2019
|
Chairet, Radhia; Salem, Yassine Ben; Aoun, Mohamed Features extraction and land cover classification using Sentinel 2 data Conférence 2019, (Cited by: 6). @conference{Chairet2019497b,
title = {Features extraction and land cover classification using Sentinel 2 data},
author = {Radhia Chairet and Yassine Ben Salem and Mohamed Aoun},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85067108312\&doi=10.1109%2fSTA.2019.8717307\&partnerID=40\&md5=bcfc51b9382e64ab682bed56c2eded1f},
doi = {10.1109/STA.2019.8717307},
year = {2019},
date = {2019-01-01},
journal = {19th International Conference on Sciences and Techniques of Automatic Control and Computer Engineering, STA 2019},
pages = {497 \textendash 500},
abstract = {Since 2015, the Sentinel 2 satellite provides a medium to high spatial resolution (10m-30m) images. For studying the land cover of Gabes area, located in the South- East of Tunisia, we exploited the 10 m bands of this satellite. We have tested the supervised classification with the SVM classifier. The classification is preceded by a segmentation step. The spectral data, the vegetation index and the texture metrics (GLCM) are used for training. The best Overall Accuracy OA (92, 12%) is obtained when all the used features are combined. © 2019 IEEE.},
note = {Cited by: 6},
keywords = {Automation, Classification (of information), Extraction, Features extraction, GLCM, High spatial resolution, Image segmentation, Land cover classification, NDVI, Overall accuracies, Process control, Sentinel 2, supervised classification, Textures},
pubstate = {published},
tppubtype = {conference}
}
Since 2015, the Sentinel 2 satellite provides a medium to high spatial resolution (10m-30m) images. For studying the land cover of Gabes area, located in the South- East of Tunisia, we exploited the 10 m bands of this satellite. We have tested the supervised classification with the SVM classifier. The classification is preceded by a segmentation step. The spectral data, the vegetation index and the texture metrics (GLCM) are used for training. The best Overall Accuracy OA (92, 12%) is obtained when all the used features are combined. © 2019 IEEE. |
Atitallah, Halima; Aribi, Asma; Aoun, Mohamed Tracking Control Design for Fractional Systems with Time Delay Conférence 2019, (Cited by: 0). @conference{Atitallah2019280b,
title = {Tracking Control Design for Fractional Systems with Time Delay},
author = {Halima Atitallah and Asma Aribi and Mohamed Aoun},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85067126817\&doi=10.1109%2fSTA.2019.8717225\&partnerID=40\&md5=8533279ab21aee4982e90554b48e071f},
doi = {10.1109/STA.2019.8717225},
year = {2019},
date = {2019-01-01},
journal = {19th International Conference on Sciences and Techniques of Automatic Control and Computer Engineering, STA 2019},
pages = {280 \textendash 285},
abstract = {Fault tolerant control has been an important subject for many researchers. Nevertheless, there are few works dealing with fractional systems up to now and especially in presence of time delay. In this context, this paper proposes a tracking control design for fractional order system with time delay. The aim is to control the system in order to obtain the same performances of a time delay fractional reference model. The controller parameters are computed in both nominal and faulty functioning in case the state is available and unavailable for measurement. The efficiency of the proposed method is illustrated through a numerical example. © 2019 IEEE.},
note = {Cited by: 0},
keywords = {Automation, Controller parameter, Delay control systems, Fault tolerant control, Fractional systems, Fractional-order systems, Navigation, Numerical methods, Process control, Reference modeling, Time delay, Timing circuits, Tracking controls},
pubstate = {published},
tppubtype = {conference}
}
Fault tolerant control has been an important subject for many researchers. Nevertheless, there are few works dealing with fractional systems up to now and especially in presence of time delay. In this context, this paper proposes a tracking control design for fractional order system with time delay. The aim is to control the system in order to obtain the same performances of a time delay fractional reference model. The controller parameters are computed in both nominal and faulty functioning in case the state is available and unavailable for measurement. The efficiency of the proposed method is illustrated through a numerical example. © 2019 IEEE. |
Chairet, Radhia; Salem, Yassine Ben; Aoun, Mohamed Features extraction and land cover classification using Sentinel 2 data Conférence 2019, (Cited by: 6). @conference{Chairet2019497,
title = {Features extraction and land cover classification using Sentinel 2 data},
