Keywords: Vehículos Aéreos, Sistemas Multi-Agente, Control de Sistemas No Lineales
Abstract: Multi-Agent Aerial Load Transport Systems (MAATS) offer greater payload capacity and fault tolerance than single-drone solutions. However, they have an underdetermined tension allocation problem that leads to uneven energy distribution, cable slack, or collisions between drones and cables. This paper presents a real-time optimization layer that improves a hierarchical load-position-attitude controller by incorporating a Sequential Quadratic Programming (SQP) algorithm. The SQP formulation minimizes the sum of squared cable tensions while imposing a cable-alignment penalty that discourages small inter-cable angles, thereby preventing tether convergence without altering the reference trajectory. We tested the method under nominal conditions by running numerical simulations of four quadrotors. Computational experiments based on numerical simulations demonstrate that the SQP routine runs in a few milliseconds on standard hardware, indicating feasibility for real-time use. A sensitivity analysis confirms that the gain of the cable-alignment penalty can be tuned online, enabling a controllable trade-off between safety margin and energy consumption with no measurable degradation of tracking performance in simulation. This framework provides a scalable path to safe and energy-balanced cooperative load transport in practical deployments.

Keywords: Control de Sistemas No Lineales, Robótica Móvil
Abstract: En este trabajo se propone una ley de control servo visual basado en imagen con convergencia en tiempo finito para un robot móvil omnidireccional con cuatro ruedas suecas. Se presenta el análisis formal de estabilidad global en tiempo finito y se valida a través de simulaciones realizadas en Matlab/Simulink.

Keywords: Modelado e Identificación de Sistemas, Control de Sistemas No Lineales, Otros Tópicos Afines
Abstract: This paper experimentally validates a recently developed switching observer strategy designed to improve state estimation by leveraging the strengths of multiple observers. In this work, we use this switching observer approach to estimate the angle and position of a real-world inverted pendulum-cart system, which, depending on the system state, alternates between swing-up and stabilization control modes. Based on estimation performance and a cost function, the observer dynamically selects the best estimate provided by either the Extended Kalman filter or the Unscented Kalman filter. Experimental results demonstrate effective regulation and smooth transitions between modes. This study highlights the potential of switching-based state estimation to enhance the robustness and reliability of feedback control systems applied to real-world nonlinear and underactuated systems.

Keywords: Robótica Móvil, Control de Sistemas No Lineales, Control Discontinuo (modos deslizantes)
Abstract: Due to the nonholonomic nature of the Unicycle Mobile Robot (UMR) kinematics, the regulation and tracking problems are typically addressed separately, often requiring a unifying time-varying or switched control scheme to handle both tasks simultaneously. In this result, we introduce a time-invariant controller design capable of solving simultaneously the tracking and regulation problems for the UMR, ensuring the convergence of the error vector to the origin in a finite time. The controller design is based on the unit vector control approach and a transformation to the Heisenberg system, which is an equivalent diffeomorphic system to the kinematics of the UMR.

Keywords: Control de Sistemas No Lineales, Vehículos Aéreos, Cómputo para Control
Abstract: This work presents the modeling and control of a PVTOL (Planar Vertical Take-Off and Landing) system with a telescopic arm on its right hand side, equipped with a tool. The model is derived using the Euler-Lagrange method. The control strategy involves a PD controller for the z direction to ensure convergence to a desired position, and a virtual control in x that ensures asymptotic stability through LaSalle’s Invariance Theorem, and a PD controller. The controller’s performance is demonstrated through numerical simulations with zero initial conditions.

Keywords: Detección y Aislamiento de Fallas, Mecatrónica, Procesos Biológicos
Abstract: This work presents a hybrid fault diagnosis framework for Continuous Stirred Tank Reactor (CSTR) bioreactors by integrating Adaptive Neuro-Fuzzy Inference Systems (ANFIS) and Zonotopic Kalman Filters (ZKF). The proposed method consists of two main stages: (1) modeling the nominal behavior of the CSTR using ANFIS trained on fault-free data to extract a compact set of fuzzy rules, and (2) implementing a ZKF to estimate system states and detect deviations associated with faults. The neuro-fuzzy model captures the system’s dynamics, while the zonotopic filter accounts for bounded uncertainty and measurement noise. Fault detection is achieved by evaluating residuals and comparing them to adaptive thresholds derived from the zonotopic bounds. Simulation results for different actuator and sensor fault scenarios demonstrate the effectiveness of the proposed approach in identifying deviations from normal operation, highlighting its potential for improving monitoring capabilities in bioprocesses.

