Publications

@conference{Khalil2022,

title = {Enhancement of Finite Set Model Predictive Control for Direct Matrix Converter fed DFIG-Wind Energy Conversion System},

author = {E. M. Khalil and N. Mohamed and H. Mohamed and S. Lassad},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85136095205\&doi=10.1109%2fENERGYCON53164.2022.9830152\&partnerID=40\&md5=f77616f4f25ca0d3cf212985ece97579},

doi = {10.1109/ENERGYCON53164.2022.9830152},

isbn = {9781665479820},

year  = {2022},

date = {2022-01-01},

journal = {ENERGYCON 2022 - 2022 IEEE 7th International Energy Conference, Proceedings},

publisher = {Institute of Electrical and Electronics Engineers Inc.},

abstract = {This paper deals with the study of finite set model predictive current control (FS-MPC) for doubly fed induction generator (DFIG) derived by direct matrix converter (DMC). The FS-MPC has proven it effectiveness in many power applications. This control technique possess a small steady state error in different operating conditions, a high sensitivity and fast dynamic response, and it can be applied in both linear and nonlinear systems. In the other hand, the frailty of this method consists of parameter mismatches which affect mathematical model. To overcome this problem, we propose to add past errors of rotor current to the cost function and adjust the weighting factors of the cost function with fuzzy decision making approach (FDM). The MATLAB/Simulink tool is used to evaluate the performance of this system in various scenarios. © 2022 IEEE.},

note = {cited By 1},

keywords = {Asynchronous generators; Cost functions; Decision making; Electric fault currents; Electric machine theory; Energy conversion; Matrix converters; Predictive control systems; Set theory; Wind power, Direct matrix converter; Doubly fed induction generators; Doubly feed induction generator; Finite set; Finite set model predictive control; Fuzzy Decision making; Model predictive; Model-predictive control; Set models, Model predictive control},

pubstate = {published},

tppubtype = {conference}

}

@conference{Walid2018138b,

title = {Robust internal model controller for quadrotor UAV},

author = {Mizouri Walid and Najar Slaheddine and Aoun Mohamed and Bouabdallah Lamjed},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85050009476\&doi=10.1109%2fASET.2018.8379848\&partnerID=40\&md5=d90913214fa716cddebe22721d3a1de3},

doi = {10.1109/ASET.2018.8379848},

year  = {2018},

date = {2018-01-01},

journal = {2018 International Conference on Advanced Systems and Electric Technologies, IC_ASET 2018},

pages = {138 \textendash 143},

abstract = {Modeling and control of Unmanned Aerial Vehicle (UAV) such quadrotor becomes more attractive to researchers due to the UAV applications and technological advancements. Therefore the quadrotor system can probably affected by model uncertainties, noises and external disturbances. In this work, a quadrotor dynamic model is presented and a new control approach based on Internal Model Control strategy is designed to stabilize the 6 DoF quadrotor UAV under model uncertainties, noises and external disturbances, provided by numerical simulations. © 2018 IEEE.},

note = {Cited by: 4},

keywords = {Aircraft control, Antennas, Disturbance, External disturbances, Internal model control, Internal model controllers, Model predictive control, Models, Quad-rotor UAV, Quadrotor dynamic modeling, Technological advancement, Uncertainty, Uncertainty analysis, Unmanned aerial vehicles (UAV)},

pubstate = {published},

tppubtype = {conference}

}

@conference{Walid2018138,

title = {Robust internal model controller for quadrotor UAV},

author = {Mizouri Walid and Najar Slaheddine and Aoun Mohamed and Bouabdallah Lamjed},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85050009476\&doi=10.1109%2fASET.2018.8379848\&partnerID=40\&md5=d90913214fa716cddebe22721d3a1de3},

doi = {10.1109/ASET.2018.8379848},

year  = {2018},

date = {2018-01-01},

journal = {2018 International Conference on Advanced Systems and Electric Technologies, IC_ASET 2018},

pages = {138 \textendash 143},

abstract = {Modeling and control of Unmanned Aerial Vehicle (UAV) such quadrotor becomes more attractive to researchers due to the UAV applications and technological advancements. Therefore the quadrotor system can probably affected by model uncertainties, noises and external disturbances. In this work, a quadrotor dynamic model is presented and a new control approach based on Internal Model Control strategy is designed to stabilize the 6 DoF quadrotor UAV under model uncertainties, noises and external disturbances, provided by numerical simulations. © 2018 IEEE.},

note = {Cited by: 4},

keywords = {Aircraft control, Antennas, Disturbance, External disturbances, Internal model control, Internal model controllers, Model predictive control, Models, Quad-rotor UAV, Quadrotor dynamic modeling, Technological advancement, Uncertainty, Uncertainty analysis, Unmanned aerial vehicles (UAV)},

pubstate = {published},

tppubtype = {conference}

}

@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}

}

@conference{Boussaid20092088,

title = {FTC approach based on predictive governor},

author = {B. Boussaid and C. Aubrun and M. Koni Ben Gayed and M. Naceur Abdelkrim},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-77950395629\&doi=10.1109%2fICCA.2009.5410345\&partnerID=40\&md5=0639b17587fcfbd646962be9381cc39f},

doi = {10.1109/ICCA.2009.5410345},

isbn = {9781424447060},

year  = {2009},

date = {2009-01-01},

journal = {2009 IEEE International Conference on Control and Automation, ICCA 2009},

pages = {2088-2093},

abstract = {In this paper, a new approach of reconfigured system is proposed to improve the performance of an active fault tolerant control system. The method is based on model predictive control and reference trajectory adjustment techniques. When an actuator fault occurs in the system, the controller balances to the nearest degraded reference trajectory. A constraint set and cost function are established to avoid actuators saturation and reduce control energy spent in closed loop dynamics. The effectiveness of the proposed method has been illustrated using a hydrothermal system subject to actuator failure and constraints on the actuator dynamic ranges. Satisfactory results have been obtained. ©2009 IEEE.},

note = {cited By 2},

keywords = {Active fault tolerant control systems; Actuator dynamics; Actuator failures; Actuator fault; Closed loop dynamic; Constraint set; Control energy; Fault tolerant control systems; Hydrothermal system; New approaches; Reconfigurable control; Reference trajectories, Actuators; Computation theory; Cost reduction; Fault tolerant computer systems; Navigation; Predictive control systems; Trajectories, Model predictive control},

pubstate = {published},

tppubtype = {conference}

}