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Es una memoria de las VI Jornadas de Investigación de la Facultad de Ingeniería de la Universidad de Costa Rica, en la que se exponen las 23 ponencias que aprobaron las revisiones de pares, de formato y de plagio. Las jornadas se desarrollaron de forma presencial, los días 23, 24 y 25 de octubre de 2024.

Abstract Maximizing healthy life expectancy is essential for enhancing well-being. Optimal exercise intensity is crucial in promoting health and ensuring safe rehabilitation. Since heart rate is related to exercise intensity, the required exercise intensity is achieved by controlling the heart rate. This study aims to control heart rate during exercise by dynamically adjusting the load on a bicycle ergometer using a proportional-integral (PI) control. The choice of PI parameters is very important because the PI parameters significantly affect the performance of heart rate control. Since the dynamic characteristics of heart rate relative to work rate vary widely from subject to subject, the PI parameters for each subject must be determined individually. In this study, PI parameters are optimized directly from exercise data using a data-driven design approach. Thus, the proposed method does not require excessive exercise of the subject to model heart rate dynamics. Using the proposed method, the heart rate can be controlled to follow a designed reference model so that the heart rate is safely increased to the desired value. The quantitative evaluation of the control results of fifteen healthy volunteers confirmed that the proposed method improved the control error of the target heart rate trajectory by approximately 40%, regardless of gender or age. In addition, it was shown that control parameters from the exercise experiment also indicate that females are more likely than males to have an elevated heart rate at the same load.

Memoria de conferencias de las V Jornadas de Investigación de la Facultad de Ingeniería del año 2023. Universidad de Costa Rica, Facultad de Ingeniería, Instituto de Investigaciones en Ingeniería.

Memoria de conferencias de las IV Jornadas de Investigación de la Facultad de Ingeniería del año 2022.

This study focuses on the design of a robust PD gain-scheduling controller (PD-GS-C) for an unstable SISO (single-input, single-output) magnetic levitation system with two electromagnets (MLS2EM). Magnetic levitation systems offer various advantages, including friction-free, reliable, fast, and cost-effective operations. However, due to their unstable and highly nonlinear nature, these systems require sophisticated feedback control techniques to ensure optimal performance and functionality. To address these challenges, in this study, we derive the nonlinear state-space mathematical model of the MLS2EM and linearize it around five different operating points. The PD-GS-C controller aims to stabilize the system and improve steady-state control error. The strategy for obtaining the PD controller gains involves a parameter space technique, which specifies performance requirements. This technique results in ranges of proportional (KP) and derivative (KD) gains that are used by the PD-GS-C structure. To optimize the controller’s performance further, we utilize the big bang–big crunch optimization technique (BB-BC) to determine the optimal PD gains within the specified ranges. The optimization process focuses on achieving optimal performance in terms of a specific performance index function. This function quantifies the system’s time-domain step response criteria, which include minimizing overshoot percentage, settling time, and rising time. The index function is inversely proportional to the desired performance criteria, meaning that the goal is to maximize the index function to optimize the system’s performance. To validate the effectiveness and viability of the proposed strategy, we conducts MATLAB simulations and real-time experiments. The simulations and experimental findings serve to demonstrate the controller’s performance and verify its capabilities in stabilizing the MLS2EM magnetic levitation system.

This study focuses on the modeling and control optimization of the pitch–roll angles orientation in a quad-rotor UAV (unmanned aerial vehicle) drone system. To address the control challenge, PID (proportional–integral–derivative) controllers are used, which have been tuned through a model-based optimization approach. A non-linear model of the system is obtained and further validated experimentally. The model is implemented in Simulink to conduct model-based optimization. The controller design uses an IMC (internal model control) model-based approach to establish the initial parameters for a PID controller. In the subsequent design phase, a multiobjective approach is taken, incorporating weighted cost functions that account for IAE (integral absolute error) and ITAE (integral of time-weighted absolute error) forms, along with battery usage. The outcomes of this design are showcased through simulations and real-world platform testing.

In this study, a data-driven design method is proposed for a dual-rate system, where the sampling interval of a plant output is restricted and is an integer multiple of the holding interval of a control input. In our proposed method, single-rate virtual reference feedback tuning (S-VRFT), where the holding interval is the same as the sampling interval, is extended to the dual-rate virtual reference feedback tuning (D-VRFT) system. In D-VRFT, a controller is decided using a set of input/output data used in S-VRFT, and it is easy to extend S-VRFT to D-VRFT and implement D-VRFT. In this study, intersample oscillations caused in such a dual-rate control system is prevented because a weighting filter is introduced for penalizing the control input deviation between the sampling instants. The filter is designed as an integrator for weighting the low-frequency domain. The improvement in fast-tracking performance as well as the ripple-free property are demonstrated through both the numerical and experimental results.

III Jornadas de Investigación 2021

Este Volumen Especial es una memoria del congreso de las II Jornadas de Investigación de la Facultad de Ingeniería de la Universidad de Costa Rica. Las jornadas se desarrollaron de forma virtual entre los días 10 y 12 de noviembre de 2020. La contribución de resúmenes a este Volumen Especial fue voluntaria por parte de las personas ponentes, por tanto, en este se exponen 53 de 70 ponencias que fueron presentadas durante el evento. Esta memoria compila los resúmenes extendidos de las ponencias en las 10 áreas temáticas que fueron abordadas en las II Jornadas de Investigación.

This paper deals with the design of a control system based on fractional order models and fractional order proportional-integral-derivative (FOPID) controllers and fractional-order proportional-integral (FOPI) controllers. The controller design takes into account the trade-off between robustness and performance as well as the trade-off between the load disturbance rejection and set-point tracking tasks. The fractional order process model is able to represent an extensive range of dynamics, including over-damped and oscillatory behaviors and this simplifies the process modelling. The tuning of the FOPID and FOPI controllers is achieved by using an optimization, as a first step, and in a second step, several fitting functions were used to capture the behavior of the optimal parameters of the controllers. In this way, a new set of tuning rules called FOMCoRoT (Fractional Order Model and Controllers Robust Tuning) is obtained for both FOPID and FOPI controllers. Simulation examples show the effectiveness of the proposed control strategy based on fractional calculus.

Se plantea en general el problema de la determinación de los parámetros óptimos de controladores bajo los criterios integrales y se describen las características de los métodos de sintonización de controladores de López, Rovira, y de Kaya y Sheib. Se presentan nuevas ecuaciones para el cálculo de los parámetros óptimos para controladores PI y PID bajo los criterios integrales IAE e ITAE. Mediante pruebas comparativas por simulación, se muestran las ventajas obtenidas con las nuevas ecuaciones presentadas.

No presenta resumen