Scopus İndeksli Yayınlar Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/395

Browse

Filters

2021 - 20262

Settings

Department: search.filters.department.Abdullah Gül UniversitySubject: search.filters.subject.Parameter Estimation

Search Results

Now showing 1 - 2 of 2
  • Article
    An Adaptation Mechanism of Model Reference Adaptive System Based on Variable Structure Control for Online Parameter Estimation of IPMSM
    (Wiley, 2026-01) Tekgun, Burak; Barut, Murat; Ates, Ertugrul
    This study introduces stator currents-based model reference adaptive system (MRAS) estimators that employ variable structured control (VSC) in the adaptation mechanism to enable the online estimation of stator resistance and permanent magnet (PM) flux in interior permanent magnet synchronous motors (IPMSMs). These MRAS estimators estimate stator resistance and PM flux by analysing the error between the stator currents measured as the reference model and the stator currents generated by the adaptive model. The performance of the proposed estimators is assessed through simulation studies. Furthermore, the proposed approach is compared to a conventional MRAS employing a fixed-gain proportional-integral (PI) controller. Simulation results and error analyses indicate that the VSC-based MRAS algorithms outperform traditional PI-based MRAS in terms of accuracy and reliability. Additionally, the proposed method eliminates the reliance on a fixed-gain PI controller, a common component in conventional MRAS systems.
  • Article
    Citation - WoS: 11
    Citation - Scopus: 12
    A Modified Multiple Shooting Algorithm for Parameter Estimation in ODEs Using Adjoint Sensitivity Analysis
    (Elsevier Science inc, 2021-02) Aydogmus, Ozgur; Tor, Ali Hakan
    To increase the predictive power of a model, one needs to estimate its unknown parameters. Almost all parameter estimation techniques in ordinary differential equation models suffer from either a small convergence region or enormous computational cost. The method of multiple shooting, on the other hand, takes its place in between these two extremes. The computational cost of the algorithm is mostly due to the calculation of directional derivatives of objective and constraint functions. Here we modify the multiple shooting algorithm to use the adjoint method in calculating these derivatives. In the literature, this method is known to be a more stable and computationally efficient way of computing gradients of scalar functions. A predator-prey system is used to show the performance of the method and supply all necessary information for a successful and efficient implementation. (C) 2020 Elsevier Inc. All rights reserved.