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Parameterization of a Novel Nonlinear Estimator for Uncertain SISO Systems with Noise Scenario

Author

Listed:
  • Ahmad Taher Azar

    (College of Computer and Information Sciences, Prince Sultan University, Riyadh 11586, Saudi Arabia
    Faculty of Computers and Artificial Intelligence, Benha University, Benha 13518, Egypt)

  • Farah Ayad Abdul-Majeed

    (Aeronautical Department, College of Technical Engineering, Alfarahidi University, Baghdad 10070, Iraq)

  • Hasan Sh. Majdi

    (Department of Chemical Engineering and Petroleum Industries, Al-Mustaqbal University College, Babylon 51001, Iraq)

  • Ibrahim A. Hameed

    (Department of ICT and Natural Sciences, Norwegian University of Science and Technology, Larsgårdsve-gen, 2, 6009 Ålesund, Norway)

  • Nashwa Ahmad Kamal

    (Faculty of Engineering, Cairo University, Giza 12613, Egypt)

  • Anwar Jaafar Mohamad Jawad

    (Department of Computer Techniques Engineering, Al-Rafidain University College, Baghdad 10064, Iraq
    College of Technical Engineering, The Islamic University, Najaf 54001, Iraq)

  • Ali Hashim Abbas

    (College of Information Technology, Imam Ja’afar Al-Sadiq University, Al-Muthanna, Samawah 66002, Iraq)

  • Wameedh Riyadh Abdul-Adheem

    (Department of Electrical Power Engineering Techniques, Al-Mamoun University College, Baghdad 10013, Iraq)

  • Ibraheem Kasim Ibraheem

    (Department of Computer Techniques Engineering, Dijlah University College, Baghdad 10022, Iraq)

Abstract

Dynamic observers are commonly used in feedback loops to estimate the system’s states from available control inputs and measured outputs. The presence of measurement noise degrades the performance of the observer and consequently degrades the performance of the controlled system. This paper presents a novel nonlinear higher-order extended state observer (NHOESO) for efficient state and disturbance estimation in presence of measurement noise for nonlinear single-input–single-output systems. The proposed nonlinear function allows a fast reconstruction of the system’s states and is robust against uncertainties and measurement noise. An analytical parameterization technique is proposed to parameterize the coefficients of the proposed nonlinear higher-order extended state observer in the case of measurement noise in the output signal. Several scenarios are simulated to demonstrate the effectiveness of the proposed observer.

Suggested Citation

  • Ahmad Taher Azar & Farah Ayad Abdul-Majeed & Hasan Sh. Majdi & Ibrahim A. Hameed & Nashwa Ahmad Kamal & Anwar Jaafar Mohamad Jawad & Ali Hashim Abbas & Wameedh Riyadh Abdul-Adheem & Ibraheem Kasim Ibr, 2022. "Parameterization of a Novel Nonlinear Estimator for Uncertain SISO Systems with Noise Scenario," Mathematics, MDPI, vol. 10(13), pages 1-17, June.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:13:p:2261-:d:850274
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    References listed on IDEAS

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    1. He, Yuzhu & Fu, Yuxuan & Qiao, Zijian & Kang, Yanmei, 2021. "Chaotic resonance in a fractional-order oscillator system with application to mechanical fault diagnosis," Chaos, Solitons & Fractals, Elsevier, vol. 142(C).
    2. Yi Chang & Peng Zhou & Ben Niu & Huanqing Wang & Ning Xu & M. O. Alassafi & A. M. Ahmad, 2021. "Switched-observer-based adaptive output-feedback control design with unknown gain for pure-feedback switched nonlinear systems via average dwell time," International Journal of Systems Science, Taylor & Francis Journals, vol. 52(9), pages 1731-1745, July.
    3. Yulin Li & Ben Niu & Guangdeng Zong & Jinfeng Zhao & Xudong Zhao, 2022. "Command filter-based adaptive neural finite-time control for stochastic nonlinear systems with time-varying full-state constraints and asymmetric input saturation," International Journal of Systems Science, Taylor & Francis Journals, vol. 53(1), pages 199-221, January.
    4. Qiao, Zijian & Shu, Xuedao, 2021. "Coupled neurons with multi-objective optimization benefit incipient fault identification of machinery," Chaos, Solitons & Fractals, Elsevier, vol. 145(C).
    5. Abdelghani Djeddi & Djalel Dib & Ahmad Taher Azar & Salem Abdelmalek, 2019. "Fractional Order Unknown Inputs Fuzzy Observer for Takagi–Sugeno Systems with Unmeasurable Premise Variables," Mathematics, MDPI, vol. 7(10), pages 1-16, October.
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