Department of Mechanical Engineering,

The main objective of our study is to determine the frequencies and the deformations
proper by the finite element method, using the code implemented in ANSYS software, this numerical
investigation by the finite element method was carried out for two types of Sandwich materials such
as aluminum and mild steel, with boundary conditions: embedding, free, free, free (ELLL) in order to
determine the modal parameters of composite plates such as frequencies as well as clean
deformations. The results obtained show that the increase of the rigidities of the materials and
increases with the increase of the rank of the mode and consequently the increase of the
eigenfrequencies. For this purpose the comparison of the characteristics of the sandwiches are carried
out on the first modes of vibration which are the most important..

The main objective of our study is to determine the frequencies and the deformations proper by the finite element method, using the code implemented in ANSYS software, this numerical investigation by the finite element method was carried out for two types of Sandwich materials such as aluminum and mild steel, with boundary conditions: embedding, free, free, free (ELLL) in order to determine the modal parameters of composite plates such as frequencies as well as clean deformations. The results obtained show that the increase of the rigidities of the materials and increases with the increase of the rank of the mode and consequently the increase of the eigenfrequencies. For this purpose the comparison of the characteristics of the sandwiches are carried out on the first modes of vibration which are the most important..

The classical sliding mode control (SMC) is a robust control scheme widely used for dealing with nonlinear systems uncertainties and disturbances. However, the conventional SMC major drawback in real applications is the chattering phenomenon problem, which involves extremely high control activity due to the switched control input. To overcome this handicap, a pratical design method that combines an adaptive neural network and sliding mode control principles is proposed in this paper. The controller design is divided into two phases. First, the chattering phenomenon is removed by replacing the sign function included in the switched control by a continuous smooth function; basing on Lyapounov stability theorem. Then, an adaptive linear neural network, that has the role of online estimate the equivalent control in the neighborhood of the sliding manifold, is developed when the controlled plant is poorly modeled. Simulation results show clearly the satisfactory chattering free tracking performance of proposed controller when it is applied for the joints angular positions control of a 6-DOF PUMA 560 robot arm.

This paper is focused on a comparison between classic Feedback Linearization Control and a proposed Active Disturbance Rejection Control method. The proposed technique does not require a precise mathematical description of the system, since it is based on the online estimation and rejection of the unmodeled elements of the dynamics. Robustness of the closed-loop control system (against external perturbation and parameters uncertainty) is discussed here. A model of a SCARA robot manipulator is used in the conducted case study as an exemplary plant. Conclusions are supported with results obtained with numerical simulations.

The classical sliding mode control (SMC) is a robust control scheme widely used for dealing with nonlinear systems uncertainties and disturbances. However, the conventional SMC major drawback in real applications is the chattering phenomenon problem, which involves extremely high control activity due to the switched control input. To overcome this handicap, a pratical design method that combines an adaptive neural network and sliding mode control principles is proposed in this paper. The controller design is divided into two phases. First, the chattering phenomenon is removed by replacing the sign function included in the switched control by a continuous smooth function; basing on Lyapounov stability theorem. Then, an adaptive linear neural network, that has the role of online estimate the equivalent control in the neighborhood of the sliding manifold, is developed when the controlled plant is poorly modeled. Simulation results show clearly the satisfactory chattering free tracking performance of proposed controller when it is applied for the joints angular positions control of a 6-DOF PUMA 560 robot arm.

This paper is focused on a comparison between classic Feedback Linearization Control and a proposed Active Disturbance Rejection Control method. The proposed technique does not require a precise mathematical description of the system, since it is based on the online estimation and rejection of the unmodeled elements of the dynamics. Robustness of the closed-loop control system (against external perturbation and parameters uncertainty) is discussed here. A model of a SCARA robot manipulator is used in the conducted case study as an exemplary plant. Conclusions are supported with results obtained with numerical simulations.

In the chemical and petrochemical industry, the Continuous Stirred Tank Reactors (CSTR) are, without doubt, one of the most popular processes. From a control point of view, the mathematical model describing the temporal evolution of the CSTR has a strongly nonlinear crosscoupled character. Moreover, modeling errors such as external disturbances, neglected dynamics, and parameter variations or uncertainties make its control task a very difficult challenge. Even though this problem has been the subject of a wide number of control strategies, this article attempts to propose a viable, robust, nonlinear decoupling control scheme. The idea behind the proposed approach lies in the design of two nested control loops. The inner loop is responsible for the compensation of the nominal model nonlinear cross-coupled terms via static nonlinear feedback; whereas the outer loop, designed around an Extended State Observer (ESO) of which the additional state gathers the global effect of modeling errors, is charged to instantaneously estimate, and then to compensate the ESO extended state. This way, the CSTR complex dynamics are reduced to a series of decoupled linear subsystems easily controllable using a simple Proportional-Integral (PI) linear control to ensure the robust pursuit of reference signals respecting the desired performance. The presented control validation was performed numerically by an objective comparison to a classical PID controller. The obtained results clearly show the viability and the effectiveness of the proposed control strategy for dealing with such nonlinear, strongly crosscoupled plants subject to a wide range of disturbances despite the precision of their described mathematical model.