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SOS-Based Nonlinear Observer Design for Simultaneous State and Disturbance Estimation Designed for a PMSM Model

Author

Listed:
  • Artun Sel

    (Department of Electrical-Electronics Engineering, TOBB University of Economics and Technology, Ankara 06510, Turkey)

  • Bilgehan Sel

    (The Bradley Department of Electrical and Computer Engineering, Virginia Tech, Blacksburg, VA 24061, USA)

  • Umit Coskun

    (Department of Physics and Astronomy, University of Kentucky, Lexington, KY 40506, USA)

  • Cosku Kasnakoglu

    (Department of Electrical-Electronics Engineering, TOBB University of Economics and Technology, Ankara 06510, Turkey)

Abstract

In this study, a type of nonlinear observer design is studied for a class of nonlinear systems. For the construction of the nonlinear observer, SOS-based optimization tools are utilized, which for some nonlinear dynamical systems have the advantage of transforming the problem into a more tractable one. The general problem of nonlinear observer design is translated into an SOS polynomial optimization which can be turned into an SDP problem. For a study problem, simultaneous state and disturbance estimation is considered, a cascaded nonlinear observer using a certain parameterization is constructed, and computation techniques are discussed. Cascade nonlinear observer structure is a design strategy that decomposes the problem into its components resulting in dimension reduction. In this paper, SOS-based methods using the cascade design technique are represented, and a simultaneous state and disturbance signal online estimation algorithm is constructed. The method with its smaller components is given in detail, the efficacy of the method is demonstrated by means of numerical simulations performed in MATLAB, and the observer is designed using numerical optimization tools YALMIP, MOSEK, and PENLAB.

Suggested Citation

  • Artun Sel & Bilgehan Sel & Umit Coskun & Cosku Kasnakoglu, 2022. "SOS-Based Nonlinear Observer Design for Simultaneous State and Disturbance Estimation Designed for a PMSM Model," Sustainability, MDPI, vol. 14(17), pages 1-12, August.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:17:p:10650-:d:898568
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    References listed on IDEAS

    as
    1. Yubo Liu & Junlong Fang & Kezhu Tan & Boyan Huang & Wenshuai He, 2020. "Sliding Mode Observer with Adaptive Parameter Estimation for Sensorless Control of IPMSM," Energies, MDPI, vol. 13(22), pages 1-18, November.
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    4. Cholleti Sriram & Jarupula Somlal & B. Srikanth Goud & Mohit Bajaj & Mohamed F. Elnaggar & Salah Kamel, 2022. "Improved Deep Neural Network (IDNN) with SMO Algorithm for Enhancement of Third Zone Distance Relay under Power Swing Condition," Mathematics, MDPI, vol. 10(11), pages 1-19, June.
    5. Chunlei Wang & Dongxing Cao & Xiangxu Qu & Chen Fan, 2022. "An Improved Finite Control Set Model Predictive Current Control for a Two-Phase Hybrid Stepper Motor Fed by a Three-Phase VSI," Energies, MDPI, vol. 15(3), pages 1-17, February.
    6. Ameni Ellouze & Omar Kahouli & Mohamed Ksantini & Ali Rebhi & Nidhal Hnaien & François Delmotte, 2021. "Continuous Stability TS Fuzzy Systems Novel Frame Controlled by a Discrete Approach and Based on SOS Methodology," Mathematics, MDPI, vol. 9(23), pages 1-18, December.
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