Keywords: Detección y Aislamiento de Fallas, Modelado e Identificación de Sistemas
Abstract: In this work, a recurrence-based measure is introduced to identify incipient faults. The approach is demonstrated using a mass-spring-damper system, where the damper’s degradation is simulated by reducing its value relative to the nominal condition. The proposed method offers two key advantages: it eliminates the need for an explicit model of the system being monitored, and it exhibits high sensitivity to minor faults. One disadvantage of the proposed method is its dependence on data. The effectiveness of recurrence measures can be heavily influenced by the quality and quantity of the data.

Keywords: Detección y Aislamiento de Fallas, Modelado e Identificación de Sistemas, Otros Tópicos Afines
Abstract: Although simultaneous incidents occasionally arise in pipe-lines, multiple leaks occur because of natural events and illegal activities. By considering the available piezometric heads and flow rates at the ends of a line and the invariant of the physical parameters, this work introduces a novel procedure for the two-leak parameter estimation off-line. The proposition leverages the fluid model with the upper and lower Hessenberg structure and the equivalent relation between two-leak and a single-leak in steady-state conditions. Specifically, the two-leak nonlinear steady-state model is transformed into two independent observable subsystems with a common variable related to the flow rate between leaks. This transformation allows estimating the unknown physical parameters of the faults by solving a nonlinear equations set Sigma for two steady-states. To achieve a robust recursive solver, bounds of the physical parameters and filtered data are required. A robust Extended Kalman Filter (EKF) obtains these values through a linear fractional transformation. To evaluate the performance of the numerical solution, a case study involving a hydraulic pilot pipeline of 160 m with two leaks is presented, which obtains a relatively satisfactory error for the two-leak parameter.

Keywords: Modelado e Identificación de Sistemas, Redes Neuronales, Otros Tópicos Afines
Abstract: This study describes the development of a model based on Artificial Neural Networks (ANN) and Neuro-Fuzzy Networks (NFN) to predict droughts in the north of Mexico City, using historical meteorological data. The process focuses on the purification, normalization and analysis of the data, with the aim of building a robust model that allows the identification of relevant weather patterns. The performance of the models is evaluated in different time horizons, observing a high accuracy in the short and medium term predictions, while analyzing its limitations for long-term forecasts. The results highlight the usefulness of ANNs and NFNs in water resources management and underscore the need to improve modelling strategies, incorporating additional variables into future research.

Keywords: Sistemas Caóticos, Redes Neuronales, Otros Tópicos Afines
Abstract: The synchronization of coupled chaotic neurons is a central problem in computational neuroscience, but its stability is often reduced to a single dependence on coupling strength. In this work, we systematically map the synchronization landscape of the Hindmarsh–Rose and Izhikevich models using conditional Lyapunov exponents. We show that stability is shaped not only by coupling but also by parameter mismatch and the choice of coupled variable, producing asymmetric sensitivity, fragmented synchronization basins, and monotonic as well as finite “synchronization windows.” In the Hindmarsh–Rose model, coupling through slow variables yields near-robust synchronization, while fast-variable coupling exposes high sensitivity to intrinsic mismatches. In the Izhikevich model, the efficiency of coupling strongly depends on whether voltage or recovery variables are used, with input current mismatches producing discontinuous basins. These results demonstrate that physiologically plausible parameter variations can shift stability dramatically, offering a more refined framework for predicting synchronized states in both healthy and pathological networks.

Keywords: Control de Sistemas No Lineales, Control Robusto, Sistemas Multi-Agente
Abstract: This paper addresses the leaderless consensus problem for a network of nonlinear Euler-Lagrange (EL) agents subject to unknown constant input disturbances. A fully decentralized and smooth control strategy based on a Proportional-Integral-Derivative (PID) scheme is proposed. The control law ensures global asymptotic convergence to the consensus goal by incorporating an integral action that rejects unknown constant disturbances. The mathematical proof of this claim is derived by applying a Lyapunov function and LaSalle–Krasovskii Invariance Principle. Numerical simulations on a network of ten 2-DoF robotic manipulators are provided to validate the proposed approach effectiveness.

