- ESPRIT, électromécanique, Department Memberadd
Research Interests: Engineering, Mathematics, Computer Science, System Identification, Stochastic Programming, and 15 moreIdentification, Mathematical Sciences, Automatica, Global Optimization, Convolution, Instrumental Variable, Smoothing, Stochastic Approximation, Nonlinear system, Input Output, Noise Measurement, Global Optimum, Autom, Least squares method, and measurement noise
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A new general relationship between cumulants and impulse response coefficients of the FIR systems is presented. This relation can be used to unify several of the FIR coefficients estimation algorithms proposed in the literature. It can be... more
A new general relationship between cumulants and impulse response coefficients of the FIR systems is presented. This relation can be used to unify several of the FIR coefficients estimation algorithms proposed in the literature. It can be further used to develop a new estimation method. This relation is illustrated with a few examples.
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ABSTRACT
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Research Interests: Engineering, Mathematics, Control Theory, Model Predictive Control, Adaptive Control, and 13 moreNonlinear Control, Parameter estimation, Linear Model, Mathematical Sciences, Advanced manufacturing technology, Chemical reactors, Control Strategy, Temperature Control, Nonlinear system, Batch Reactor, Nonlinear Model, Predictive Control, and Recursive Least Square
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In this paper, two methodologies are proposed to enhance the automatic noise cancellation and signal separation between heart and lung sounds. In fact, transient signals such as heart and lung signals may undergo abrupt or sharp change in... more
In this paper, two methodologies are proposed to enhance the automatic noise cancellation and signal separation between heart and lung sounds. In fact, transient signals such as heart and lung signals may undergo abrupt or sharp change in the first and second derivatives. A real separation between such two interfering mixed signals needs an efficient approach to avoid losing important information in both signals. Rhythmic cardiac signal contains important characteristics which can be exploited to develop adaptive based algorithms that allow efficient separation between lung and heart signals when they are mixed in a recorded signal. In the first proposed methodology we have developed an algorithm based on adaptive filtering technique and build using multiple filtering functions with coefficients correlated to the mixed source signal. In the second methodology, fast independent component analysis was developed to cancel heart sound in lung mixed sound. Both methods are well detailed in this work, and a comparative study is achieved to evaluate the efficiency of each method. A high accuracy of the new proposed algorithms is found and many applications are used to quantify the performances of these techniques.
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Multiple lung obstructive and restrictive lung diseases are considered to experiment a new methodology based on Passive Time Delay Technique (PTDT). Lung sounds were recorded using a multichannel stethoscope on 32 healthy subjects, 20... more
Multiple lung obstructive and restrictive lung diseases are considered to experiment a new methodology based on Passive Time Delay Technique (PTDT). Lung sounds were recorded using a multichannel stethoscope on 32 healthy subjects, 20 COPD patients and 20 patients with different lung disorders. The sensors were distributed on the posterior and anterior chest wall. During recordings, all participants were breathing at matching airflow rates. Calculated time delay (TD) was identified for inspiration phase and an average TD value was provided after three repetitive measurements for each inspiration phase. TD computed in COPD patients: 440 ± 87 % (P < 0.05) was remarkably greater than time delay computed with normal subjects: 160 ± 10 % (P < 0.05) it was also greater than TD recorded with different other lung disorders patients. Results were presented as mean ± SD, standard deviation of time delay in ms. Significant P values (P < 0.05) were indicated using Wilcoxon test. Preliminary results are very encouraging to develop this technique and enhance lung diseases monitoring.
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In this paper, we propose a solution for tstabilizing problem of second order delay plant by Proportional-Integral (PI) controller. An extension of the Hermite -Biehler theorem, which is applicable to quasi - polynomials, is used to seek... more
In this paper, we propose a solution for tstabilizing problem of second order delay plant by Proportional-Integral (PI) controller. An extension of the Hermite -Biehler theorem, which is applicable to quasi - polynomials, is used to seek the stability region of the controller and the computation o f its optimum parameters via Abstract—In this paper, we propose a solution for the stabilizing problem of second order delay plant by Propo r- tional-Integral (PI) controller. An extension of the Her mite- Biehler theorem, which is applicable to quasi -polynomials, is used to seek the stability region of the controller and the computation of its optimum parameters via Genetic Algo- rithms. Moreover we compare the stabilities regions and different optimization performances obtained for a system which can be modeled by first and second order delay sy s- tem.
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In this paper, we consider the control of time delay system by first order controller. By Using the Hermite-Biehler theorem, which is applicable to quasipolynomials, we seek a stability region of the controller for first order delay... more
In this paper, we consider the control of time delay system by first order controller. By Using the Hermite-Biehler theorem, which is applicable to quasipolynomials, we seek a stability region of the controller for first order delay systems.
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Research Interests: Engineering, Model Predictive Control, Problem Solving, Mathematical Sciences, Advanced manufacturing technology, and 10 moreChemical reactors, Chemical Reactor, Control Strategy, Temperature Control, Nonlinear system, Batch Reactor, Nonlinear Model, Pilot Plant, Predictive Control, and exothermic reaction
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A new method is used to solve the nonconvex optimization problem of the nonlinear model predictive control (NMPC) for Hammerstein model. Using nonlinear models in MPC leads to a nonlinear and nonconvex optimization problem. Since control... more
A new method is used to solve the nonconvex optimization problem of the nonlinear model predictive control (NMPC) for Hammerstein model. Using nonlinear models in MPC leads to a nonlinear and nonconvex optimization problem. Since control performances depend essentially on the results of the optimization method, in this work, we propose to use the filled function as a global optimization method to solve the nonconvex optimization problem. Using this method, the control law can be obtained through two steps. The first step consists of determining a local minimum of the objective function. In the second step, a new function is constructed using the local minimum of the objective function found in the first step. The new function is called the filled function; the new constructed function allows us to obtain an initialization near the global minimum. Once this initialization is determined, we can use a local optimization method to determine the global control sequence. The efficiency of...
