Extractive distillation with salts, unlike other dehydration technologies, is better due to the null toxicity that exists in the distillate, since salt cannot be evaporated. With this distillation technology, it is possible to obtain a high concentration of ethanol, however, there are still problems in the control of the distillation columns in the presence of disturbances. The present work deals with the simulation and control of an extractive distillation column using CaCl${}_2$ as a separating agent, for which the Aspen Dynamics^® simulator is used. The measurement and control of the ethanol composition are carried out by means of temperature, in addition, four control structures are evaluated and compared. These structures are L, D, LV, and DV, which are the most common in conventional distillation, and their performance is measured by means of deterministic indicators applying changes (disturbances) of composition and the flow rate in the main feed of the column. The most relevant results of this work lead to the fact that by applying a controller, it is possible to maintain the desired purity above the international purity standards (99% ethanol) that govern biofuels.

One of the separation processes used for the production and purification of hydrogen is molecular sieve adsorption using the Pressure Swing Adsorption (PSA) method. The process uses two beds containing activated carbon and a sequence of four steps (adsorption, depressurization, purge, and repressurization) for hydrogen production and purification. The initial composition is 0.11 CO, 0.61 H₂, and 0.28 CH₄ in molar fractions. The aim of this work is to bring the purity of hydrogen to 0.99 in molar fraction and implement controllers that can maintain the desired purity even in the presence of the disturbances that occur in the PSA process. The controller design (discrete PID and state feedback control) was based on the Hammerstein–Wiener model, which had an 80% fit over the rigorous PSA model. Both controllers were validated on a virtual plant of the PSA process, showing great performance and robustness against disturbances. The results obtained show that it is possible to follow the desired trajectory and attenuate double disturbances, while managing to maintain the purity of hydrogen at a value of 0.99 in molar fraction, which meets the international standards to be used as a biofuel.

Pressure swing adsorption (PSA) technology is used in various applications. PSA is a cost-effective process with the ability to produce high-purity bio-hydrogen (99.99%) with high recovery rates. In this article, a PSA process for the production of bio-hydrogen is proposed; it uses two columns packed with type 5A zeolite, and it has a four-step configuration (adsorption, depressurization, purge, and repressurization) for bio-hydrogen production and regeneration of the beds. The aim of this work is to design and use an active fault-tolerant control (FTC) controller to raise and maintain a stable purity of 0.9999 in molar fraction (99.99%), even with the occurrence of actuator faults. To validate the robustness and performance of the proposed discrete FTC, it has been compared with a discrete PID (proportional–integral–derivative) controller in the presence of actuator faults and trajectory changes. Both controllers achieve to maintain stable purity by reducing the effect of faults; however, the discrete PID controller is not robust to multiple faults since the desired purity is lost and fails to meet international standards to be used as bio-fuel. On the other hand, the FTC scheme reduces the effects of individual and multiple faults by striving to maintain a purity of 0.9999 in molar fraction and complying with international standards to be used as bio-fuel.

Fractional-order calculus (FOC) has gained significant attention in electric vehicle (EV) energy storage and management systems, as it provides enhanced modeling and analysis capabilities compared to traditional integer-order approaches. This review presents a comprehensive survey of recent advancements in the application of FOC to EV energy storage systems, including lithium-ion batteries (LIBs), supercapacitors (SCs), and fuel cells (FCs), as well as their integration within energy management systems (EMS). The review focuses on developments in electrochemical, equivalent circuit, and data-driven models formulated in the fractional-order domain, which improve the representation of nonlinear, memory-dependent, and multi-scale dynamics of energy storage devices. It also discusses the benefits and limitations of current FOC-based models, identifies open challenges such as computational feasibility and parameter identification, and outlines future research directions. Overall, the findings indicate that FOC offers a robust framework with significant potential to advance next-generation EV energy storage and management systems.

Quadrotor unmanned aerial vehicles (QUAVs) are widely used in civil and defense applications, yet reliable trajectory tracking remains challenging under external disturbances and limited sensing. Conventional backstepping–sliding mode controllers ensure robustness only by selecting discontinuous gains larger than the disturbance bound, which increases chattering and limits the use of smooth switching functions. This paper addresses these limitations by integrating explicit disturbance compensation into a backstepping–sliding framework through a super-twisting observer (STO). The STO reconstructs matched disturbances acting on the translational and rotational dynamics in real time, and the estimated signals are directly injected into the control law. This approach enables effective disturbance rejection beyond the nominal sliding gain while preserving robustness under smooth control actions. Simulation results under single- and multi-frequency perturbations demonstrate accurate disturbance reconstruction (FIT indices above 95%), improved tracking performance, and a significant reduction in chattering. The proposed strategy provides a robust control solution for QUAVs operating in uncertain environments.

Adsorption processes are characterized by their kinetics and equilibrium isotherms described by mathematical models. Nowadays, adsorption with molecular sieves is a method used to separate certain elements or molecules from a mixture and produce hydrogen, nitrogen, oxygen, ethanol, or water treatment. This study had two main objectives. The first one was focused on the use of different natural (Clinoptilolite-S.L. Potosi, Clinoptilolite-Puebla, and Heulandite-Sonora) and synthetic (Zeolite Type 3A) adsorbents to separate the mixtures $H_{2}O/H_{2}S{O}_4$ and $H_{2}O/C_2{H}_{5}OH$ . It was determined that both Zeolite Type-3A and Heulandite-Sonora have greater adsorption capacity in a shorter time compared with the Clinoptilolites at different temperatures. The second objective was the simulation of a pressure swing adsorption process to dehydrate ethanol using the parameters obtained from Zeolite Type 3A (with maximum adsorption capacity). Several configurations were considered to calculate the appropriate nominal values for the optimal process. The results illustrate that the purity of ethanol is increased when the following parameters are considered in the adsorption process: a high pressure, a constant temperature between 100 and 120 ${}^{°}$ C, a feed composition near the azeotropic point with lower water content, and a purge pressure near the vacuum. Finally, the results show that it is possible to take advantage of the length of the absorber bed in order to reduce the energy costs by increasing the ethanol production as well as complying with the international purity standards.