Keywords: Sistemas de Parámetros Distribuidos, Control Robusto, Robótica Móvil
Abstract: In practical robotic legged locomotion, the flexibility of non-rigid legs can compromise both stability and tracking performance, particularly under external disturbances, noise, and distributed vibrations due to impact and walking transition phases. To address this challenge, we propose a boundary H-infinity control strategy for distributed-parameter models of legged robots. The controller is designed to ensure robust stability and disturbance attenuation through actuation at the boundary. Numerical simulations, including both unforced and perturbed scenarios, corroborate the theoretical predictions and demonstrate the effectiveness of the proposed control law.

Keywords: Control de Procesos, Control Robusto, Control de Sistemas No Lineales
Abstract: This paper presents a nonlinear PI controller designed to regulate the concentration in an exothermic Continuous Stirred Tank Reactor (CSTR) that exhibits inverse response dynamics. The proposed strategy extends a conventional PI control structure by introducing a nonlinear gain adapted specifically to systems with inverse action. The main challenge addressed in this work lies in redesigning the gain function so that the controller remains effective even when an increase in the manipulated variable causes the controlled variable to decrease.

To evaluate the proposed controller, a model of the reactor was implemented, and comparative simulations were carried out under reference tracking and disturbance rejection scenarios. The performance was assessed using key indices, including ISE, IAE, TVu, overshoot, and settling time. Results show that the nonlinear controller significantly reduces oscillations and accelerates the system's stabilization compared to a standard PI controller. However, this comes at the cost of a more abrupt control signal, as evidenced by the increase in the total variation of the control action.

Additionally, disturbance rejection tests demonstrated the nonlinear controller’s ability to recover more rapidly after abrupt changes in the system. These findings support the viability of the proposed nonlinear gain structure for improving the dynamic performance of systems with inverse characteristics. As future work, the practical implementation of the controller in real industrial environments is suggested.

Keywords: Sistemas de Eventos Discretos, Sistemas Discretos, Control Robusto
Abstract: Neuromorphic control is receiving increasing attention due to its advantages over classical control approaches, including sparse and event-driven sensing and actuation, energy-efficient hardware implementations, and asynchronous signal processing. However, a formal control-theoretical foundation remains an open challenge. This paper proposes a possible step towards closing this gap by rigorously analyzing a neuromorphic control architecture applied to a damped pendulum for stable limit cycle generation of a desired amplitude. A well-defined Poincaré map is developed to establish conditions for the existence, uniqueness, and local asymptotic stability of its fixed points, which correspond to stable limit cycles. Simulations confirm these predictions, demonstrating how classical tools can provide a formal theoretical framework for neuromorphic and event-based control systems.

Keywords: Sistemas Biomédicos, Control Robusto, Procesos Biológicos
Abstract: This paper tackles the Bispectral Index (BIS) regulation problem in automated anesthetic procedures using propofol and remifentanil simultaneously. The controller design is based on an interval predictor that does not require any filtering or observer design to estimate the drug concentrations on the patient's effect--site, and only the direct measurement of the BIS signal and the knowledge of a feasible interval of initial condition are needed. The design takes into account the pharmacodynamic and pharmacokinetic models and ensures the convergence of the regulation error to a compact set around the origin despite perturbations.

Keywords: Modelado e Identificación de Sistemas, Control de Procesos, Sistemas Económicos y Sociales
Abstract: This paper introduces a dynamic economic benefit function for continuous tubular reactors, tailored for gasification reactors by incorporating a syngas quality index to assess commercial viability and adjust market value based on quality. The gasifier exhibits tristability with nominal (of highest conversion), grate (of intermediate conversion), and extinction (with null conversion) steady-states (SS). For the first time, the economic benefit was continuously computed over time for the entire operation (startup, SS, and shutdown) using an efficient reduced-order model, providing a dynamic economic performance assessment. The results indicate that the nominal SS operation offers the highest profitability with quick returns and high-quality syngas, whereas the extended grate SS operation can be similarly profitable under certain conditions. This work could be the foundation for: (i) incorporating profit dynamics into other continuous processes, (ii) designing operation conditions with different proportion of syngas and biochar production, maintaining a profitable operation, and (iii) devising monitoring and control designs focused on sustaining or enhancing the economic returns from biomass gasification.

