In this paper, an adaptive tracking controller for a piezo-actuated stage is designed considering the LUGRE model. The adaptation algorithm of the parameterized hysteretic function is used to achieve a displacement-tracking objective under the mechanical parameters uncertainties. The Lyapunov theory is used to derive an adaptive law for the system stability. The effectiveness of the proposed controller is validated considering real-time simulation. The validation results of the proposed controller presents good performances and robustness under an external load-disturbance and parameter uncertainties.

In this paper, an adaptive tracking controller for a piezo-actuated stage is designed considering the LUGRE model. The adaptation algorithm of the parameterized hysteretic function is used to achieve a displacement-tracking objective under the mechanical parameters uncertainties. The Lyapunov theory is used to derive an adaptive law for the system stability. The effectiveness of the proposed controller is validated considering real-time simulation. The validation results of the proposed controller presents good performances and robustness under an external load-disturbance and parameter uncertainties.

In this paper, an adaptive tracking controller for a piezo-actuated stage is designed considering the LUGRE model. The adaptation algorithm of the parameterized hysteretic function is used to achieve a displacement-tracking objective under the mechanical parameters uncertainties. The Lyapunov theory is used to derive an adaptive law for the system stability. The effectiveness of the proposed controller is validated considering real-time simulation. The validation results of the proposed controller presents good performances and robustness under an external load-disturbance and parameter uncertainties.

In this paper, an adaptive tracking controller for a piezo-actuated stage is designed considering the LUGRE model. The adaptation algorithm of the parameterized hysteretic function is used to achieve a displacement-tracking objective under the mechanical parameters uncertainties. The Lyapunov theory is used to derive an adaptive law for the system stability. The effectiveness of the proposed controller is validated considering real-time simulation. The validation results of the proposed controller presents good performances and robustness under an external load-disturbance and parameter uncertainties.

A robust nonlinear controller based on an improved feedback linearization technique with state observer is developed for a class of nonlinear systems with uncertainties and external disturbances. First, by combining classical feedback linearization approach with a discontinuous control and a fuzzy logic system, we design and study a robust controller for uncertain nonlinear systems. Second, we propose an optimized extended Kalman filter (EKF) for the observation of the states. The parameters to be optimized are the covariance matrices Q and R, which play an important role in the EKF performances. The particle swarm optimization algorithm insures this optimization. Lyapunov synthesis approach is used to prove the stability of the whole control loop. The proposed approach is applied on a two-link robot system under Matlab environment. Simulation results have confirmed the effectiveness of the proposed approach against uncertainties and external disturbances; and exhibited a more superior performance than the non-improved control actions.

A robust nonlinear controller based on an improved feedback linearization technique with state observer is developed for a class of nonlinear systems with uncertainties and external disturbances. First, by combining classical feedback linearization approach with a discontinuous control and a fuzzy logic system, we design and study a robust controller for uncertain nonlinear systems. Second, we propose an optimized extended Kalman filter (EKF) for the observation of the states. The parameters to be optimized are the covariance matrices Q and R, which play an important role in the EKF performances. The particle swarm optimization algorithm insures this optimization. Lyapunov synthesis approach is used to prove the stability of the whole control loop. The proposed approach is applied on a two-link robot system under Matlab environment. Simulation results have confirmed the effectiveness of the proposed approach against uncertainties and external disturbances; and exhibited a more superior performance than the non-improved control actions.

A robust nonlinear controller based on an improved feedback linearization technique with state observer is developed for a class of nonlinear systems with uncertainties and external disturbances. First, by combining classical feedback linearization approach with a discontinuous control and a fuzzy logic system, we design and study a robust controller for uncertain nonlinear systems. Second, we propose an optimized extended Kalman filter (EKF) for the observation of the states. The parameters to be optimized are the covariance matrices Q and R, which play an important role in the EKF performances. The particle swarm optimization algorithm insures this optimization. Lyapunov synthesis approach is used to prove the stability of the whole control loop. The proposed approach is applied on a two-link robot system under Matlab environment. Simulation results have confirmed the effectiveness of the proposed approach against uncertainties and external disturbances; and exhibited a more superior performance than the non-improved control actions.

Rock typing is a process of rock classification based on mineralogical composition, grainshape pore size distribution (PSD) and communication. In addition to rock-fluid interaction, dynamic behavior and the capillary effect are also considered. In that purpose data need process involve: integrating, analyzing and synthesizing data brought out from different source: Petrophysics, cores analysis, well tests, MDT tooland production profiles. Achievement of rock typing reservoir based on fluid - solid behavior and their relation constitute an important issue not only for making distinguished different rock types but also for fluid gas contacts.For the case study, our investigation is concerned with the determination of the rock type dynamism resulting in reservoir rocks having similar dynamic behavior. Outcome from this process is to establish a representative petrophysical model able to predict any effect own to the change of the rock properties or fluid characteristics. Establishment of numerical model in  that context, and its relative changes can be ascribed to rapid petrophysical variation characteristics: related to pore size, geometry, grain size distribution, fluid behavior and circulation with essential reference to permeability. This latter can affect the simulation time and consequently, the accuracy in the calculation process. In this conducted investigation, application of linear regression method is involving permeability and porosity core measurement, stressing on their coefficient of correlation. Results have led to different clusters classification according to the linearity regarding permeability-porosity changes. Extrapolation can be made for the non-cored reservoir sections or non-cored boreholes associated to the considered field. In that principle geological models can be set. Application of these listed method for TAGI (TriasArgilo-GreseuxInferieur: Lower Shaly – SansdtoneTriasic Formation) in B-H Basin (Algeria) has revealed the presence of six main rock types: sand type 1 (RT-1), sand Type 2 (RT-2), sand type 3 (RT-3), sand type 4 (RT-4), sand type 5 (RT-5) and sand type 6 (RT-6).

Rock typing is a process of rock classification based on mineralogical composition, grainshape pore size distribution (PSD) and communication. In addition to rock-fluid interaction, dynamic behavior and the capillary effect are also considered. In that purpose data need process involve: integrating, analyzing and synthesizing data brought out from different source: Petrophysics, cores analysis, well tests, MDT tooland production profiles. Achievement of rock typing reservoir based on fluid - solid behavior and their relation constitute an important issue not only for making distinguished different rock types but also for fluid gas contacts.For the case study, our investigation is concerned with the determination of the rock type dynamism resulting in reservoir rocks having similar dynamic behavior. Outcome from this process is to establish a representative petrophysical model able to predict any effect own to the change of the rock properties or fluid characteristics. Establishment of numerical model in  that context, and its relative changes can be ascribed to rapid petrophysical variation characteristics: related to pore size, geometry, grain size distribution, fluid behavior and circulation with essential reference to permeability. This latter can affect the simulation time and consequently, the accuracy in the calculation process. In this conducted investigation, application of linear regression method is involving permeability and porosity core measurement, stressing on their coefficient of correlation. Results have led to different clusters classification according to the linearity regarding permeability-porosity changes. Extrapolation can be made for the non-cored reservoir sections or non-cored boreholes associated to the considered field. In that principle geological models can be set. Application of these listed method for TAGI (TriasArgilo-GreseuxInferieur: Lower Shaly – SansdtoneTriasic Formation) in B-H Basin (Algeria) has revealed the presence of six main rock types: sand type 1 (RT-1), sand Type 2 (RT-2), sand type 3 (RT-3), sand type 4 (RT-4), sand type 5 (RT-5) and sand type 6 (RT-6).