Electronic structure and magnetic properties of KXF3(X= Fe, Co, Mn, V) from ab initio calculations.

In this work we have performed first-principle calculations of the structural, electronic and magnetic properties of KFeF3, KCoF3, KMnF3, KVF3, using full-potential linearized augmented plane-wave (FP-LAPW) scheme within GGA. Features such as the lattice constant, bulk modulus and its pressure derivative are reported. Also, we have presented our results of the band structure and the density of states. The magnetic moments of KFeF3, KCoF3, KMnF3, KVF3 compounds are in most came from the exchange-splitting of X-3d orbital. Keywords: Magnetic materials; Ab initio calculations; Electronic structur

Algebraic estimation in partial derivatives systems: parameters and differentiation problems

International audienceTwo goals are sought in this paper: namely, to provide a succinct overview on algebraic techniques for numerical differentiation and parameter estimation for linear systems and to present novel algebraic methods in the case of several variables. The state-of-art in the introduction is followed by a brief description of the methodology in the subsequent sections. Our new algebraic methods are illustrated by two examples in the multidimensional case. Some algebraic preliminaries are given in the appendix

A new method for estimating derivatives based on a distribution approach

International audienceIn many applications, the estimation of derivatives has to be done from noisy measured signal. In this paper, an original method based on a distribution approach is presented. Its interest is to report the derivatives on infinitely differentiable functions. Thus, the estimation of the derivatives is done only from the signal. Besides, this method gives some explicit formulae leading to fast calculus. For all these reasons, it is an efficient method in the case of noisy signals as it will be confirmed in several examples

A Numerical Algorithm for Filtering and State Observation

This paper deals with a numerical method for data fitting and estimation of continuous higher-order derivatives of a given signal from its non-exactsampled data. The proposed algorithm is a generalization of the algorithm proposed by Reinsch (1967). This algorithm is conceived as a key element in the structure of the numerical observer discussed in our recent papers. Satisfactory results are obtained which prove the efficiency of the proposed approach

A numerical procedure for filtering and efficient high-order signal differentiation

In this paper, we propose a numerical algorithm for filtering and robust signal differentiation. The numerical procedure is based on the solution of a simplified linear optimization problem. A compromise between smoothing and fidelity with respect to the measurable data is achieved by the computation of an optimal regularization parameter that minimizes the Generalized Cross Validation criterion (GCV). Simulation results are given to highlight the effectiveness of the proposed procedure

Induction motor speed control using reduced-order model

Induction machines have a highly nonlinear model with only partial state information. The unavailability of all states and the presence of unknown disturbances make controller design and proving closed-loop stability challenging tasks. In this paper, we present a control scheme for induction motor speed control using a reduced, second-order model. The model greatly simplifies the control structure and its stability analysis. Current and speed measurements are used while the unknown flux and load torque are estimated using observers. The closed-loop stability of the observer-based control structure is established using Lyapunov's analysis. Simulation studies carried out on a 50 HP induction motor driven by a three-phase inverter show that the proposed controller achieves good speed control for both the regulation and tracking test cases under unknown disturbance