Keywords: Control de Procesos, Control Óptimo, Control Discontinuo (modos deslizantes)
Abstract: This paper introduces an extremum seeking control, ESC, that relies on the model to compute the gradient of the performance index with respect to the control input. The resulting mathematical expression of the gradient is a function of the plant states and the control and unknown inputs. In our case study, we use a nonlinear Luenberger observer to estimate the unmeasured states, and thus provide an estimate of the gradient. Such case study considers a biohydrogen production process via the ADM1 model, which feeds with an unknown concentration of glucose a continuous bioreactor where a biomass grows and produce hydrogen. To maximize the hydrogen production rate, we consider two common ESC laws and compare their closed loop performance. For this case study, the control law that avails of the sign of the gradient solely outperforms the control law that uses the gradient value. In fact, the convergence time to the optimal production rate is reduced by two orders of magnitude, when considering the former control law with measurements of all the states.

Keywords: Control Inteligente, Cómputo para Control, Control Supervisor
Abstract: This paper presents a methodological proposal for an Agroclimatic Comfort Index (ACI) designed to support decision-making in managing retractable roofing systems for cherry orchards. The methodology formalizes comfort functions and aggregation while deliberately avoiding fixed thresholds or weights, allowing flexibility across phenological stages. We explore candidate weighting strategies (equal, stage-dependent, expert-elicited, information- and data-driven) and propose operational proxies as a basis for future agronomic validation. To enable real-time monitoring, we also describe a cost-effective microclimate platform based on long-range connectivity and cloud integration, capable of continuously acquiring temperature, relative humidity, solar radiation, and soil/air temperature. Beyond mitigating climatic risks, the framework is conceived to enable stage-tuned microclimate control and, eventually, quality differentiation. Agronomic validation remains a key step for broad adoption and integration into precision agriculture workflows.

Keywords: Mecatrónica, Redes Neuronales, Control Clásico
Abstract: Navigation and path planning are indispensable processes for autonomous agricultural robots, as they enable efficient and safe operation in dynamic farming environments. This paper presents a deep learning-based visual navigation and path planning system for an autonomous crop-spraying robot, developed and evaluated within a controlled agricultural environment. The system aims to develop a trajectory generation and obstacle avoidance through the integration of custom semantic segmentation with a centroid-based trajectory planner and a PID controller employed to ensure accurate path following. Additionally, a data augmentation strategy enhances the robustness of the segmentation model under varying lighting and weather conditions. To evaluate the effectiveness of the segmentation module, several neural network architectures were tested and compared against a custom model specifically designed for agricultural scenarios, demonstrating significant improvements in crop row detection accuracy, trajectory tracking, and overall navigation performance, achieving a precision of 94.04%, an accuracy of 98.08%, and an IoU of 91.02%.

Keywords: Modelado e Identificación de Sistemas, Tecnología para Control, Educación en Control
Abstract: This work introduces an experimental benchmark for modeling the dynamics of a direct current (DC) motor based on actual measurement data. The goal is to analyze two data-driven algorithms for testing their ability to capture the underlying dynamics of the motor. The proposed methodology encompasses both linear modeling, using the numerical algorithm for subspace state space system identification (N4SID), and nonlinear modeling via the sparse identification of nonlinear dynamics (SINDy) framework. The results show how SINDy outperforms N4SID in capturing the actual dynamics of the DC motor.

Keywords: Sistemas Electromecánicos, Control Basado en pasividad, Sistemas Electrónicos de Potencia
Abstract: This article proposes a robust sensorless speed control method based on passivity, compensating for the initial position of the surface permanent magnet synchronous motor (SPMSM). The controller effectively addresses challenges such as unknown initial rotor position, parameter uncertainties, and time-varying internal and external disturbances. Speed, initial position, and load torque estimation algorithms are accurately estimated through extended state observers. These high-gain observer estimates ensure stability and performance under dynamic conditions, preserving system passivity while injecting additional damping when necessary. The control structure's adaptability is a key feature, allowing it to maintain stability and performance under varying conditions. The proposed scheme is rigorously validated through realistic simulations in MATLAB/Simulink-PSIM, including co-simulation of electrical and mechanical subsystems. This comprehensive validation process demonstrates the method's robustness in maintaining reliable performance even with external perturbations, noise, and uncertainties in model parameters.

