Saïda Bedoui

A new recursive algorithm for simultaneous identification of discrete time delay systems

Abstract A new algorithm for simultaneous online identification of unknown time delay and parameters of discrete-time delay systems is proposed in this paper. This algorithm consists in constructing a linear-parameters formulation and using the recursive least squares approach to solve the obtained system. Simulation example and experimental test results are presented to illustrate the performance of the proposed approach.

Hierarchical gradient based identification of discrete-time delay systems

In this paper, we apply a hierarchical identification principle to identify simultaneously the unknown time delay and dynamic parameters of discrete-time delay systems. In our approach, we separate the nonlinear cost function into two simple cost functions and present a gradient iterative algorithm for estimating directly the time delay and the parameters. The cost function used to estimate the time delay is an integer nonlinear programming problem (IP) and the solution of the integer version of a nonlinear optimization problem is obtained by rounding the solution for its continuous relaxation (CP). Furthermore, we give an appropriate choice of the convergence factor. Finally, the effectiveness of this method has been illustrated through simulation.

Online Identification of Multivariable Discrete Time Delay Systems Using a Recursive Least Square Algorithm

This paper addresses the problem of simultaneous identification of linear discrete time delay multivariable systems. This problem involves both the estimation of the time delays and the dynamic parameters matrices. In fact, we suggest a new formulation of this problem allowing defining the time delay and the dynamic parameters in the same estimated vector and building the corresponding observation vector. Then, we use this formulation to propose a new method to identify the time delays and the parameters of these systems using the least square approach. Convergence conditions and statistics properties of the proposed method are also developed. Simulation results are presented to illustrate the performance of the proposed method. An application of the developed approach to compact disc player arm is also suggested in order to validate simulation results.

Nonlinear approach for the identification of discrete time delay systems

A new approach for simultaneous recursive identification of an unknown time delay of discrete-time delay systems is proposed in this paper. The proposed Levenberg-Marquardts algorithm is used to deal with the identification problem. The effectiveness of this method has been illustrated through simulation.

Multistage for identification of Wiener time delay systems based on hierarchical gradient approach

ABSTRACT This paper deals with the problem of identification of Wiener systems with unknown integer time delay. This problem presents several difficulties, since it consists in estimating simultaneously the integer time delay, the parameters of the linear dynamic subsystem and the parameters of the non-linear static block. To overcome these difficulties, we propose a new approach to identify the Wiener time delay systems based on the Hierarchical gradient identification principle. This proposed method consists, first, in decoupling the original optimization problem into three simple separate criteria jointly optimized and second, in using the gradient algorithm to minimize each function. The analysis gives us insight into the properties of this algorithm and develops condition that must be satisfied to ensure the convergence and to guarantee the use of rounding property. Simulation results are presented to illustrate the performance of the proposed method.

Sensor fault estimation and compensation for hybrid switched system

In this paper, we proposed a new way that allows the identification and the compensation of sensor fault at the same time for hybrid switched systems. Indeed, to compensate this fault we chose the additive fault tolerant control (FTC). The synthesis of this FTC requires two important stages. The first step, provide the estimation of the fault by using Data-based Projection Method (MPD). The second step, is to generate the additive control and then to add it to the nominal control. The importance of the combination between the additive fault tolerant control and the Data-based Projection Method to estimate and to compensate the fault has been shown by an example.

Time delay system identification based on optimization approaches

In this paper, the problem of estimating the time delay and dynamic parameters of monovariable time delay discrete is addressed. This problem involves both the estimation of the time delay and the dynamic parameters from input-output data. In fact, we have considered our previous method which consists in minimizing a quadratic criterion using either the gradient method or the Levenberg-Marquardt method. The used criterion is deduced from a formulation allowing to define the time delay and the dynamic parameters in the same estimated vector and to build the corresponding observation vector. In order to improve the performance of this approach, we advocate the use of the quasi-Newton approach based on the Broyden-Fletcher-Goldfarb-Shanno (BFGS) algorithm. Simulation results are presented to illustrate the performance of the new solution.

Performance of a blind equalization algorithm for Rayleigh and Rician channels

This document surveys the blind equalization issue. Our approach is based on the reformulation of the equalization problem in an identification problem in existence of limited noise. The objective of the proposed method is to estimate the settings of the equalizer such that the output of the equalizer is in a neighborhood of the input constellation. The proposed method can be applied in real-time and under different type of fading channel. Some numerical experiments are presented to clarify performance of our approach under different channels: Rayleigh and Rician channels.

Identification of Hammerstein nonlinear systems with delayed input

This paper focuses on the identification problem of Hammerstein nonlinear systems with delayed input. This problem involves both the estimation of the time delay and the parameters by applying respectively the Variable Regression Estimation (VRE) technique and the gradient approach. Simulation results are presented to illustrate the the performance of the proposed method.

Time delay estimation for a class of block-oriented nonlinear models

An identification method is described for Wiener time delay systems. It consists in identifying in two-stage the parameters and the time delay: the estimation of the parameters is solved by applying a gradient algorithm and the time delay is identified by using a Variable Regression Estimation technique. Simulation results are presented to illustrate the performance of the proposed method.