Kaouther Ibn Taarit

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A fast identification algorithm is proposed for systems with delayed inputs. It is based on a non-asymptotic distributional estimation technique initiated in the framework of systems without delay. Such technique leads to simple realization schemes, involving integrators, multipliers and piecewise polynomial or exponential time functions. Thus, it allows(More)
This paper deals with on-line identification of continuous-time systems subject to impulsive terms. Using a distribution framework, a scheme is proposed in order to annihilate singular terms in differential equations representing a class of impulsive systems. As a result, an on-line estimation of unknown parameters is provided, regardless of the switching(More)
In this paper, we propose an online continuous identification technique of first-order plus dead time (FOPDT) using typical inputs. The impulse test is assessed at the beginning to deduce the basis of the identification algorithm, due to its uncomplicated physical interpretation. The remaining typical test signals are then inferred easily. These test(More)
This research considers the problem of online identification of continuous-time system with multiple unknown time delays from sampled data. The presented algorithm estimates, simultaneously, the linear parameters and the multiple time delays. Therefore, a Sequential Nonlinear Least Square algorithm is used. Indeed, we propose a new formulation of the(More)
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