Keywords: Sistemas Electrónicos de Potencia, Control de Sistemas Lineales, Modelado e Identificación de Sistemas
Abstract: This paper presents the control of a unidirectional, active front-end three-phase rectifier using sliding mode control (SMC). The control has been implemented in a DSP-TMS320F28335 and validated using Hardware-in-the-Loop (HIL). Regulation of the output voltage on the DC-bus is achieved through sinusoidal pulse width modulation (SPWM). The proposed rectifier maintains input voltages and currents in phase, improving power quality and system efficiency. The use of sliding-mode control provides a robust strategy against various disturbances and variations in AC voltages and currents. To evaluate the effectiveness of the proposed control technique, the behavior of the three-phase rectifier under various disturbances in the power grid is analyzed using Typhoon HIL 402. The disturbances considered include harmonic generation, load variations on the direct current (DC) bus, and unbalance in alternating current (AC) input voltages. These scenarios allow validating the robustness and stability of the system under adverse and variable conditions.

Keywords: Sistemas Electrónicos de Potencia, Control Discontinuo (modos deslizantes), Control Robusto
Abstract: This study explores the application of a DC/DC buck power converter integrated with sliding mode control (SMC) to achieve smooth and precise startup control for a permanent magnet DC motor (PMDC). The control objective is to track the speed trajectory for the motor and the voltage for the converter. The primary goal is to regulate the motor’s voltage during startup, ensuring a controlled ramp-up that minimizes inrush currents and mechanical stress, which are critical for enhancing motor longevity and system reliability. The study includes a comprehensive theoretical analysis, supported by simulation to demonstrate the effectiveness of the proposed approach.

Keywords: Sistemas Eléctricos de Potencia, Sistemas Adaptables, Control Robusto
Abstract: Accurate phase and frequency estimation in single-phase power systems is challenging due to the lack of redundant signal information, making grid synchronization harder than in three-phase systems. Measurement distortions, amplitude variations, and frequency deviations further complicate the task.

This work presents a novel adaptive observer that generates a quadrature signal under uncertain frequency conditions while simultaneously providing an accurate frequency estimate. The quadrature signal enables robust phase angle estimation when paired with a classical phase-locked loop. Unlike conventional approaches, we offer a rigorous convergence analysis and a systematic gain-tuning procedure for the proposed observer.

Keywords: Control Basado en pasividad, Sistemas Eléctricos de Potencia, Modelado e Identificación de Sistemas
Abstract: In this work, a passivity-based controller for a step-up/step-down converter is designed and validated through numerical results. The proposed control scheme consists of two control loops: an inner loop and an outer loop. The inner control loop is designed using passivity-based control techniques to track the inductor currents through damping injection and energy shaping. Additionally, an uncertainty estimator based on the immersion and invariance (I&I) approach is employed to enhance the robustness of the inner control loop. Meanwhile, the voltage regulation is handled by a PI controller, which maintains the voltage at the desired reference level. The proposed converter and control strategy are well-suited for regulating the voltage fluctuations of lithium-ion batteries when used as the input source to the converter.

Keywords: Modelado e Identificación de Sistemas, Sistemas Estocásticos, Sistemas Electrónicos de Potencia
Abstract: This paper introduces a Transformer-based machine learning framework for real-time analysis of operational data in microgrids, capable of learning and reproducing normal operational patterns from generation, storage, and consumption data. By combining temporal feature engineering with self-attention mechanisms, the approach captures complex dependencies across time while adapting to dynamic fluctuations in demand, weather, and system conditions. A custom simulation environment was developed to generate realistic time-series data for training under diverse operating scenarios. The methodology emphasizes adaptability through ensemble learning and incremental recalibration, useful for robust fault detection, system supervision, and energy management. Performance is validated using real-world data from a microgrid demonstrator deployed in an educational building, demonstrating the model’s accuracy, scalability, and practical relevance.

