Examinando por Autor "Camacho, Oscar"

Mostrando 1 - 8 de 8
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    Class of quasi fractional analytic functions
    (Elsevier B.V., 2025-12) Camacho, Oscar; Chalco, Ronny; Di Teodoro, Antonio; Gude, Juan José; Vargas, Carlos; Cerda, Adrian; Galán, Josué; Villegas, María
    The document presents a class of quasi-fractional analytic functions, exploring their properties in complex analysis and fractional calculus. Definitions, theorems, and proofs are established that link these functions with concepts such as Gauss's Theorem and the Cauchy-Pompeiu formula. Additionally, the relationship between harmonicity and quasi-fractional analyticity is investigated, also introducing the concept of quasi-generalized fractional analytic functions.
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    Fractional-order model identification based on the process reaction curve: a unified framework for chemical processes
    (Elsevier B.V., 2024-03) Gude, Juan José; García Bringas, Pablo; Herrera, Marco; Rincón, Luis; Teodoro, Antonio di; Camacho, Oscar
    This study introduces a novel method for identifying dynamic systems aimed at deriving reduced-fractional-order models. Applicable to processes exhibiting an S-shaped step response, the method effectively characterizes fractional behavior within the range of fractional orders (α∈[0.5,1.0]). The uniqueness of this approach lies in its hybrid nature, combining one-variable optimization techniques for estimating the model fractional order α with analytical expressions to estimate parameters T and L. This hybrid approach leverages information from the reaction curve obtained through an open-loop step-test experiment. The proposed method demonstrates its efficacy and simplicity through several illustrative examples, showcasing its advantages over established analytical and optimization-based techniques. Notably, the hybrid approach proves particularly advantageous compared to methods relying on the process reaction curve. To highlight its practical applicability, the identification algorithm based on this hybrid approach is implemented on hardware using a microprocessor. The experimental prototype successfully identifies the First-Order Plus Dead Time (FFOPDT) model of a thermal-based process, validating the proposed method's real-world utility.
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    A general identification procedure for reduced-order fractional models based on the process reaction curve
    (Elsevier B.V., 2025-12) Gude, Juan José; Di Teodoro, Antonio; Camacho, Oscar; García Bringas, Pablo
    Recent advances in fractional calculus and computation have enabled the development of more accurate and flexible models for industrial process dynamics. Among these, the Fractional First-Order Plus Dead-Time (FFOPDT) and Fractional Dual-Pole Plus Dead-Time (FDPPDT) models have shown notable performance in representing systems with overdamped step responses. This work introduces a unified analytical identification procedure for both models, derived from the process reaction curve obtained through a simple open-loop step test. The proposed methodology is validated through numerical simulations, and the results demonstrate that it achieves comparable or superior performance to existing methods, with the added benefits of analytical simplicity and computational efficiency, making it suitable for industrial applications.
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    A hybrid control framework for chemical processes with long time delay: theory and experiments
    (American Chemical Society, 2024-07) Teodoro, Antonio di; Herrera, Marco; Rincón, Luis; Gude, Juan José; Camacho, Oscar
    This paper proposes a hybrid control framework based on internal model concepts, sliding mode control methodology, and fractional-order calculus theory. As a result, a modified Smith predictor (SP) is proposed for nonlinear systems with significant delays. The particular predictive approach enhances the sliding mode control (SMC) controller’s transient responses for dead-time processes, and the SMC gives the predictive structure robustness for model mismatches by combining the previous methods with fractional order concepts; the result is a dynamical sliding mode controller. A numerical example is considered to evaluate the performance of the proposed approach, where a step change, external disturbance, and parametric uncertainty test are performed. A real application in the TCLab Arduino kit is presented; the proposed method presented good performance with a little amount of chattering, and in the disturbance rejection case, the overshoot increased with an aggressive response; in both cases, better tuning parameters can improve the process response and the controller action.
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    An introduction to weighted operators via composition and selected properties, aimed at numerical implementation
    (Elsevier B.V., 2025-12) Camacho, Oscar; Chalco, Ronny; Di Teodoro, Antonio; Gude, Juan José ; Montaluisa, Renato; Vargas, Carlos; Vega, Sebastián; Villegas, María
    This work introduces a novel class of weighted fractional operators constructed through the composition of differential and integral operators. In particular, we propose the operator q¯Dxμ, which generalizes classical fractional derivatives while maintaining essential properties such as linearity. Although the semigroup property and the Leibniz rule do not hold in their traditional forms, we derive analogous formulations by combining the proposed operator with the Riemann-Liouville derivative. Furthermore, a numerical representation based on the Grünwald-Letnikov method is developed, enabling efficient discretization and simulation of the weighted operator in cases where analytical solutions are intractable. The approach also considers the interplay between Laplace transforms and convolutions, which is crucial for real-world applications in control and signal processing.
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    A new fractional reduced-order model-inspired system identification method for dynamical systems
    (Institute of Electrical and Electronics Engineers Inc., 2023) Gude, Juan José; Teodoro, Antonio di; Camacho, Oscar; García Bringas, Pablo
    This paper presents a new method for identifying dynamical systems to get fractional-reduced-order models based on the process reaction curve. This proposal uses information collected from the process. It can be applied to processes with an S-shaped step response that can be considered with fractional behavior and a fractional order range of α in [0.5, 1.0]. The proposed approach combines obtaining the fractional order of the model using asymptotic properties of the Mittag-Leffler function with time-based parameter estimation by considering two arbitrary points on the process reaction curve. The improvement in terms of accuracy of the identified FFOPDT model is obtained due to a more accurate estimation of α parameter. This method is characterized by its effectiveness and simplicity of implementation, which are key aspects when applying at an industrial level. Several examples are used to illustrate the effectiveness and simplicity of the proposed method compared to other well-established methods and other approaches based on the process reaction curve. Finally, it is also implemented on microprocessor-based hardware to demonstrate the applicability of the proposed method to identify the fractional model of a thermal process.
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    Sliding mode control design using a generalized reduced-order fractional model for chemical processes
    (Elsevier B.V., 2024-12) Gude, Juan José; Di Teodoro, Antonio; Agudelo, D’hamar; Herrera Garzón, Marco Antonio; Rincón, Luis; Camacho, Oscar
    This article presents a comprehensive study that evaluates the potential advantages of adopting a unified, systematic, and organized general fractional model within the Sliding Mode Control (SMC) design framework. The exploration extends to the model's applicability in a variety of disciplines. Although prior research has utilized SMC and fractional-order systems independently, no previous work has established a mathematical framework that integrates a generic fractional-order SMC model. The study addresses this gap and highlights potential implications for control design and applications in a variety of fields, particularly for chemical processes.
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    A Weighted Fractional Order PID controller for nonlinear systems with variable delay
    (Elsevier B.V., 2025-12) Camacho, Oscar; Chalco, Ronny; Di Teodoro, Antonio ; Gude, Juan José ; Montaluisa, Renato; Vargas, Carlos; Vega, Sebastián
    This paper presents a Weighted Fractional Order PID (WFO-PID) controller that enhances the conventional Fractional Order PID (FOPID) structure by introducing explicit weighting factors for the tuning terms. These weights, combined with fractional orders and gain parameters, provide greater flexibility in tuning, enabling for more precise control over system dynamics. The proposed controller is applied to a mixing tank process with variable time delay, a representative case of industrial processes with challenging dynamics. Its performance is benchmarked against both PID and FOPID controllers, demonstrating improved reference tracking and disturbance rejection, particularly under varying delay conditions and noise in the transmitter. The findings highlight the WFO-PID method's efficiency in managing intricate control situations.