This study presents a small-scale hip exoskeleton incorporating bi-directional artificial muscles constructed with springs of Shape Memory Alloy (SMA). The prototype can effectively support hip motion in both extension and flexion, spanning an angular range of −20∘ to 200∘. Experiments for thermo-mechanical characterization were executed to assess the performance of the SMA muscles throughout the entire motion range. The outcomes not only confirmed the suitability of the SMA muscles for the designed exoskeleton but also provided valuable insights into their behavior and capabilities. System identification experiments were carried out to establish an accurate transfer function, guiding the tuning of Proportional-Integral-Derivative (PID) controllers for enhanced motion-control effectiveness. The safety of the SMA system was addressed with a focus on preventing overheating. Challenges in accurately measuring the temperature of a thin spring were overcome by utilizing two thermocouples for each SMA springs group. Additionally, conventional SMA temperature measurement methods, such as infrared and resistance-based techniques, are limited by high cost, nonlinearity, and small range. This study presents a model-based temperature estimation algorithm that integrates a heat transfer model, electrical input data, and thermocouple data to enable accurate and real-time SMA temperature estimation without additional sensors, offering a cost-effective and reliable alternative. To evaluate the small hip prototype and its controller capabilities, control experiments were executed for both stepping and sinusoidal trajectories. The exoskeleton successfully tracked the desired trajectories, showing its precision. Moreover, system performance under adaptive control was further investigated, revealing an RMSE of 0.94∘ 94⁰ in sinusoidal trajectory experiments, indicating reliable disturbance rejection in the angle measurements.

The main challenge in the automation of the large rotary crane with tower-torsion is the accurate positioning and vibration suppression of the load-sway. The start-of-the-art optimal trajectory generation approaches need to consider several state and input constraints to increase the accuracy; therefore, it requires a large amount of computation time and is not applicable for the practical environment. This study presents an efficient method for optimal trajectory generation considering load-sway suppression and collision avoidance in a fast computation time, which includes two control strategies: the offline bi-objective trajectory generation between the contradictory objectives of total motion time and the collision avoidance fitting function, and the online modification of the optimal trajectory, which is formulated as one-degree-of-freedom optimization to reduce the total motion time and satisfy the entire constraints. The experimental validation with a lab-scale three-dimensional rotary crane is provided to show the effectiveness of the proposed method for practical applications.

Rotary crane systems are essential for transporting heavy loads and hazardous materials. Manual operation can be challenging for new or unskilled operators. This study addresses the challenge of precise final load positioning in construction sites by proposing a trajectory generation system that integrates obstacle avoidance and load-sway suppression. A load monitor camera (LMC) captures the load environment, and the result is displayed on a user-friendly interface designed with error prevention, simplicity, and ergonomic considerations. A usability evaluation has confirmed that the interface reduces task completion time and is well accepted by novice users. The operator selects the final load position from the LMC image, after which a slow-motion trajectory is automatically generated using a cycloidal velocity profile to suppress load-sway. The A* algorithm is used for obstacle avoidance, and its efficiency has been validated through comparison with the Dijkstra algorithm. A benchmark comparison with an S-curve trajectory using trapezoidal trajectory profile has demonstrated the proposed method’s superiority in minimizing sway. Additionally, a disturbance sensitivity analysis under wind conditions has evaluated system robustness and highlights potential improvements. Simulations and lab-scale experiments have confirmed that the proposed method enables safe, smooth, and precise final positioning while avoiding obstacles.