Keywords: Control Robusto, Control de Sistemas Lineales, Sistemas Biomédicos
Abstract: This paper addresses the control design problem for reference tracking in precision medicine. Assuming that the control action could be implemented by a cyberphysical device (responsible for injecting and estimating the concentration of the drug in the body), the proposed schema aims to guarantee an effective and safe treatment. Since the drug concentration in the body's compartments is always non-negative, in the pharmacokinetics (PK) context, the reference tracking control design must assure that the states of the closed-loop system remain positive. For this purpose, sufficient linear matrix inequality (LMI) conditions are developed to provide off-line control gains based on the Lyapunov Theory. Additionally, the decay rate is used as an optimization criterion in the controller design, such that the higher the rate, the faster the system achieves the reference value. The pharmacokinetic process is represented by a discrete-time linear parameter varying (LPV) system and a numerical experiment, based on this model, is presented to illustrate the validity and effectiveness of the proposed technique.

Keywords: Procesos Biotecnológicos, Control de Sistemas No Lineales, Control Robusto
Abstract: Anaerobic digestion is a well-known technology for simultaneously degrading organic contaminants or residues and their valorization by generating valuable energy resources such as hydrogen and methane. Co-digestion has been introduced to increase biogas production by combining difficult-to-digest organic waste with easily degradable substrates. Two-stage anaerobic digestion has been introduced to enhance energy recovery efficiency and operational stability. Anaerobic digestion is a complex process that requires suitable controllers. This work presents the design and application of two simple robust controllers to improve biogas production compared to nominal operation. Results show that both controller designs can improve biogas production by manipulating the dilution rate of the methanogenic reactor.

Keywords: Sistemas Biomédicos, Procesos Biotecnológicos, Control de Procesos
Abstract: This paper presents a systematic approach for tuning the Robust Integral of the Sign of the Error (RISE) controller applied to pressure-controlled mechanical ventilation systems using metaheuristic optimization algorithms. Unlike previous studies that rely on ideal conditions and manual tuning, the proposed method incorporates non-ideal factors such as actuator saturation and time delay, which are common in real-world respiratory systems. Several bio-inspired algorithms from different metaheuristic classes were evaluated, including PSO, TLBO, POA, GWO, and MPA. The RISE controller tuned by the MPA algorithm exhibited the best overall performance under both nominal and uncertain scenarios. Additionally, the POA-based tuning yielded reduced overshoot and undershoot in critical phases of the respiratory cycle. The results highlight the effectiveness of metaheuristic optimization in enhancing control accuracy in artificial respiratory support systems.

Keywords: Modelado e Identificación de Sistemas, Control de Procesos, Procesos Biotecnológicos
Abstract: This work introduces a nonlinear dynamic model utilizing the Sparse Identification of Nonlinear Dynamics (SINDy) algorithm and its integration with a model predictive controller (MPC) in the context of a photo-Fenton process. A raceway reactor for water treatment is simulated, targeting the degradation of recalcitrant pharmaceutical compounds. The SINDy model is identified from data generated by the physicochemical process and validated under new operational conditions. Additionally, its performance is compared with a linear state-space model obtained through subspace identification, highlighting the advantages and limitations of both approaches. Subsequently, an MPC controller is designed to regulate the concentration of gabapentin (GBP), considered a critical contaminant. The results demonstrate the high predictive capability of the SINDy model and its superior adaptability compared to the linear model, as well as the high performance of the controller under variable scenarios. These findings emphasize the feasibility of applying sparse identification techniques and advanced control in advanced oxidation processes.

Keywords: Control de Procesos, Control Óptimo, Control de Sistemas No Lineales
Abstract: In this work, the convergence time of the Extremum Seeking Control applied to ensure the optimal performance of a distillation column is studied and diminished in such a way that it is comparable to the one of a linear PI controller. The distillation column is one of the trays in continuous operation that separates an ideal binary mixture. Firstly, a sensitive-type analysis of the convergence time with respect to the ESC tuning parameters is carried out, locating the values for which the convergence time is minimum; next, a variation of the ESC is applied, which consists of the addition of a decreasing function to initially speed up the ESC performance, and a saturation block is also added to constrain likely large changes in the control inputs. The control problem is one of regulation, for which, for validation purposes, the optimal conditions for the testing cases are determined by a conventional sensitivity analysis of the output with respect to the inputs. The testing runs show not only the effectiveness of the ESC but also that the modified ESC has a reduced convergence time compared to the typical ESC, and it is even comparable to that of a linear PI controller.

Keywords: Control de Sistemas No Lineales, Control Difuso
Abstract: This paper proposes a proportional derivative output feedback controller for the stabilization of nonlinear singular systems. The derivative part of the controller normalizes the system by completing the rank of the descriptor matrix. Sufficient conditions in the form of linear matrix inequalities are achieved via the Lyapunov method. Numerical examples illustrate the performance of the proposal.

