Search alternatives:
generation algorithm » genetic algorithm (Expand Search), detection algorithm (Expand Search)
Showing 1 - 6 results of 6 for search 'arbitrary generation algorithm*', query time: 0.04s Refine Results
  1. 1

    Selection of the learning gain matrix of an iterative learning control algorithm in presence of measurement noise by Saab, Samer S.

    Published 2005
    “…This work also provides a recursive algorithm that generates the appropriate learning gain functions that meet the arbitrary high precision output tracking objective. …”
    Get full text
    Get full text
    Get full text
    Get full text
    article
  2. 2

    Optimal selection of the forgetting matrix into an iterative learning control algorithm by Saab, Samer S.

    Published 2005
    “…A recursive optimal algorithm, based on minimizing the input error covariance matrix, is derived to generate the optimal forgetting matrix and the learning gain matrix of a P-type iterative learning control (ILC) for linear discrete-time varying systems with arbitrary relative degree. …”
    Get full text
    Get full text
    Get full text
    Get full text
    article
  3. 3

    A stochastic iterative learning control algorithm with application to an induction motor by Saab, Samer S.

    Published 2004
    “…The convergence characteristics are shown to be similar to the ones of the optimal recursive algorithm. The proposed ILC algorithms are applied to two different models of an induction motor for angular speed tracking control. …”
    Get full text
    Get full text
    Get full text
    Get full text
    article
  4. 4

    Fuzzy Logic Adaptive Crow Search Algorithm for MPPT of a Partially Shaded Photovoltaic System by Mohamed Ali Zeddini (22047920)

    Published 2024
    “…<p dir="ltr">The arbitrary selection of the Crow Search Algorithm (CSA) parameters, the Awareness Probability (AP) and the Flight Length (fl) results in poor convergence performance and efficiency even if the CSA performs well when solving global optimization problems. …”
  5. 5
  6. 6