In this article, various investigations on soft exoskeletons are presented and their functional and structural characteristics are analyzed. The present work is oriented to the studies of the last decade and covers the upper and lower joints, specifically the shoulder, elbow, wrist, hand, hip, knee, and ankle. Its functionality, applicability, and main characteristics are exposed, such as degrees of freedom, force, actuators, power transmission methods, control systems, and sensors. The purpose of this work is to show the current trend in the development of soft exoskeletons, in addition to specifying the essential characteristics that must be considered in its design and the challenges that its construction implies.

New biofuels are in demand and necessary to address the climate problems caused by the gases generated by fossil fuels. Biohydrogen, which is a clean biofuel with great potential in terms of energy capacity, is currently impacting our world. However, to produce biohydrogen, it is necessary to implement novel processes, such as Pressure Swing Adsorption (PSA), which raise the purity of biohydrogen to 99.99% and obtain a recovery above 50% using lower energy efficiency. This paper presents a PSA plant to produce biohydrogen and obtain a biofuel meeting international criteria. It focuses on implementing controllers on the PSA plant to maintain the desired purity stable and attenuate disturbances that affect the productivity, recovery, and energy efficiency generated by the biohydrogen-producing PSA plant. Several rigorous tests were carried out to observe the purity behavior in the face of changes in trajectories and combined perturbations by considering a discrete observer-based LQR controller compared with a discrete PID control system. The PSA process controller is designed from a simplified model, evaluating its performance on the real nonlinear plant considering perturbations using specialized software. The results are compared with a conventional PID controller, giving rise to a significant contribution related to a biohydrogen purity stable (above 0.99 in molar fraction) in the presence of disturbances and achieving a recovery of 55% to 60% using an energy efficiency of 0.99% to 7.25%.

Today, there are new technologies to produce bioethanol: one of them is the Pressure Swing Adsorption (PSA) process. This process has displaced other separation technologies due to the use of natural adsorbents and its methodology to obtain high purities with a lower energy cost. The aim of this work focuses on the optimization of the PSA process (experimental case) to obtain a higher recovery and production of bioethanol using lower energy consumption. The results are favorable since the energy cost is reduced to a range of 60% and 62%, obtaining purities above 99% wt of ethanol and recovery between 75% and 77.41%. The bioethanol produced and purified in the different scenarios meets international standards to be used as a fuel or oxygenating additive.

Motor impairments significantly affect individuals’ ability to perform activities of daily living, reducing autonomy and quality of life. In response to this, robot-assisted rehabilitation has emerged as an effective and practical solution, enabling controlled limb movements and supporting functional recovery. This study presents the development of an upper-limb exoskeleton designed to assist rehabilitation by integrating neurophysiological signal processing and real-time control strategies. The system incorporates a proportional–derivative (PD) controller to execute cyclic flexion and extension movements based on a sinusoidal reference signal, providing repeatability and precision in motion. The exoskeleton integrates a brain–computer interface (BCI) that utilizes electroencephalographic signals for therapy selection and engagement enabling user-driven interaction. The EEG data extraction was possible by using the UltraCortex Mark IV headset, with electrodes positioned according to the international 10–20 system, targeting alpha-band activity in channels O1, O2, P3, P4, Fp1, and Fp2. These channels correspond to occipital (O1, O2), parietal (P3, P4), and frontal pole (Fp1, Fp2) regions, associated with visual processing, sensorimotor integration, and attention-related activity, respectively. This approach enables a more adaptive and personalized rehabilitation experience by allowing the user to influence therapy mode selection through real-time feedback. Experimental evaluation across five subjects showed an overall mean accuracy of 86.25% in alpha wave detection for EEG-based therapy selection. The PD control strategy achieved smooth trajectory tracking with a mean angular error of approximately 1.70°, confirming both the reliability of intention detection and the mechanical precision of the exoskeleton. Also, our core contributions in this research are compared with similar studies inspired by the rehabilitation needs of stroke patients. In this research, the proposed system demonstrates the potential of integrating robotic systems, control theory, and EEG data processing to improve rehabilitation outcomes for individuals with upper-limb motor deficits, particularly post-stroke patients. By focusing the exoskeleton on a single degree of freedom and employing low-cost manufacturing through 3D printing, the system remains affordable across a wide range of economic contexts. This design choice enables deployment in diverse clinical settings, both public and private.