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Model inversion Iterative Learning Control (ILC) for a class of nonsquare linear time variant/invariant multi-input multi-output (MIMO) systems is considered in this paper. A new ILC algorithm is developed based on σ-right inversion of... more
Model inversion Iterative Learning Control (ILC) for a class of nonsquare linear time variant/invariant multi-input multi-output (MIMO) systems is considered in this paper. A new ILC algorithm is developed based on σ-right inversion of nonsquare learning gain matrices to resolve the matrix inversion problems appeared in the direct model inversion of nonsquare MIMO systems. Furthermore, a sufficient and necessary monotonic convergence condition is established. With rigorous analysis, the proposed ILC scheme guarantees the convergence of the tracking error. To prove the effectiveness and to illustrate the performance of the proposed approach for linear time-invariant (LTI) and time-varying nonsquare systems, two illustrative examples are simulated.
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The multimodel approach offers a very satisfactory results in modelling, diagnose and control of complex systems. In the modelling case, this approach passes by three steps: the determination of the model’s library, the validities... more
The multimodel approach offers a very satisfactory results in modelling, diagnose and control of complex systems. In the modelling case, this approach passes by three steps: the determination of the model’s library, the validities computation and the establishment of the final model. In this context, this paper focuses on the elaboration of a comparative study between three recent methods of validities computation. Thus, it highlight the method that offers the best performances in term of precision. To achieve this goal, we apply, these three methods on two simulation examples in order to compare their performances.
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This paper addresses the static output feedback (SOF) control design problem of Linear Parameter Varying (LPV) affine systems. We aim all along the work to establish robust stability and stabilizability conditions, formulated in terms of... more
This paper addresses the static output feedback (SOF) control design problem of Linear Parameter Varying (LPV) affine systems. We aim all along the work to establish robust stability and stabilizability conditions, formulated in terms of Linear Matrix Inequalities (LMIs). The conditions are parameterized by a real α that allows to bring to feasibility some unfeasible problems. Also the separation between the Lyapunov matrix and the state matrix are done by use of some useful lemmas. This reduces the conservatism engendered and achieves the relaxation of the problem by the addition of slack variables. We prove by numerical examples the contribution of the newly proposed approach for both the analysis and the synthesis of the LPV system.
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The present work focuses on robust predictive control (RPC) of uncertain processes modeled by Controlled Auto Regressive Integrated Moving Average (CARIMA) model. The RPC is based on worst case strategy, e.g., the control law is obtained... more
The present work focuses on robust predictive control (RPC) of uncertain processes modeled by Controlled Auto Regressive Integrated Moving Average (CARIMA) model. The RPC is based on worst case strategy, e.g., the control law is obtained by the resolution of a min-max optimization problem. In fact, the presence of uncertainty on the AR part of the CARIMA model leads to the resolution of a non convex optimization problem. In this work, non conventional methods such as Hopfield neural networks (HNN) and genetic algorithms (GA) are used for the resolution of the non convex optimization problem. The efficiency of the HNN and GA optimizers are tested on benchmark functions. Simulation results are also presented to illustrate the performance of the RPC based on HNN and GA.
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IMACS Multiconference on "Computational Engineering in Systems Applications"(CESA), October 4-6, 2006, Beijing, China. Constrained Nonlinear Multi-objective Predictive Control Faouzi Bouani 1, Kaouther Laabidi 2, Mekki Ksouri3... more
IMACS Multiconference on "Computational Engineering in Systems Applications"(CESA), October 4-6, 2006, Beijing, China. Constrained Nonlinear Multi-objective Predictive Control Faouzi Bouani 1, Kaouther Laabidi 2, Mekki Ksouri3 'National Institute ofApplied Sciences and ...
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ABSTRACT This paper propose a robust nonlinear unknown input observer &quot;this an extension of the Luenberger observer in unknown inputs&quot; based on first order Taylor expansion. The observer is characterized by its... more
ABSTRACT This paper propose a robust nonlinear unknown input observer &quot;this an extension of the Luenberger observer in unknown inputs&quot; based on first order Taylor expansion. The observer is characterized by its simplicity in the mathematical development can also attack a large class of nonlinear systems without go through a canonical transformation. A systematic method for calculating the gain of the observer is presented (11). The necessary and sufficient conditions for the existence of the observer are given. A numerical example is given to illustrate the attractiveness and the simplicity of the new design procedure. I. INTRODUCTION A fault tolerant system is able of maintaining stability and a degree of performance in the presence of disturbances. These systems are generally classified into two approaches: Passive Fault-Tolerant Control Systems and Active Fault-Tolerant Control Systems. In our case we will consider the Passive Fault-Tolerant Control Systems.
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Equipement Faible Coût pour l'Enseignement Scientifique et Technique La réalisation de 140 manipulations est décrite en détail avec des coûts souvent de l'ordre de un dollar. Ces manipulations conviennent parfaitement pour les enfants du... more
Equipement Faible Coût pour l'Enseignement Scientifique et Technique
La réalisation de 140 manipulations est décrite en détail avec des coûts souvent de l'ordre de un dollar.
Ces manipulations conviennent parfaitement pour les enfants du collège ou du lycée.
La réalisation de 140 manipulations est décrite en détail avec des coûts souvent de l'ordre de un dollar.
Ces manipulations conviennent parfaitement pour les enfants du collège ou du lycée.