2023 |
Dabbaghi, Boudour; Hamidi, Faical; Jerbi, Houssem; Aoun, Mohamed Estimating and enlarging the domain of attraction for a nonlinear system with input saturation Conférence 2023. Résumé | Liens | BibTeX | Étiquettes: Actuator saturations, Algebra, Algebraic representations, Computational geometry, Convex hull, Differential algebraic, Differential algebraic representation, Domain of attraction, Input saturation, Nonlinear, Nonlinear systems, Stabilization problems @conference{Dabbaghi2023b, This paper focuses on the stabilization problem of a nonlinear system subject to actuator saturation. Such that the results are based on the differential algebraic representation and use of a convex hull description subject to the saturation effects. The contribution of this work is to estimate enlarging domain of attraction. Therefore, for find the largess domain of attraction, the block matrix-variable will be chosen. Numerical examples are provided to illustrate the efficiency of this new approach. © 2023 IEEE. |
Dabbaghi, B.; Hamidi, F.; Jerbi, H.; Aoun, M. Estimating and enlarging the domain of attraction for a nonlinear system with input saturation Conférence Institute of Electrical and Electronics Engineers Inc., 2023, ISBN: 9798350327564, (cited By 0). Résumé | Liens | BibTeX | Étiquettes: Actuator saturations; Algebraic representations; Convex hull; Differential algebraic; Differential algebraic representation; Domain of attraction; Input saturation; Nonlinear; Stabilization problems, Algebra; Computational geometry, Nonlinear systems @conference{Dabbaghi2023, This paper focuses on the stabilization problem of a nonlinear system subject to actuator saturation. Such that the results are based on the differential algebraic representation and use of a convex hull description subject to the saturation effects. The contribution of this work is to estimate enlarging domain of attraction. Therefore, for find the largess domain of attraction, the block matrix-variable will be chosen. Numerical examples are provided to illustrate the efficiency of this new approach. © 2023 IEEE. |
2022 |
Jerbi, Houssem; Dabbagui, Boudour; Hamidi, Faical; Aoun, Mohamad; Bouazzi, Yassine; Aoun, Sondess Ben Computing the Domain of Attraction using Numerical Techniques Conférence 2022, (Cited by: 0). Résumé | Liens | BibTeX | Étiquettes: Asymptotically stable equilibrium, Basins of attraction, Carleman linearization, Domain of attraction, Iterative methods, Linearization, Lyapunov functions, Lyapunov’s functions, Lypaunov functions, MATLAB, Non-linear modelling, Nonlinear systems, Numerical methods, Numerical techniques, Quadratic lyapunov function, Stability analyze, System stability @conference{Jerbi2022b, Stability analysis of controlled nonlinear systems is a problem of fundamental importance in system engineering. This paper elaborates an explicit numerical technique to maximize a quadratic Lyapunov function for the class of polynomial nonlinear models. Using the computed Lyapunov function an enlarged subsets of the basin of attraction of an asymptotically stable equilibrium can be computed in an iterative analytical way. We mainly use the Carleman linearization technique that converts a nonlinear autonomous system of finite dimension into an equivalent linear infinite dimension one. We implement the sampling technique as a numerical tool allowing the maximization of estimated regions of attraction. An example is given to demonstrate the efficiency of the proposed approach. The numerical study analysis of the designed scheme is led using the Matlab software environment. © 2022 IEEE. |
Jerbi, Houssem; Dabbagui, Boudour; Hamidi, Faical; Aoun, Mohamad; Bouazzi, Yassine; Aoun, Sondess Ben Computing the Domain of Attraction using Numerical Techniques Conférence 2022, (Cited by: 0). Résumé | Liens | BibTeX | Étiquettes: Asymptotically stable equilibrium, Basins of attraction, Carleman linearization, Domain of attraction, Iterative methods, Linearization, Lyapunov functions, Lyapunov’s functions, Lypaunov functions, MATLAB, Non-linear modelling, Nonlinear systems, Numerical methods, Numerical techniques, Quadratic lyapunov function, Stability analyze, System stability @conference{Jerbi2022, Stability analysis of controlled nonlinear systems is a problem of fundamental importance in system engineering. This paper elaborates an explicit numerical technique to maximize a quadratic Lyapunov function for the class of polynomial nonlinear models. Using the computed Lyapunov function an enlarged subsets of the basin of attraction of an asymptotically stable equilibrium can be computed in an iterative analytical way. We mainly use the Carleman linearization technique that converts a nonlinear autonomous system of finite dimension into an equivalent linear infinite dimension one. We implement the sampling technique as a numerical tool allowing the maximization of estimated regions of attraction. An example is given to demonstrate the efficiency of the proposed approach. The numerical study analysis of the designed scheme is led using the Matlab software environment. © 2022 IEEE. |
