In this article, we present ARPM (Augmented Reality-based Preventive Maintenance) system, which aims at offering to the technician of a Cement Factory a virtual assistance in real time using various forms of 3D models, images or even texts, in order to help him to maintain and inspect his equipment. This system not only offers the possibility of reducing costs of the preventive maintenance, but also allows monitoring and even anticipating failures. In order to ensure a reliable maintenance operation, we adapted our system to be compatible with the CMMS system (Computerized Maintenance Management System) already exists in the Cement factory

In this article, we present ARPM (Augmented Reality-based Preventive Maintenance) system, which aims at offering to the technician of a Cement Factory a virtual assistance in real time using various forms of 3D models, images or even texts, in order to help him to maintain and inspect his equipment. This system not only offers the possibility of reducing costs of the preventive maintenance, but also allows monitoring and even anticipating failures. In order to ensure a reliable maintenance operation, we adapted our system to be compatible with the CMMS system (Computerized Maintenance Management System) already exists in the Cement factory

In this article, we present ARPM (Augmented Reality-based Preventive Maintenance) system, which aims at offering to the technician of a Cement Factory a virtual assistance in real time using various forms of 3D models, images or even texts, in order to help him to maintain and inspect his equipment. This system not only offers the possibility of reducing costs of the preventive maintenance, but also allows monitoring and even anticipating failures. In order to ensure a reliable maintenance operation, we adapted our system to be compatible with the CMMS system (Computerized Maintenance Management System) already exists in the Cement factory

In this article, we present ARPM (Augmented Reality-based Preventive Maintenance) system, which aims at offering to the technician of a Cement Factory a virtual assistance in real time using various forms of 3D models, images or even texts, in order to help him to maintain and inspect his equipment. This system not only offers the possibility of reducing costs of the preventive maintenance, but also allows monitoring and even anticipating failures. In order to ensure a reliable maintenance operation, we adapted our system to be compatible with the CMMS system (Computerized Maintenance Management System) already exists in the Cement factory

A robust nonlinear controller based on an improved feedback linearization technique with state observer in presence of uncertainties and external disturbances is developed for a class of nonlinear systems. First, by combining classical feedback linearization approach with a robust control term and a fuzzy logic system, we design and study an efficient controller for such systems. Second, we propose an optimized extended Kalman filter for the observation of the states. The parameters to be optimized are the covariance matrices Q and G, which play an important role in the extended Kalman filter performances. This optimization is insured by the particle swarm optimization algorithm. The Lyapunov synthesis approach is used to prove the stability of the whole control loop. The proposed approach is simulated on a nonlinear inverted-pendulum system. Simulation results demonstrate the robustness and effectiveness of the proposed scheme and exhibit a more superior performance than its conventional counterpart.

A robust nonlinear controller based on an improved feedback linearization technique with state observer in presence of uncertainties and external disturbances is developed for a class of nonlinear systems. First, by combining classical feedback linearization approach with a robust control term and a fuzzy logic system, we design and study an efficient controller for such systems. Second, we propose an optimized extended Kalman filter for the observation of the states. The parameters to be optimized are the covariance matrices Q and G, which play an important role in the extended Kalman filter performances. This optimization is insured by the particle swarm optimization algorithm. The Lyapunov synthesis approach is used to prove the stability of the whole control loop. The proposed approach is simulated on a nonlinear inverted-pendulum system. Simulation results demonstrate the robustness and effectiveness of the proposed scheme and exhibit a more superior performance than its conventional counterpart.

A robust nonlinear controller based on an improved feedback linearization technique with state observer in presence of uncertainties and external disturbances is developed for a class of nonlinear systems. First, by combining classical feedback linearization approach with a robust control term and a fuzzy logic system, we design and study an efficient controller for such systems. Second, we propose an optimized extended Kalman filter for the observation of the states. The parameters to be optimized are the covariance matrices Q and G, which play an important role in the extended Kalman filter performances. This optimization is insured by the particle swarm optimization algorithm. The Lyapunov synthesis approach is used to prove the stability of the whole control loop. The proposed approach is simulated on a nonlinear inverted-pendulum system. Simulation results demonstrate the robustness and effectiveness of the proposed scheme and exhibit a more superior performance than its conventional counterpart.

In this work, a new robust nonlinear controller is presented in presence of large external disturbances for a quadrotor aircraft. The controller is based on an improved sliding mode control. The improvement is done by adding two other terms, one is a backstepping synthesis and the other one is a fuzzy logic term in order to reduce the chattering phenomenon and achieve more acceptable performance. The dynamical motion equations are obtained by Euler-Newton formalism. Lyapunov theorem is used to prove the stability of control system. A simulation is carried out to illustrate the effectiveness of the proposed control.

In this work, a new robust nonlinear controller is presented in presence of large external disturbances for a quadrotor aircraft. The controller is based on an improved sliding mode control. The improvement is done by adding two other terms, one is a backstepping synthesis and the other one is a fuzzy logic term in order to reduce the chattering phenomenon and achieve more acceptable performance. The dynamical motion equations are obtained by Euler-Newton formalism. Lyapunov theorem is used to prove the stability of control system. A simulation is carried out to illustrate the effectiveness of the proposed control.

In this work, a new robust nonlinear controller is presented in presence of large external disturbances for a quadrotor aircraft. The controller is based on an improved sliding mode control. The improvement is done by adding two other terms, one is a backstepping synthesis and the other one is a fuzzy logic term in order to reduce the chattering phenomenon and achieve more acceptable performance. The dynamical motion equations are obtained by Euler-Newton formalism. Lyapunov theorem is used to prove the stability of control system. A simulation is carried out to illustrate the effectiveness of the proposed control.

In this work, a new robust nonlinear controller is presented in presence of large external disturbances for a quadrotor aircraft. The controller is based on an improved sliding mode control. The improvement is done by adding two other terms, one is a backstepping synthesis and the other one is a fuzzy logic term in order to reduce the chattering phenomenon and achieve more acceptable performance. The dynamical motion equations are obtained by Euler-Newton formalism. Lyapunov theorem is used to prove the stability of control system. A simulation is carried out to illustrate the effectiveness of the proposed control.