Rosas-Caro, Julio

Main Affiliation
Preferred name
Rosas-Caro, Julio
Official Name
Rosas Caro, Julio César
ORCID
0000-0003-0161-0575
Researcher ID
R-6224-2018
Scopus Author ID
57191227591

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    Guest Editorial: Advances in Non‐Isolated DC–DC Converters and Their Applications
    (Institution of Engineering and Technology (IET), 2026-01)
    Rosas-Caro, Julio  
    ;
    Valdez‐Resendiz, Jesus E.
    ;
    Robles-Campos, Héctor R.  
    ;
    Gopal, Yatindra
    ;
    Babaiahgari, Bhanu
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    Control Algorithm for an Inverter-Based Virtual Synchronous Generator with Adjustable Inertia
    (MDPI AG, 2025-09-05)
    Christian A. Villada-Leon
    ;
    Johnny Posada Contreras
    ;
    Rosas-Caro, Julio  
    ;
    Rafael A. Núñez-Rodríguez
    ;
    Juan C. Valencia
    <jats:p>This paper presents the design and implementation of a control algorithm for power converters in a microgrid, with the main objective of providing the flexibility to adjust the system inertia. The increasing integration of renewable energy sources in microgrids has driven the development of advanced control techniques to ensure stability and power quality. The proposed algorithm combines droop control, synchronverter dynamics, and virtual impedance to achieve a robust and efficient control strategy. Simulations were conducted to validate the algorithm’s performance, demonstrating its capability to maintain voltage within acceptable limits and improve the inertial response of the microgrid. The results contribute to the advancement of intelligent and resilient microgrid development, which is essential for the transition towards a more sustainable energy system.</jats:p>
      25
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    Data-Driven Based Control Applied to DC Network Converters for Voltage Bus Stabilization
    (2020)
    J. Loranca-Coutino
    ;
    C.V. Villarreal-Hernandez
    ;
    Ruiz-Martinez, O.F.  
    ;
    Mayo Maldonado, Jonathan
    ;
    J.E. Valdez-Resendiz
      1  11
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    A Multilevel Boost Converter with Reduced Inductor Current
    (2023)
    Rosas-Caro, Julio  
    ;
    Jesus E. Valdez-Resendiz
    ;
    Gerardo Escobar
    ;
    Francisco Beltran-Carbajal
    <jats:p>DC–DC converters are gaining attention due to their importance in key applications like renewable energy generation. A desirable feature in new DC–DC converters is a reduction in the size, which can be achieved with a reduction in the energy stored in the inductors. This article introduces a new step-up DC–DC converter topology with the following advantages: (i) a larger relation of duty cycle vs. voltage gain compared with the classical boost topology and (ii) an inductor with smaller current and smaller inductance (for the same power conversion characteristics) compared to the traditional boost converter. The smaller inductor current is an advantage against many step-up topologies with the inductor in series with the input (and then the input and the inductor currents are equal). The necessary inductance to achieve a certain current ripple is also reduced compared to the classical boost topology. This results in an inductor with a smaller amount of stored energy, lower inductance, and lower current. The proposed topology can be scaled to have a full family of large-voltage-gain converters. This paper presents the mathematical analysis, simulations, and experiments to assess the benefits of the proposition.</jats:p>
      1  10Scopus© Citations 13
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    Energy Recycling Laboratory Experimental Test Bench for Three-Phase FACTS Devices Prototypes
    (2019)
    Jesus E. Valdez-Resendiz
    ;
    Mayo Maldonado, Jonathan
    ;
    Rosas-caro, Julio  
    ;
    Alejo-Reyes, Avelina  
    ;
    Armando Llamas-Terres
    Scopus© Citations 1  2  17
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      26
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    Neural Network Trajectory Tracking Control on Electromagnetic Suspension Systems
    (2023)
    Francisco Beltran-Carbajal
    ;
    Hugo Yañez-Badillo
    ;
    Ruben Tapia-Olvera
    ;
    Rosas-caro, Julio  
    ;
    Carlos Sotelo
    <jats:p>A new adaptive-like neural control strategy for motion reference trajectory tracking for a nonlinear electromagnetic suspension dynamic system is introduced. Artificial neural networks, differential flatness and sliding modes are strategically integrated in the presented adaptive neural network control design approach. The robustness and efficiency of the magnetic suspension control system on desired smooth position reference profile tracking can be improved in this fashion. A single levitation control parameter is tuned on-line from a neural adaptive perspective by using information of the reference trajectory tracking error signal only. The sliding mode discontinuous control action is approximated by a neural network-based adaptive continuous control function. Control design is firstly developed from theoretical modelling of the nonlinear physical system. Next, dependency on theoretical modelling of the nonlinear dynamic system is substantially reduced by integrating B-spline neural networks and sliding modes in the electromagnetic levitation control technique. On-line accurate estimation of uncertainty, unmeasured external disturbances and uncertain nonlinearities are conveniently evaded. The effective performance of the robust trajectory tracking levitation control approach is depicted for multiple simulation operating scenarios. The capability of active disturbance suppression is furthermore evidenced. The presented B-spline neural network trajectory tracking control design approach based on sliding modes and differential flatness can be extended to other controllable complex uncertain nonlinear dynamic systems where internal and external disturbances represent a relevant issue. Computer simulations and analytical results demonstrate the effective performance of the new adaptive neural control method.</jats:p>
      1  4Scopus© Citations 10
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    Failure mode and effects analysis and sensitivity analysis for a neutral point re-injection multi-pulse voltage source converter
    (Elsevier BV, 2025-09)
    Valderrabano-Gonzalez, Antonio  
    ;
    F. Beltran-Carbajal
    ;
    Robles-Campos, Héctor R.  
    ;
    R. Tapia-Olvera
    ;
    Rosas-Caro, Julio  
    Sensitivity Analysis plays a crucial role in the design, control, and optimization of multi-pulse Voltage Source Converters. It helps engineers assess how variations in parameters influence system performance, enabling the development of more efficient and robust converters. This study presents some Failure Modes and Effects Analysis that intends to identify the most affected components when a gate disconnection failure occurs, making them critical points for stress management. Additionally, the most vulnerable components when gates remain connected to high value are distinguished. Verifying the voltage output shape, it can be noticed that RMS voltage measurements are not a reliable indicator for tracking failure, whereas THD offers a more effective solution. Understanding these failure modes is essential for refining the design and control strategies of electronic converters, particularly in applications such as motor control and StatCom. Sensitivity analysis also strengthens control algorithms, ensuring that they can effectively accommodate parameter fluctuations while aiding in fault diagnosis and failure prediction. The early detection of switch malfunctions in power converters is essential for maintaining system reliability, safety, performance, and cost efficiency. Timely identification allows for proactive maintenance, preventing extensive damage and ensuring continuous operation. As the converters become increasingly integral to various applications, implementing reliable fault detection mechanisms is essential for sustaining their optimal performance and long-term functionality.
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