component analysis to interval data. International Journal of Control, Automation and Systems, 15(2), 776–789. doi:10.1007/s12555-015-0258-x.
  • Deng, F., Liu, C., & Chen, Z. (2023). Modular Multilevel Converters: Control, Fault Detection, and Protection. John Wiley & Sons, Hoboken, United States. doi:10.1002/9781119875635.
  • Du, D., Sun, S., Cocquempot, V., & Zhao, H. (2024). H∞/H− fault detection observer design for nonlinear conformable fractional-order systems. Journal of Computational and Applied Mathematics, 441, 115711. doi:10.1016/j.cam.2023.115711.
  • Zeghlache, S., Ghellab, M. Z., Djerioui, A., Bouderah, B., & Benkhoris, M. F. (2023). Adaptive fuzzy fast terminal sliding mode control for inverted pendulum-cart system with actuator faults. Mathematics and Computers in Simulation, 210, 207–234. doi:10.1016/j.matcom.2023.03.005.
  • Veisi, A., & Delavari, H. (2023). Adaptive fractional backstepping intelligent controller for maximum power extraction of a wind turbine system. Journal of Renewable and Sustainable Energy, 15(6). doi:10.1063/5.0161571.
  • Keijzer, T., Engelbrecht, J. A. A., Goupil, P., & Ferrari, R. M. G. (2023). A sliding mode observer approach to oscillatory fault detection in commercial aircraft. Control Engineering Practice, 141, 105719. doi:10.1016/j.conengprac.2023.105719.
  • Delavari, H., & Veisi, A. (2024). A new robust nonlinear controller for fractional model of wind turbine based DFIG with a novel disturbance observer. Energy Systems, 15(2), 827–861. doi:10.1007/s12667-023-00566-3.
  • Cao, F., Jia, F., & He, X. (2024). Input Design for Active Fault Detection: Reconciling System Control Objectives. IEEE Transactions on Cybernetics, 54(7), 3931–3942. doi:10.1109/TCYB.2023.3331971.
  • Veisi, A., Delavari, H., & Shanaghi, F. (2023). Maximum Power Point Tracking in a Photovoltaic System by Optimized Fractional Nonlinear Controller. 2023 8th International Conference on Technology and Energy Management (ICTEM). doi:10.1109/ictem56862.2023.10083639.
  • Veisi, A., & Delavari, H. (2023). Adaptive optimized fractional order control of doubly‐fed induction generator (DFIG) based wind turbine using disturbance observer. Environmental Progress & Sustainable Energy, 43(2). doi:10.1002/ep.14087.
  • Veisi, A., & Delavari, H. (2021). Adaptive Fractional order Control of Photovoltaic Power Generation System with Disturbance Observer. 2021 7th International Conference on Control, Instrumentation and Automation (ICCIA). doi:10.1109/iccia52082.2021.9403598.
  • DDelavari, H., & Veisi, A. (2021). Robust Control of a Permanent Magnet Synchronous Generators based Wind Energy Conversion. 2021 7th International Conference on Control, Instrumentation and Automation (ICCIA). doi:10.1109/iccia52082.2021.9403590.
  • Golmankhaneh, A. K. (2022). Fractal Calculus And Its Applications: Fα-calculus. In Fractal Calculus And Its Applications: Fα-calculus. World Scientific. doi:10.1142/12988.
  • Huang, J., Zhang, T., Fan, Y., & Sun, J. Q. (2019). Control of Rotary Inverted Pendulum Using Model-Free Backstepping Technique. IEEE Access, 7, 96965–96973. doi:10.1109/ACCESS.2019.2930220.
  • Shtessel, Y., Edwards, C., Fridman, L., & Levant, A. (2014). Sliding Mode Control and Observation. Control Engineering, Springer, New York, United States. doi:10.1007/978-0-8176-4893-0.
  • Zhang, X., He, J., Ma, H., Ma, Z., & Ge, X. (2023). Stability Enhancement Methods of Inverters Based on Lyapunov Function, Predictive Control, and Reinforcement Learning, Springer Nature, Singapore. doi:10.1007/978-981-19-7191-4.
  • Björnsson, H. (2023). Lyapunov Functions for Stochastic Systems: Theory and Numerics. PhD Thesis, University of Iceland, Reykjavík, Iceland.
  • Nath, K., & Dewan, L. (2017). Control of a rotary inverted pendulum via adaptive techniques. 2017 International Conference on Emerging Trends in Computing and Communication Technologies (ICETCCT). doi:10.1109/icetcct.2017.8280315.
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