Djeddi A, Dib D, Azar A-T, Abdelmalek S.
Fractional Order Unknown Inputs Fuzzy Observer for Takagi–Sugeno Systems with Unmeasurable Premise Variables. Mathematics [Internet]. 2019;7 (10).
Publisher's VersionAbstract
This paper presents a new procedure for designing a fractional order unknown input observer (FOUIO) for nonlinear systems represented by a fractional-order Takagi–Sugeno (FOTS) model with unmeasurable premise variables (UPV). Most of the current research on fractional order systems considers models using measurable premise variables (MPV) and therefore cannot be utilized when premise variables are not measurable. The concept of the proposed is to model the FOTS with UPV into an uncertain FOTS model by presenting the estimated state in the model. First, the fractional-order extension of Lyapunov theory is used to investigate the convergence conditions of the FOUIO, and the linear matrix inequalities (LMIs) provide the stability condition. Secondly, performances of the proposed FOUIO are improved by the reduction of bounded external disturbances. Finally, an example is provided to clarify the proposed method. The obtained results show that a good convergence of the outputs and the state estimation errors were observed using the new proposed FOUIO.
Meddour H.
LOCAL PERSISTENCE OF GEOMETRIC STRUCTURES FOR BOUSSINESQ SYSTEM WITH ZERO VISCOSITY. [Internet]. 2019;71 (4) :285-303.
Publisher's VersionAbstract
The current paper deals with the local well-posedness problem for the twodimensional partial viscous Boussinesq system when the initial vorticity belongs to the patch class. We prove in particular some results concerning the regularity persistence of the patch boundary and establish the convergence towards the inviscid limit when the molecular diffusivity goes to zero.
Bounibane B, Djeffal E-A.
Kernel function-based interior-point algorithms for linear optimisation. International Journal of Mathematical Modelling and Numerical Optimisation [Internet]. 2019;9 (2) :158.
Publisher's VersionAbstract
We propose a primal-dual interior-point algorithm for linear optimisation based on a class of kernel functions which is eligible. New search directions and proximity measures are defined based on these functions. We derive the complexity bounds for large and small-update methods respectively. These are currently the best known complexity results for such methods.