2003 |
Malti, R.; Aoun, M.; Battaglia, J. -L.; Oustaloup, A.; Madani, K. Fractional Multimodels – Application to Heat Transfer Modeling Conférence vol. 36, no. 16, 2003, (Cited by: 4). Résumé | Liens | BibTeX | Étiquettes: Fractional differentiation, Fractional dynamics, Fractional order, Heat transfer model, Heat transfer performance, Heat transfer process, Identification (control systems), Linear systems, Multi-model, Multi-models, Nonlinear systems, Phase change temperature @conference{Malti20031663b, This paper deals with identification of non linear systems using non linear fractional differentiation multimodels. All sub-models are described by fractional differentiation transfer functions. Performance of the newly proposed class of models is illustrated on a heat transfer process near a phase change temperature. © 2003 International Federation of Automatic Control. |
Malti, R.; Aoun, M.; Battaglia, J. -L.; Oustaloup, A.; Madani, K. Fractional Multimodels – Application to Heat Transfer Modeling Conférence vol. 36, no. 16, 2003, (Cited by: 4). Résumé | Liens | BibTeX | Étiquettes: Fractional differentiation, Fractional dynamics, Fractional order, Heat transfer model, Heat transfer performance, Heat transfer process, Identification (control systems), Linear systems, Multi-model, Multi-models, Nonlinear systems, Phase change temperature @conference{Malti20031663, This paper deals with identification of non linear systems using non linear fractional differentiation multimodels. All sub-models are described by fractional differentiation transfer functions. Performance of the newly proposed class of models is illustrated on a heat transfer process near a phase change temperature. © 2003 International Federation of Automatic Control. |
2002 |
Aoun, Mohamed; Malti, Rachid; Cois, Olivier; Oustaloup, Alain System identification using fractional hammerstein models Conférence vol. 15, no. 1, 2002, (Cited by: 23). Résumé | Liens | BibTeX | Étiquettes: Automation, Continuous time systems, Fractional differentiation, Fractional model, Fractional order, Hammerstein model, Hammerstein-type models, Identification (control systems), Identification method, Linear systems, Non-linear modelling, Nonlinear systems, Riemann-liouville definitions @conference{Aoun2002265b, Identification of continuous-time non-linear systems characterised by fractional order dynamics is studied. The Riemann-Liouville definition of fractional differentiation is used. A new identification method is proposed through the extension of Hammerstein-type models by allowing their linear part to belong to the class of fractional models. Fractional models are compact and so are used here to model complex dynamics with few parameters. Copyright © 2002 IFAC. |
Aoun, Mohamed; Malti, Rachid; Cois, Olivier; Oustaloup, Alain System identification using fractional hammerstein models Conférence vol. 15, no. 1, 2002, (Cited by: 23). Résumé | Liens | BibTeX | Étiquettes: Automation, Continuous time systems, Fractional differentiation, Fractional model, Fractional order, Hammerstein model, Hammerstein-type models, Identification (control systems), Identification method, Linear systems, Non-linear modelling, Nonlinear systems, Riemann-liouville definitions @conference{Aoun2002265, Identification of continuous-time non-linear systems characterised by fractional order dynamics is studied. The Riemann-Liouville definition of fractional differentiation is used. A new identification method is proposed through the extension of Hammerstein-type models by allowing their linear part to belong to the class of fractional models. Fractional models are compact and so are used here to model complex dynamics with few parameters. Copyright © 2002 IFAC. |
Publications
2023 |
Estimating and enlarging the domain of attraction for a nonlinear system with input saturation Conférence 2023. |
Estimating and enlarging the domain of attraction for a nonlinear system with input saturation Conférence Institute of Electrical and Electronics Engineers Inc., 2023, ISBN: 9798350327564, (cited By 0). |
2022 |
Computing the Domain of Attraction using Numerical Techniques Conférence 2022, (Cited by: 0). |
Computing the Domain of Attraction using Numerical Techniques Conférence 2022, (Cited by: 0). |
2003 |
Fractional Multimodels – Application to Heat Transfer Modeling Conférence vol. 36, no. 16, 2003, (Cited by: 4). |
Fractional Multimodels – Application to Heat Transfer Modeling Conférence vol. 36, no. 16, 2003, (Cited by: 4). |
2002 |
System identification using fractional hammerstein models Conférence vol. 15, no. 1, 2002, (Cited by: 23). |
System identification using fractional hammerstein models Conférence vol. 15, no. 1, 2002, (Cited by: 23). |