Temperature, solar insolation, shading and faults affect the performance of the photovoltaic array. Often, the PV arrays get shadowed, completely or partially, by the passing clouds neigh boring buildings, towers or by trees, and other utilities. The situation is of a interest in a case of the large PV power plants. In the case of the shading the characteristics of the PV module are more complex with the several peak values. Under such conditions, it is very difficult to determine the maximum power point (MPP). MATLAB-programmed modelling and simulation of photovoltaic module is presented here, by focusing on the effects of partial shading on the output of the photovoltaic (PV) module and Faults Bypass Diode. The proposed models facilitate simulating the dynamic performances of PV-based power systems and have been validated by means of simulation study. The southern part of Algeria, where the experimental system is mounted, is particularly well appropriate to photovoltaic systems. To evaluate the effectiveness of the proposed model, experiments have been conducted to compare the experimental and simulated current-voltage (IV) and power-voltage (PV) curves of a PV system under some predefined partial shading and faults bypass diode, using different PV technologies such as mono-crystalline and multi-crystalline.

Temperature, solar insolation, shading and faults affect the performance of the photovoltaic array. Often, the PV arrays get shadowed, completely or partially, by the passing clouds neigh boring buildings, towers or by trees, and other utilities. The situation is of a interest in a case of the large PV power plants. In the case of the shading the characteristics of the PV module are more complex with the several peak values. Under such conditions, it is very difficult to determine the maximum power point (MPP). MATLAB-programmed modelling and simulation of photovoltaic module is presented here, by focusing on the effects of partial shading on the output of the photovoltaic (PV) module and Faults Bypass Diode. The proposed models facilitate simulating the dynamic performances of PV-based power systems and have been validated by means of simulation study. The southern part of Algeria, where the experimental system is mounted, is particularly well appropriate to photovoltaic systems. To evaluate the effectiveness of the proposed model, experiments have been conducted to compare the experimental and simulated current-voltage (IV) and power-voltage (PV) curves of a PV system under some predefined partial shading and faults bypass diode, using different PV technologies such as mono-crystalline and multi-crystalline.

Recently, researches in the interventional microrobots have taken the lion’s share in the field of biomedical devices. The aim of biomedical microrobots is to reach inaccessible areas of the human body and deliver drugs in high position. This work presents a new approach to elaborate a new physics-based model for novel self-propelled swimming microrobots. The robot is composed of an ellipsoidal head and hybrid tail that are propelled by a joint polymer metal composite actuator. Green’s function is used to solve the coupled elastic/fluid problems caused by the vibrating hybrid tail in a fluid. This method allowed producing the velocity of microrobot. For the control of the swimming microrobot in hazardous environment, the flatness-fuzzy-based control strategy is developed to eliminate the effect of nonlinear model and to generate the optimal trajectory of flat outputs. The fuzzy technique is aimed to adjust the law control gains in real time for improving the precision of the proposed microrobot in tracking the desired trajectory in fluid. The multi-objectives genetic algorithm is employed to optimize both the reference trajectory and the design parameters in order to enhance the time response and to minimize the dynamic tracking error of the trajectory. To achieve this, a numerical model based on accurate solutions of Navier–Stokes equations is developed. The results of the simulation show that the proposed design with ellipsoidal head gives better performance in comparison with that achieved by the conventional structure.

Recently, researches in the interventional microrobots have taken the lion’s share in the field of biomedical devices. The aim of biomedical microrobots is to reach inaccessible areas of the human body and deliver drugs in high position. This work presents a new approach to elaborate a new physics-based model for novel self-propelled swimming microrobots. The robot is composed of an ellipsoidal head and hybrid tail that are propelled by a joint polymer metal composite actuator. Green’s function is used to solve the coupled elastic/fluid problems caused by the vibrating hybrid tail in a fluid. This method allowed producing the velocity of microrobot. For the control of the swimming microrobot in hazardous environment, the flatness-fuzzy-based control strategy is developed to eliminate the effect of nonlinear model and to generate the optimal trajectory of flat outputs. The fuzzy technique is aimed to adjust the law control gains in real time for improving the precision of the proposed microrobot in tracking the desired trajectory in fluid. The multi-objectives genetic algorithm is employed to optimize both the reference trajectory and the design parameters in order to enhance the time response and to minimize the dynamic tracking error of the trajectory. To achieve this, a numerical model based on accurate solutions of Navier–Stokes equations is developed. The results of the simulation show that the proposed design with ellipsoidal head gives better performance in comparison with that achieved by the conventional structure.

Recently, researches in the interventional microrobots have taken the lion’s share in the field of biomedical devices. The aim of biomedical microrobots is to reach inaccessible areas of the human body and deliver drugs in high position. This work presents a new approach to elaborate a new physics-based model for novel self-propelled swimming microrobots. The robot is composed of an ellipsoidal head and hybrid tail that are propelled by a joint polymer metal composite actuator. Green’s function is used to solve the coupled elastic/fluid problems caused by the vibrating hybrid tail in a fluid. This method allowed producing the velocity of microrobot. For the control of the swimming microrobot in hazardous environment, the flatness-fuzzy-based control strategy is developed to eliminate the effect of nonlinear model and to generate the optimal trajectory of flat outputs. The fuzzy technique is aimed to adjust the law control gains in real time for improving the precision of the proposed microrobot in tracking the desired trajectory in fluid. The multi-objectives genetic algorithm is employed to optimize both the reference trajectory and the design parameters in order to enhance the time response and to minimize the dynamic tracking error of the trajectory. To achieve this, a numerical model based on accurate solutions of Navier–Stokes equations is developed. The results of the simulation show that the proposed design with ellipsoidal head gives better performance in comparison with that achieved by the conventional structure.