Soft robotics, a recent advancement in robotics systems, distinguishes itself by utilizing soft and flexible materials like silicon rubber, prioritizing safety during human interaction, and excelling in handling complex or delicate objects. Soft pneumatic actuators, a prevalent type of soft robot, are the focus of this paper. A new geometrical parameter for soft artificial pneumatic muscles is introduced, enabling the prediction of actuation behavior using analytical models based on specific design parameters. The study investigated the impact of the chamber pitch parameter and actuation conditions on the deformation direction and internal stress of three tested soft pneumatic muscle (SPM) models. Simulation involved the modeling of hyperelastic materials using finite element analysis. Additionally, an artificial neural network (ANN) was employed to predict pressure values in three chambers at desired Cartesian positions. The trained ANN model demonstrated exceptional performance. It achieved high accuracy with training, validation, and testing residuals of 99.58%, 99.89%, and 99.79%, respectively. During the validation simulations and neural network results, the maximum errors in the x, y, and z coordinates were found to be 9.3%, 7.83%, and 8.8%, respectively. These results highlight the successful performance and efficacy of the trained ANN model in accurately predicting pressure values for the desired positions in the soft pneumatic muscles.

In this paper an efficient, compact, and cheap power source design for an off-grid PV water pumping system is investigated. The proposed system consists of a PV array, battery, three-port converter (TPC), three-phase voltage source inverter, and induction motor pump. Power is extracted from PV sources during the daytime and used to charge batteries through the three-port converter, then used later to supply load during the nighttime. An intelligent MPPT method is used to obtain PV maximum power; a jellyfish optimization technique with different control algorithms is used to optimize and tune controllers’ parameters among the system. Different modes for the TPC are discussed depending on PV power availability. The proposed system is simulated to assess system performance under different conditions; also the system is efficient with reduced number of components than conventional converters. A complete unified power management over PV input port, battery port, and load port has occurred for all operation modes. At all operation modes, the system has been feeding load without any unmet loads. A real case study in Al-Kharijah oasis is studied and simulation results are listed; for the Dom case DC bus ripple factor voltage percentage equals 0.8%, in the Dim case equals 3%, and in the Siso mode equals 9%.

Due to the absence of mechanical contact, active magnetic bearing can be electrically controlled in an accuracy of a micrometer. This makes it a good choice to be used for robot manipulation in the micrometer scale, especially in environments that need to be very clean, for example, surgery or clean rooms. Moreover, it can be used in the applications that need high precision micromotion such as semiconductor wafers manipulation. Despite all these benefits, there are few studies that have investigated the application of active magnetic bearing in the robotics field in spotless environments for micromotion applications. This article proposes a new novel six-degree of freedom two-link manipulator using two contactless joints with active magnetic bearing. The key design aspects of the proposed manipulator are presented. The proposed manipulator is designed using finite element method. Each joint roll angle is controlled using a PID-based feedback linearization controller, while a state feedback controller with integral term is used for controlling the active magnetic bearing five-degree of freedom. The stability analysis of the system, under the proposed controller, is carried out. The robustness of the controllers is tested against end effector payload variations. The results demonstrate that the proposed two-link manipulator is feasible and valid for the applications in spotless environments that need high precision accuracy micromotion control. These significant findings have indicated the feasibility of implementing this proposed manipulator in practice and open the door for developing other types of robots with complete contactless joints using active magnetic bearing.

Because of the increasing and escalating demand on energy sources, utilizing renewable energy sources efficiently becomes mandatory. This paper aims to construct and discuss efficient and low-cost configuration of standalone PV water pumping system with three-phase induction motor. This configuration is achieved by using optimized PI-controllers with the Jellyfish optimizer and a high gain DC to DC converter with maximum power point tracking technique to extract maximum power from the PV system. In addition to the high gain DC to DC converter, the proposed system consists of PV array, DC to DC bidirectional converter with batteries in order to save excess PV power and reuse it when there is no enough output power for the system, three-phase inverter, three-phase induction motor, and pump to drive the water. The proposed system succeeded to keep the total harmonic distortion for the AC output voltage within 0.61%, and keep DC bus voltage ripple factor within 0.2%, both are within acceptable limits. The system is designed, modeled, and simulated in detail using MATLAB/Simulink software to evaluate the performance under fast variations of climatic profile.

The world is moving toward reliance on electric vehicles as a substitute for internal combustion engine vehicles Due to global concerns about climate change. The main barriers to EV widespread adoption of EV are long charging time and lack of infrastructure. Fast charging stations (FCSs) can solve these problems, but FCSs present a large and unexpected load on the grid. One of the solutions to mitigate the impact of FCSs on the grid is to use renewable energy sources and energy storage. This paper proposes the design and control of a 100-kW standalone DC fast charging station with two charging slots based on photovoltaic power and battery energy storage. The station location is at Alamein, Egypt. Station sizing is carried out based on real load profile using HOMER software. MATLAB Simulink is used to verify station performance under real weather conditions and solar irradiance of station location. The results show that the proposed station can meet various load conditions.

This paper investigates the design, modelling and control of a novel contactless active robotic joint using active magnetic bearing (AMB). A robot with such joint avoids dust generation, oil lubrication and friction. This makes such robot suitable for applications in clean environments such as clean and surgery rooms. Also, such joint can be used in space robots, self-reconfiguration robots and robots with selective compliance. In contrast to the passive joint with AMB that needs the control of 5 degree-of-freedom (DOF), the proposed joint here needs the control of 6-DOFs. The additional variable to be controlled is the robot joint angle. Frameless, brushless, direct drive, high torque DC motor (BLDC) is used to control the robot joint angle. A contactless sensor for robot joint angle measurement is proposed. The mutual interaction between the control of the BLDC motor and the AMB is studied. Although in this paper tracking control of the robot joint angle and stabilization of the other 5-DOFs to their null values are carried out, it is possible to carry out tracking control of all the 6-DOFs. This leads to enlarge the mobility of the joint from 1-DOF to 6-DOFs. Feedback linearization controller is used to track the robot joint angle desired trajectory. State feedback controller is used to stabilize the AMB. The proposed system is designed and simulated using CATIA and MATLAB/Simulink. The results prove the feasibility of the proposed robotic joint from design and control view points.