Keywords: Sistemas Adaptables, Control de Sistemas No Lineales, Robótica de Maipuladores
Abstract: In this paper, we propose some indirect adaptive control schemes to achieve finite-time regulation for the simplest non-linear mechanical system: a pendulum. Our control proposal is composed of two parts: a Proportional-Derivative nonlinear feedback and a finite-time estimation algorithm. Two parameter estimation laws based on the Dynamic Regressor Extension and Mixed are proposed: one of them relies on Kreisselmeier's dynamic extension, while the other employs a least-square estimator with forgetting factor. The performance of the proposed controllers is thoroughly analyzed through various simulations.

Keywords: Sistemas Caóticos, Control de Sistemas No Lineales, Control Clásico
Abstract: We propose an anticontrol method to construct piecewise linear systems with multiscroll attractors. In our approach feedback design is use to manipulate the eigendirections of each linear partition of state space, in order to generate or inhibit scrolls around each equilibrium point by adjusting the corresponding controller gains. We design multiscroll attractors with different symmetries, homoclinic and heteroclinic chaos, and even multistable attractors. Using this flexible chaos generation technique different versions of chaotic attractors can be generated from systems with very similar structure. Our results are illustrated with numerical simulations of different forms of anti-controlled linear time-invariant system with three multiscroll attractors.

Keywords: Control Discontinuo (modos deslizantes), Sistemas de Parámetros Distribuidos, Control de Sistemas No Lineales
Abstract: Deep geothermal energy holds significant promise for meeting large-scale energy demands while reducing CO_2 emissions. However, a key challenge lies in the injection of fluids into the Earth's crust, which can induce seismic events by reactivating pre-existing faults or creating new ones. In this study, we use a novel robust control approach to mitigate induced seismicity in geothermal systems. We begin with a simplified physical model that captures the coupling between a three-dimensional diffusion equation, describing fluid pressure propagation, and a nonlinear equation governing the seismicity rate. Building on this, we develop a robust tracking control strategy that ensures the seismicity rate to follow a predefined safe reference in finite time, while maintaining a continuous control signal. This control design minimizes seismic risk without compromising fluid circulation, which is critical for geothermal energy production and storage. The proposed sliding-mode control method handles uncertainties and unknown dynamics inherent to subsurface environments. Using simulation scenarios inspired by the Pohang Enhanced Geothermal System, South Korea, we demonstrate the method’s effectiveness and robustness under varying energy demands. The results highlight its potential for real-time implementation in operational geothermal systems.

Keywords: Sistemas Electromecánicos, Control Clásico, Control de Sistemas No Lineales
Abstract: In the presented manuscript, the design of a control law coupled with different linear state observers is used for the stabilization of an inverted rotatory pendulum at its unstable equilibrium point. The proposed controller is a feedback state algorithm designed from the Taylor series linearization around the equilibrium point. Since the state vector requires the angular displacements and velocities, and only the first ones are measured, different linear state observers are designed to deal with the problem, including Luenberger, Kalman Filter, Extended Kalman Filter, Sliding mode, and reduced order observers. Experimental open and closed-loop results are presented that allow a qualitative and quantitative analysis of: (i) the dynamic observer's performance, (ii) the parametric perturbation robustness of the control-observer schemes, and (iii) the computational resources needed for each of the observation algorithms. This analysis compares different observers' algorithms and establishes which one presents significant advantages for the embedded control implementation applied in under-actuated systems.

Keywords: Control Basado en pasividad, Control de Sistemas No Lineales, Sistemas Electromecánicos
Abstract: This work addresses the problem of current optimization control for synchronous motors using the well-known Maximum Torque Per Ampere (MTPA) strategy integrated with a Passivity-Based Control (PBC) that guarantees the convergence to the optimal currents. First, a current tracking control scheme based on the PBC is implemented by exploiting the system’s structure and decomposing it into its subsystems to ensure reference current convergence. Then the optimization procedure is explained in detail, step by step, using the Lagrange multipliers method for an interior permanent magnet synchronous motor (IPMSM) with constant inductances, enabling the current tracking control to achieve optimal performance. Finally, the proposed approach is validated through numerical simulations conducted in MATLAB/Simulink environment.