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Articles by K.E. Ali
Total Records ( 4 ) for K.E. Ali
  O. Asseu , T.R. Ori , K.E. Ali , Z. Yeo , S. Ouattara and X. Lin-Shi
  The aim of this study is to present a high dynamic current control and speed estimation strategy for Permanent Magnet Synchronous Motor (PMSM) drives without a speed transducer. The strategy is based on the exact linearization methodology and Extended Sliding Mode Observer (ESMO) algorithm. The performances of the proposed control strategy are analysed by simulations for a 1.6 kW PMSM. The obtained results show the effectiveness of the proposed robust current control approach and speed observation algorithm under load torque and stator resistance variation.
  K.E. Ali , K.Y. Kouadio , E.-P. Zahiri , A. Aman , A.P. Assamoi and B. Bourles
  The Gulf of Guinea (GG) is an area where a seasonal upwelling takes place, along the equator and its northern coasts between Benin and Cote d’Ivoire. The coastal upwelling has a real impact on the local yet documented biological resources. However, climatic impact studies of this seasonal upwelling are paradoxically very rare and disseminated and this impact is still little known, especially on the potential part played by the upwelling onset on the regional precipitation in early boreal summer. This study shows that coastal precipitations of the July-September period are correlated by both the coastal and equatorial sea-surface temperatures (SSTS). This correlation results in a decrease or a rise of rainfall when the SSTs are abnormally cold or warm respectively. The coastal areas that are more subject to coastal and equatorial SSTs influence are located around the Cape Three Points, where the coastal upwelling exhibits the maximum of amplitude.
  O. Asseu , Z. Yeo , M. Koffi , M.A. Kouacou and K.E. Ali
  This study proposes a novel method to achieve good performance for rotor time constant and flux estimation in induction motor sensorless control, using a reduced order Extended Kalman Filter (EKF) instead of a full-order EKF. This new algorithm uses a reduced order state-space model that is discretized in a particular and innovative way proposed in this study. With this model structure, only the rotor flux components are estimated while the full order EKF also estimates stator current components. Thus, as compared with the full order EKF, this new approach strongly reduces the execution time of the observation and simplifies the tuning of covariance matrices, since, the number of elements to be adjusted is reduced. The satisfying simulations results on Matlab-Simulink environment for a 1.8 kW induction motor, demonstrate the good performance and stability of the proposed reduced order EKF algorithm against parameter variation, modeling uncertainty, measurement and system noises.
  O. Asseu , S. Ouattara , K.E. Ali , Z. Yeo and M. Koffi
  This study uses a robust input-output linearization via feedback control in order to assure a good dynamic performance, stability and a decoupling of the stator currents for an induction motor in a field-oriented (d, q) coordinate. However, this control requires the knowledge of certain variables (rotor flux, torque) that are difficult to access or simply impossible to measure and also the rotor time constant variation can induce a performance degradation of the system. Thus, a fifth-order Discrete-time extended Kalman filter approach is proposed for on-line estimation of rotor flux, currents, rotor time constant and torque in an induction motor. The interesting simulations and experimental results obtained on a testing bench for a 5.5 kW induction motor permit to validate the effectiveness and good performance of the proposed nonlinear control and extended Kalman filter algorithm in the presence of parameter variation, modeling uncertainty and measurement noise.
 
 
 
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