Sahbi Boubaker

316L stainless steel joined to mild steel is widespread in several applications to reach a requested good association of mechanical properties at a lower cost. The activating tungsten inert gas (ATIG) weld was carried out using a modified flux composed of 76.63% SiO2 + 13.37% Cr2O3 + 10% NaF to meet standard recommendations in terms of limiting the root penetration. Modified optimal flux gave a depth of penetration 1.84 times greater than that of conventional tungsten inert gas (TIG) welds and a root penetration of up to 0.8 mm. The microstructure of the dissimilar joints was investigated using a scanning electron microscope and EDS analysis. The mechanical properties of the weld were not affected by the modified flux. The results show that the energy absorbed in the fusion zone in the case of ATIG weld (239 J/cm2) is greater than that of TIG weld (216 J/cm2). It was found that the weld bead obtained with the optimal flux combination in ATIG welding can better withstand sudden loads. The obtained UTS value (377 MPa) for ATIG welding was close to that of TIG welding (376 MPa). The average Vickers hardness readings for ATIG welds in the fusion zone are up to 277 HV, compared to 252 HV for conventional TIG welding.

This paper presents a predefined-time fractional-order control for a quadrotor system subjected to perturbations. First, a fractional-order sliding manifold is proposed to ensure a predefined-time convergence of the tracking error. Second, a fractional-order switching-type predefined-time controller is proposed to achieve robustness against external disturbances. The predefined stability/convergence are proved using Lyapunov functions. The proposed method is validated using an adequate scenario and compared to other controllers to show the feasibility and superiority of the proposed one.

In this paper, a low-cost monitoring system for an off-grid photovoltaic (PV) system, installed at an isolated location (Sahara region, south of Algeria), is designed. The PV system is used to supply a small-scale greenhouse farm. A simple and accurate fault diagnosis algorithm was developed and integrated into a low-cost microcontroller for real time validation. The monitoring system, including the fault diagnosis procedure, was evaluated under specific climate conditions. The Internet of Things (IoT) technique is used to remotely monitor the data, such as PV currents, PV voltages, solar irradiance, and cell temperature. A friendly web page was also developed to visualize the data and check the state of the PV system remotely. The users could be notified about the state of the PV system via phone SMS. Results showed that the system performs better under this climate conditions and that it can supply the considered greenhouse farm. It was also shown that the integrated algorithm is able to detect and identify some examined defects with a good accuracy. The total cost of the designed IoT-based monitoring system is around 73 euros and its average energy consumed per day is around 13.5 Wh.