author = {Radhia Chairet and Yassine Ben Salem and Mohamed Aoun},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85067108312\&doi=10.1109%2fSTA.2019.8717307\&partnerID=40\&md5=bcfc51b9382e64ab682bed56c2eded1f},
doi = {10.1109/STA.2019.8717307},
year = {2019},
date = {2019-01-01},
journal = {19th International Conference on Sciences and Techniques of Automatic Control and Computer Engineering, STA 2019},
pages = {497 \textendash 500},
abstract = {Since 2015, the Sentinel 2 satellite provides a medium to high spatial resolution (10m-30m) images. For studying the land cover of Gabes area, located in the South- East of Tunisia, we exploited the 10 m bands of this satellite. We have tested the supervised classification with the SVM classifier. The classification is preceded by a segmentation step. The spectral data, the vegetation index and the texture metrics (GLCM) are used for training. The best Overall Accuracy OA (92, 12%) is obtained when all the used features are combined. © 2019 IEEE.},
note = {Cited by: 6},
keywords = {Automation, Classification (of information), Extraction, Features extraction, GLCM, High spatial resolution, Image segmentation, Land cover classification, NDVI, Overall accuracies, Process control, Sentinel 2, supervised classification, Textures},
pubstate = {published},
tppubtype = {conference}
}
Since 2015, the Sentinel 2 satellite provides a medium to high spatial resolution (10m-30m) images. For studying the land cover of Gabes area, located in the South- East of Tunisia, we exploited the 10 m bands of this satellite. We have tested the supervised classification with the SVM classifier. The classification is preceded by a segmentation step. The spectral data, the vegetation index and the texture metrics (GLCM) are used for training. The best Overall Accuracy OA (92, 12%) is obtained when all the used features are combined. © 2019 IEEE. |
Atitallah, Halima; Aribi, Asma; Aoun, Mohamed Tracking Control Design for Fractional Systems with Time Delay Conférence 2019, (Cited by: 0). @conference{Atitallah2019280,
title = {Tracking Control Design for Fractional Systems with Time Delay},
author = {Halima Atitallah and Asma Aribi and Mohamed Aoun},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85067126817\&doi=10.1109%2fSTA.2019.8717225\&partnerID=40\&md5=8533279ab21aee4982e90554b48e071f},
doi = {10.1109/STA.2019.8717225},
year = {2019},
date = {2019-01-01},
journal = {19th International Conference on Sciences and Techniques of Automatic Control and Computer Engineering, STA 2019},
pages = {280 \textendash 285},
abstract = {Fault tolerant control has been an important subject for many researchers. Nevertheless, there are few works dealing with fractional systems up to now and especially in presence of time delay. In this context, this paper proposes a tracking control design for fractional order system with time delay. The aim is to control the system in order to obtain the same performances of a time delay fractional reference model. The controller parameters are computed in both nominal and faulty functioning in case the state is available and unavailable for measurement. The efficiency of the proposed method is illustrated through a numerical example. © 2019 IEEE.},
note = {Cited by: 0},
keywords = {Automation, Controller parameter, Delay control systems, Fault tolerant control, Fractional systems, Fractional-order systems, Navigation, Numerical methods, Process control, Reference modeling, Time delay, Timing circuits, Tracking controls},
pubstate = {published},
tppubtype = {conference}
}
Fault tolerant control has been an important subject for many researchers. Nevertheless, there are few works dealing with fractional systems up to now and especially in presence of time delay. In this context, this paper proposes a tracking control design for fractional order system with time delay. The aim is to control the system in order to obtain the same performances of a time delay fractional reference model. The controller parameters are computed in both nominal and faulty functioning in case the state is available and unavailable for measurement. The efficiency of the proposed method is illustrated through a numerical example. © 2019 IEEE. |
2017
|
Atitallah, Halima; Aribi, Asma; Aoun, Mohamed Diagnosis of time-delay fractional systems Conférence 2017, (Cited by: 3). @conference{Atitallah2017284b,
title = {Diagnosis of time-delay fractional systems},
author = {Halima Atitallah and Asma Aribi and Mohamed Aoun},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85024400530\&doi=10.1109%2fSTA.2016.7952042\&partnerID=40\&md5=7df0719cec19ecdfbff3cbb2ec3bfeda},
doi = {10.1109/STA.2016.7952042},
year = {2017},
date = {2017-01-01},
journal = {2016 17th International Conference on Sciences and Techniques of Automatic Control and Computer Engineering, STA 2016 - Proceedings},