The calculation of the output current of distribution generation (DG) units interfaced with an inverter during the fault is a major issue for isolated and grid-connected distributed networks. The droop control inverter interfaced DG has controlled output current within 2 pu. during the fault. Furthermore, the current output of DG during the fault depends on solar irradiation and wind speed, increasing the uncertainty due to the intermittent nature of renewable energy sources. The installation of DG modifies the fault current direction and strength, which makes relay coordination more difficult. Overcurrent relays are used to defend isolated and grid-connected microgrids. This paper uses different techniques to study the fault current's probability distribution function (PDF) for isolated and grid-connected MGs. We use the droop control and virtual impedance techniques to calculate the probability of the short circuit current that the inverter-interfaced DG contributes. Wind and PV system output power generation samples are tested on MGs using the Monte Carlo Simulation (MCS) approach. A coordination time probability for relays on each line has been calculated to find the mean and standard deviation values of a setting time for overcurrent relays on a faulted bus. The proposed probabilistic model has been tested on the isolated and grid-connected IEEE 33-bus with 5 DGs and MGs using MATLAB code. We found that the droop control method gives a much longer overcurrent relay operating time than the virtual impedance method. This is true for DG buses for both modes of isolated and grid-connected MGs, as well as buses that connect branches. Additionally, for two modes—isolated and grid-connected MGs—the standard deviation of the relay operating time calculated by droop control is higher than its value calculated by the virtual impedance on the same bus.

In Egypt, the production of power and the associated environmental problems are starting to take the stage. One environmentally responsible way to lessen the power crisis is to employ renewable energy sources effectively and efficiently. This paper proposes to develop a hydrogen energy storage-based green (or environmentally friendly) power plant on many Egyptian cities such as Sohag city. To produce green hydrogen, the proposed power station uses energy storage, solar, and wind power. Energy storage systems are used to store extra energy produced by wind turbines and solar panels and to supply energy when the output of renewable energy is low. An optimized design of the proposed power plant uses hydrogen energy to satisfy peak load requirements and reduce GHG (greenhouse gas) emissions. Electrolysis is the method used in the proposed solar/wind power plant to create hydrogen. Water can be split into hydrogen and oxygen via electrolysis, a process that uses electricity. Renewable energy sources can be used to power this procedure, ensuring that the hydrogen produced is “green” and does not contribute to greenhouse gas emissions. The design of the power plant incorporates advanced electrolysis technology, such as proton exchange membrane (PEM) electrolyzers, which are efficient and well-suited for integrating with renewable energy sources.

To enhance the stability and reliability of the system, the converters’ parallel operation can be cascaded to address the constraints posed by the substantial integration of renewable resources. Buck-boost DC-DC converters are often controlled via a cascaded control approach to allow parallel operation. The converter’s output current and its voltage will be controlled by nested loop control. This study proposes adaptive droop control parameters that are updated and verified online using the principal current sharing loops to minimize the fluctuation in load current sharing. When the converters in the microgrid are paralleled, load sharing will be accomplished using the droop control approach in addition to nested proportional-integral-based voltage and current control loops. To restore the correct voltage across the DC microgrid, an outer addition voltage secondary loop will be used, rectifying any voltage disparities caused by the droop management strategy. Several common load resistances and input voltage variations are used to test the suggested method. Using a linearized model, this work assesses the stability and performance of the proposed method. It then confirms the findings with an adequate model created in MATLAB/SIMULINK, Real-Time Simulation Fundamentals, and hardware-based experiments.

A DC microgrid is an efficient way to combine diverse sources; conventional droop control is unable to achieve both accurate current sharing and required voltage regulation. This paper provides a new adaptive control approach for DC microgrid applications that satisfies both accurate current sharing and appropriate voltage regulation depending on the loading state. As the load increases in parallel, so do the output currents of the distributed generating units, and correct current sharing is necessary under severe load conditions. The suggested control approach raises the equivalent droop gains as the load level increases in parallel and provides accurate current sharing. The droop parameters were checked online and changed using the principal current sharing loops to reduce the variation in load current sharing, and the second loop also transferred the droop lines to eliminate DC microgrid bus voltage fluctuation in the adaptive droop controller, which is different and inventive. The proposed algorithm is tested using a variety of input voltages and load resistances. This work assesses the performance and stability of the suggested method using a linearized model and verifies the results using an acceptable model created in MATLAB/SIMULINK Software Version 9.3 and using Real-Time Simulation Fundamentals and hardware-based experimentation.