Anis Khouaja

Convergence analysis of the alternating RGLS algorithm for the identification of the reduced complexity Volterra model

In this paper we provide a convergence analysis of the alternating RGLS (Recursive Generalized Least Square) algorithm used for the identification of the reduced complexity Volterra model describing stochastic non-linear systems. The reduced Volterra model used is the 3rd order SVD-PARAFC-Volterra model provided using the Singular Value Decomposition (SVD) and the Parallel Factor (PARAFAC) tensor decomposition of the quadratic and the cubic kernels respectively of the classical Volterra model. The Alternating RGLS (ARGLS) algorithm consists on the execution of the classical RGLS algorithm in alternating way. The ARGLS convergence was proved using the Ordinary Differential Equation (ODE) method. It is noted that the algorithm convergence canno׳t be ensured when the disturbance acting on the system to be identified has specific features. The ARGLS algorithm is tested in simulations on a numerical example by satisfying the determined convergence conditions. To raise the elegies of the proposed algorithm, we proceed to its comparison with the classical Alternating Recursive Least Squares (ARLS) presented in the literature. The comparison has been built on a non-linear satellite channel and a benchmark system CSTR (Continuous Stirred Tank Reactor). Moreover the efficiency of the proposed identification approach is proved on an experimental Communicating Two Tank system (CTTS).

Identification of nonlinear stochastic systems described by a reduced complexity Volterra model using an ARGLS algorithm

This paper proposes a stochastic identification algorithm of a model describing non linear stochastic system. The identified model known as SVD-PARAFAC-Volterra model [1] results from tensor decomposition of kernels of classical Volterra model. The proposed algorithm uses the Recursive Generalized Least Square (RGLS) method in alternative way to estimate the parameters of the model. The algorithm validation is ensured by simulation results.

Constrained predictive control of a SISO nonlinear system based on third-order S-PARAFAC Volterra models:

This paper is concerned with the identification and nonlinear predictive control approach for a nonlinear process based on a third-order reduced complexity, discrete-time Volterra model called the third-order S-PARAFAC Volterra model. The proposed model is given using the PARAFAC tensor decomposition that provides a parametric reduction compared with the conventional Volterra model. In addition, the symmetry property of the Volterra kernels allows us to further reduce the complexity of the model. These properties allow synthesizing a nonlinear model-based predictive control (NMBPC). Then we construct the general form of a new predictor and we propose an optimization algorithm formulated as a quadratic programming (QP) algorithm under linear and nonlinear constraints. The performance of the proposed third-order S-PARAFAC Volterra model and the developed NMBPC algorithm are illustrated on a numerical simulation and validated on a benchmark such as a continuous stirred-tank reactor system.

Elements discrimination in the study of super-heavy elements using an ionization chamber

Abstract Dedicated ionization chamber (IC) was built and installed to measure the energy loss of very heavy nuclei at 2.7 MeV / u produced in fusion reactions in inverse kinematics (beam of 208 Pb ). After going through the IC, products of reactions on 12 C , 18 O targets are implanted in a Si detector. Their identification through their α-decay chain is ambiguous when their half-life is short. After calibration with Pb and Th nuclei, the IC signal allowed us to resolve these ambiguities. In the search for rare super-heavy nuclei produced in fusion reactions in inverse or symmetric kinematics, such a chamber will provide direct information on the nuclear charge of each implanted nucleus.

NEW DETECTOR SYSTEM FOR SUPER HEAVY ELEMENTS DETECTION

A new detector system dedicated for very/super heavy elements (VHE/SHE) detection that decay by spontaneous fission is presented. Such a decay mode of nuclei can be found e.g. in the region of Z≈100 (Fermium). Future experiments realized in the frame of French-Polish collaboration at the cyclotrons in GANIL and in the Heavy Ion Laboratory (HIL), University of Warsaw, is described. The results of test measurements made in the HIL for reactions 20Ne(8 A.MeV)+120Sn, 179Au are presented.