pages = {284 \textendash 292},
abstract = {In this paper, a model-based diagnosis method, called Luenberger diagnosis observer, recently developed for fractional order systems, is extended for time-delay fractional systems. A sufficient convergence condition of the fault indicator using Bilinear Matrix Inequalities is detailed. A numerical example illustrating the method's validity in detecting faults is finally presented. © 2016 IEEE.},
note = {Cited by: 3},
keywords = {Automation, Bilinear matrix inequality, Convergence conditions, Convergence of numerical methods, Delay control systems, Diagnosis, Fault detection, Fault indicators, Fractional systems, Fractional-order systems, Luenberger observers, Model based diagnosis, Numerical methods, Process control, residual, Time delay},
pubstate = {published},
tppubtype = {conference}
}
In this paper, a model-based diagnosis method, called Luenberger diagnosis observer, recently developed for fractional order systems, is extended for time-delay fractional systems. A sufficient convergence condition of the fault indicator using Bilinear Matrix Inequalities is detailed. A numerical example illustrating the method’s validity in detecting faults is finally presented. © 2016 IEEE. |
Yakoub, Z.; Chetoui, M.; Amairi, M.; Aoun, M. Model-based fractional order controller design Conférence vol. 50, no. 1, 2017, (Cited by: 3; All Open Access, Bronze Open Access). @conference{Yakoub201710431b,
title = {Model-based fractional order controller design},
author = {Z. Yakoub and M. Chetoui and M. Amairi and M. Aoun},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85031827269\&doi=10.1016%2fj.ifacol.2017.08.1971\&partnerID=40\&md5=c84f02810425251e2e6444d4c36ec8dd},
doi = {10.1016/j.ifacol.2017.08.1971},
year = {2017},
date = {2017-01-01},
journal = {IFAC-PapersOnLine},
volume = {50},
number = {1},
pages = {10431 \textendash 10436},
abstract = {This paper deals with model-based fractional order controller design. The objective is identification for controller design in order to achieve the desired closed-loop performances. Firstly, the fractional order closed-loop bias-eliminated least squares method is used to identify the process model. Then, based on the numerical optimization of a frequency-domain criterion, the fractional controller is designed. If the proposed algorithm detects any changes in the process parameters, the controller is updated to keep the same performances. A numerical example is presented to show the efficiency of the proposed scheme. © 2017},
note = {Cited by: 3; All Open Access, Bronze Open Access},
keywords = {Bias elimination, Closed loops, Controllers, Fractional differentiation, Frequency domain analysis, Identification for control, Least squares approximations, Optimization, Process control, Recursive least square (RLS)},
pubstate = {published},
tppubtype = {conference}
}
This paper deals with model-based fractional order controller design. The objective is identification for controller design in order to achieve the desired closed-loop performances. Firstly, the fractional order closed-loop bias-eliminated least squares method is used to identify the process model. Then, based on the numerical optimization of a frequency-domain criterion, the fractional controller is designed. If the proposed algorithm detects any changes in the process parameters, the controller is updated to keep the same performances. A numerical example is presented to show the efficiency of the proposed scheme. © 2017 |
Yakoub, Z.; Chetoui, M.; Amairi, M.; Aoun, M. A comparison between the direct and the indirect fractional order closed-loop bias eliminated least squares method Conférence 2017, (Cited by: 0). @conference{Yakoub2017271b,
title = {A comparison between the direct and the indirect fractional order closed-loop bias eliminated least squares method},
author = {Z. Yakoub and M. Chetoui and M. Amairi and M. Aoun},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85024378403\&doi=10.1109%2fSTA.2016.7951978\&partnerID=40\&md5=f96317e305a1fb9879331639139ecc89},
doi = {10.1109/STA.2016.7951978},
year = {2017},
date = {2017-01-01},
journal = {2016 17th International Conference on Sciences and Techniques of Automatic Control and Computer Engineering, STA 2016 - Proceedings},
pages = {271 \textendash 282},
abstract = {This paper deals with the fractional closed-loop system identification. A comparison between the direct and the indirect approach is processed. The fractional order bias eliminated least squares method is used to identify the fractional closed-loop transfer function. This method is founded on the ordinary least squares method and the state variable filter. A numerical example is treated to show the efficiency of each approach and discuss results. © 2016 IEEE.},
note = {Cited by: 0},
keywords = {Automation, Closed loops, Direct approach, Fractional differentiation, Identification (control systems), indirect approach, Least Square, Least squares approximations, Process control},
pubstate = {published},
tppubtype = {conference}
}
This paper deals with the fractional closed-loop system identification. A comparison between the direct and the indirect approach is processed. The fractional order bias eliminated least squares method is used to identify the fractional closed-loop transfer function. This method is founded on the ordinary least squares method and the state variable filter. A numerical example is treated to show the efficiency of each approach and discuss results. © 2016 IEEE. |
Achnib, Asma; Chetoui, Manel; Lanusse, Patrick; Aoun, Mohamed A comparative study of the output and the state feedback predictive control Conférence 2017, (Cited by: 1). @conference{Achnib201734b,
title = {A comparative study of the output and the state feedback predictive control},
author = {Asma Achnib and Manel Chetoui and Patrick Lanusse and Mohamed Aoun},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85024379902\&doi=10.1109%2fSTA.2016.7952029\&partnerID=40\&md5=779b88cd1e20f8d1c6c3614eb10555e4},
doi = {10.1109/STA.2016.7952029},
year = {2017},
date = {2017-01-01},
journal = {2016 17th International Conference on Sciences and Techniques of Automatic Control and Computer Engineering, STA 2016 - Proceedings},
pages = {34 \textendash 41},
abstract = {In this paper the effectiveness of predictive control in the problems of tracking and control is studied. The principle and the implementation of the algorithm of this control are presented. In this work, two approaches using different system models are developed: The output feedback and the state feedback predictive control. The performances and the robustness of both approaches are assessed with the help of two examples. © 2016 IEEE.},
note = {Cited by: 1},
keywords = {Automation, Comparative studies, Feedback, Model predictive control, Output feedback, Predictive control, Process control, Robustness (control systems), State feedback, State feedback predictive control, System models},
pubstate = {published},
tppubtype = {conference}
}
In this paper the effectiveness of predictive control in the problems of tracking and control is studied. The principle and the implementation of the algorithm of this control are presented. In this work, two approaches using different system models are developed: The output feedback and the state feedback predictive control. The performances and the robustness of both approaches are assessed with the help of two examples. © 2016 IEEE. |
Atitallah, Halima; Aribi, Asma; Aoun, Mohamed Diagnosis of time-delay fractional systems Conférence 2017, (Cited by: 3). @conference{Atitallah2017284,
title = {Diagnosis of time-delay fractional systems},
author = {Halima Atitallah and Asma Aribi and Mohamed Aoun},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85024400530\&doi=10.1109%2fSTA.2016.7952042\&partnerID=40\&md5=7df0719cec19ecdfbff3cbb2ec3bfeda},
doi = {10.1109/STA.2016.7952042},
year = {2017},
date = {2017-01-01},
journal = {2016 17th International Conference on Sciences and Techniques of Automatic Control and Computer Engineering, STA 2016 - Proceedings},
pages = {284 \textendash 292},
abstract = {In this paper, a model-based diagnosis method, called Luenberger diagnosis observer, recently developed for fractional order systems, is extended for time-delay fractional systems. A sufficient convergence condition of the fault indicator using Bilinear Matrix Inequalities is detailed. A numerical example illustrating the method's validity in detecting faults is finally presented. © 2016 IEEE.},
note = {Cited by: 3},
keywords = {Automation, Bilinear matrix inequality, Convergence conditions, Convergence of numerical methods, Delay control systems, Diagnosis, Fault detection, Fault indicators, Fractional systems, Fractional-order systems, Luenberger observers, Model based diagnosis, Numerical methods, Process control, residual, Time delay},
pubstate = {published},
tppubtype = {conference}
}
In this paper, a model-based diagnosis method, called Luenberger diagnosis observer, recently developed for fractional order systems, is extended for time-delay fractional systems. A sufficient convergence condition of the fault indicator using Bilinear Matrix Inequalities is detailed. A numerical example illustrating the method’s validity in detecting faults is finally presented. © 2016 IEEE. |
Achnib, Asma; Chetoui, Manel; Lanusse, Patrick; Aoun, Mohamed A comparative study of the output and the state feedback predictive control Conférence 2017, (Cited by: 1). @conference{Achnib201734,
title = {A comparative study of the output and the state feedback predictive control},
author = {Asma Achnib and Manel Chetoui and Patrick Lanusse and Mohamed Aoun},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85024379902\&doi=10.1109%2fSTA.2016.7952029\&partnerID=40\&md5=779b88cd1e20f8d1c6c3614eb10555e4},
doi = {10.1109/STA.2016.7952029},
year = {2017},
date = {2017-01-01},
journal = {2016 17th International Conference on Sciences and Techniques of Automatic Control and Computer Engineering, STA 2016 - Proceedings},
pages = {34 \textendash 41},
abstract = {In this paper the effectiveness of predictive control in the problems of tracking and control is studied. The principle and the implementation of the algorithm of this control are presented. In this work, two approaches using different system models are developed: The output feedback and the state feedback predictive control. The performances and the robustness of both approaches are assessed with the help of two examples. © 2016 IEEE.},
note = {Cited by: 1},
keywords = {Automation, Comparative studies, Feedback, Model predictive control, Output feedback, Predictive control, Process control, Robustness (control systems), State feedback, State feedback predictive control, System models},
pubstate = {published},
tppubtype = {conference}
}
In this paper the effectiveness of predictive control in the problems of tracking and control is studied. The principle and the implementation of the algorithm of this control are presented. In this work, two approaches using different system models are developed: The output feedback and the state feedback predictive control. The performances and the robustness of both approaches are assessed with the help of two examples. © 2016 IEEE. |
2016
|
Gasmi, N.; Thabet, A.; Boutayeb, M.; Aoun, M. Ob_server design fo a class of nonlinear discrete time systems Conférence 2016, (Cited by: 8). @conference{Gasmi2016799b,
title = {Ob_server design fo a class of nonlinear discrete time systems},
author = {N. Gasmi and A. Thabet and M. Boutayeb and M. Aoun},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84979691968\&doi=10.1109%2fSTA.2015.7505084\&partnerID=40\&md5=c0a9f25a510a1303bdee32a74f93b688},
doi = {10.1109/STA.2015.7505084},
year = {2016},
date = {2016-01-01},
journal = {16th International Conference on Sciences and Techniques of Automatic Control and Computer Engineering, STA 2015},
pages = {799 \textendash 804},
abstract = {This paper focuses in the observer design for non-linear discrete time systems. The main objective is the application of the Differential Mean Value Theorem (DMVT) to transform the nonlinear dynamics error to a linear parameter varying (LPV) system. This aims to introduce a less restrictive condition on the nonlinear functions. To ensure asymptotic stability, sufficient conditions are formulated in Linear Matrix Inequalities (LMIs). For comparison, an observer based on the utilization of the One-Sided Lipschitz condition is introduced. High performances are shown through numerical simulation. © 2015 IEEE.},
note = {Cited by: 8},
keywords = {Asymptotic stability, Automation, Differential mean value theorems, Digital control systems, Discrete time control systems, Linear matrix inequalities, Linear parameter varying systems, Mathematical transformations, Nonlinear discrete-time systems, Nonlinear functions, Observer design, Observer-based, One-sided Lipschitz condition, Process control, Restrictive conditions},
pubstate = {published},
tppubtype = {conference}
}
This paper focuses in the observer design for non-linear discrete time systems. The main objective is the application of the Differential Mean Value Theorem (DMVT) to transform the nonlinear dynamics error to a linear parameter varying (LPV) system. This aims to introduce a less restrictive condition on the nonlinear functions. To ensure asymptotic stability, sufficient conditions are formulated in Linear Matrix Inequalities (LMIs). For comparison, an observer based on the utilization of the One-Sided Lipschitz condition is introduced. High performances are shown through numerical simulation. © 2015 IEEE. |
Frej, G. Bel Haj; Thabet, A.; Boutayeb, M.; Aoun, M. Decentralized observers of a large class of nonlinear interconnected systems Conférence 2016, (Cited by: 1). @conference{BelHajFrej2016905b,
title = {Decentralized observers of a large class of nonlinear interconnected systems},
author = {G. Bel Haj Frej and A. Thabet and M. Boutayeb and M. Aoun},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84979657055\&doi=10.1109%2fSTA.2015.7505091\&partnerID=40\&md5=51044233aec05c7e771789c2852c0f99},
doi = {10.1109/STA.2015.7505091},
year = {2016},
date = {2016-01-01},
journal = {16th International Conference on Sciences and Techniques of Automatic Control and Computer Engineering, STA 2015},
pages = {905 \textendash 910},
abstract = {The objective of this paper is the synthesis of decentralized state observers for large class of nonlinear interconnected systems. The procedure uses the Differential Mean Value Theorem (DMVT) to simplify the design of estimation and control matrices gains. A general condition on the non linear time-varying interconnections functions is introduced. To ensure asymptotic stability, sufficient conditions are formulated in Linear Matrix Inequalities (LMIs). High performances are shown through numerical simulation. © 2015 IEEE.},
note = {Cited by: 1},
keywords = {Asymptotic stability, Automation, Control matrices, Decentralized state observers, Differential mean value theorems, Linear matrix inequalities, Matrix algebra, Non linear, Nonlinear interconnected systems, Process control},
pubstate = {published},
tppubtype = {conference}
}
The objective of this paper is the synthesis of decentralized state observers for large class of nonlinear interconnected systems. The procedure uses the Differential Mean Value Theorem (DMVT) to simplify the design of estimation and control matrices gains. A general condition on the non linear time-varying interconnections functions is introduced. To ensure asymptotic stability, sufficient conditions are formulated in Linear Matrix Inequalities (LMIs). High performances are shown through numerical simulation. © 2015 IEEE. |
Chouki, Rihab; Aribi, Asma; Aoun, Mohamed; Abdelkarim, Mohamed N. Additive fault tolerant control for fractional order model systems Conférence 2016, (Cited by: 6). @conference{Chouki2016340b,
title = {Additive fault tolerant control for fractional order model systems},
author = {Rihab Chouki and Asma Aribi and Mohamed Aoun and Mohamed N. Abdelkarim},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84979671278\&doi=10.1109%2fSTA.2015.7505227\&partnerID=40\&md5=6704d86caedf5e247753ba423958421a},
doi = {10.1109/STA.2015.7505227},
year = {2016},
date = {2016-01-01},
journal = {16th International Conference on Sciences and Techniques of Automatic Control and Computer Engineering, STA 2015},
pages = {340 \textendash 345},
abstract = {The additive fault tolerant control (FTC) for the fractional order model is presented, in this paper. Hence, two steps are compulsory in order to design the additive control. The first one being the estimation of the sensor fault amplitude which is realized by using the fractional Luenberger observer and the second one consists in generating the additive fault tolerant control law and then sum it to the nominal control of the fractional order model. © 2015 IEEE.},
note = {Cited by: 6},
keywords = {Additive faults, Automation, Fault tolerance, Fractional order models, Luenberger observers, Process control, Sensor fault},
pubstate = {published},
tppubtype = {conference}
}
The additive fault tolerant control (FTC) for the fractional order model is presented, in this paper. Hence, two steps are compulsory in order to design the additive control. The first one being the estimation of the sensor fault amplitude which is realized by using the fractional Luenberger observer and the second one consists in generating the additive fault tolerant control law and then sum it to the nominal control of the fractional order model. © 2015 IEEE. |
Gasmi, N.; Thabet, A.; Boutayeb, M.; Aoun, M. Ob_server design fo a class of nonlinear discrete time systems Conférence 2016, (Cited by: 8). @conference{Gasmi2016799,
title = {Ob_server design fo a class of nonlinear discrete time systems},
author = {N. Gasmi and A. Thabet and M. Boutayeb and M. Aoun},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84979691968\&doi=10.1109%2fSTA.2015.7505084\&partnerID=40\&md5=c0a9f25a510a1303bdee32a74f93b688},
doi = {10.1109/STA.2015.7505084},
year = {2016},
date = {2016-01-01},
journal = {16th International Conference on Sciences and Techniques of Automatic Control and Computer Engineering, STA 2015},
pages = {799 \textendash 804},
abstract = {This paper focuses in the observer design for non-linear discrete time systems. The main objective is the application of the Differential Mean Value Theorem (DMVT) to transform the nonlinear dynamics error to a linear parameter varying (LPV) system. This aims to introduce a less restrictive condition on the nonlinear functions. To ensure asymptotic stability, sufficient conditions are formulated in Linear Matrix Inequalities (LMIs). For comparison, an observer based on the utilization of the One-Sided Lipschitz condition is introduced. High performances are shown through numerical simulation. © 2015 IEEE.},
note = {Cited by: 8},
keywords = {Asymptotic stability, Automation, Differential mean value theorems, Digital control systems, Discrete time control systems, Linear matrix inequalities, Linear parameter varying systems, Mathematical transformations, Nonlinear discrete-time systems, Nonlinear functions, Observer design, Observer-based, One-sided Lipschitz condition, Process control, Restrictive conditions},
pubstate = {published},
tppubtype = {conference}
}
This paper focuses in the observer design for non-linear discrete time systems. The main objective is the application of the Differential Mean Value Theorem (DMVT) to transform the nonlinear dynamics error to a linear parameter varying (LPV) system. This aims to introduce a less restrictive condition on the nonlinear functions. To ensure asymptotic stability, sufficient conditions are formulated in Linear Matrix Inequalities (LMIs). For comparison, an observer based on the utilization of the One-Sided Lipschitz condition is introduced. High performances are shown through numerical simulation. © 2015 IEEE. |
Frej, G. Bel Haj; Thabet, A.; Boutayeb, M.; Aoun, M. Decentralized observers of a large class of nonlinear interconnected systems Conférence 2016, (Cited by: 1). @conference{BelHajFrej2016905c,
title = {Decentralized observers of a large class of nonlinear interconnected systems},
author = {G. Bel Haj Frej and A. Thabet and M. Boutayeb and M. Aoun},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84979657055\&doi=10.1109%2fSTA.2015.7505091\&partnerID=40\&md5=51044233aec05c7e771789c2852c0f99},
doi = {10.1109/STA.2015.7505091},
year = {2016},
date = {2016-01-01},
journal = {16th International Conference on Sciences and Techniques of Automatic Control and Computer Engineering, STA 2015},
pages = {905 \textendash 910},
abstract = {The objective of this paper is the synthesis of decentralized state observers for large class of nonlinear interconnected systems. The procedure uses the Differential Mean Value Theorem (DMVT) to simplify the design of estimation and control matrices gains. A general condition on the non linear time-varying interconnections functions is introduced. To ensure asymptotic stability, sufficient conditions are formulated in Linear Matrix Inequalities (LMIs). High performances are shown through numerical simulation. © 2015 IEEE.},
note = {Cited by: 1},
keywords = {Asymptotic stability, Automation, Control matrices, Decentralized state observers, Differential mean value theorems, Linear matrix inequalities, Matrix algebra, Non linear, Nonlinear interconnected systems, Process control},
pubstate = {published},
tppubtype = {conference}
}
The objective of this paper is the synthesis of decentralized state observers for large class of nonlinear interconnected systems. The procedure uses the Differential Mean Value Theorem (DMVT) to simplify the design of estimation and control matrices gains. A general condition on the non linear time-varying interconnections functions is introduced. To ensure asymptotic stability, sufficient conditions are formulated in Linear Matrix Inequalities (LMIs). High performances are shown through numerical simulation. © 2015 IEEE. |
Chouki, Rihab; Aribi, Asma; Aoun, Mohamed; Abdelkarim, Mohamed N. Additive fault tolerant control for fractional order model systems Conférence 2016, (Cited by: 6). @conference{Chouki2016340,
title = {Additive fault tolerant control for fractional order model systems},
author = {Rihab Chouki and Asma Aribi and Mohamed Aoun and Mohamed N. Abdelkarim},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84979671278\&doi=10.1109%2fSTA.2015.7505227\&partnerID=40\&md5=6704d86caedf5e247753ba423958421a},
doi = {10.1109/STA.2015.7505227},
year = {2016},
date = {2016-01-01},
journal = {16th International Conference on Sciences and Techniques of Automatic Control and Computer Engineering, STA 2015},
pages = {340 \textendash 345},
abstract = {The additive fault tolerant control (FTC) for the fractional order model is presented, in this paper. Hence, two steps are compulsory in order to design the additive control. The first one being the estimation of the sensor fault amplitude which is realized by using the fractional Luenberger observer and the second one consists in generating the additive fault tolerant control law and then sum it to the nominal control of the fractional order model. © 2015 IEEE.},
note = {Cited by: 6},
keywords = {Additive faults, Automation, Fault tolerance, Fractional order models, Luenberger observers, Process control, Sensor fault},
pubstate = {published},
tppubtype = {conference}
}
The additive fault tolerant control (FTC) for the fractional order model is presented, in this paper. Hence, two steps are compulsory in order to design the additive control. The first one being the estimation of the sensor fault amplitude which is realized by using the fractional Luenberger observer and the second one consists in generating the additive fault tolerant control law and then sum it to the nominal control of the fractional order model. © 2015 IEEE. |
