Person:
Minchala Ávila, Luis Ismael

Birth Date

1963-11-27

ORCID

0000-0003-0822-0705

Scopus Author ID

56102775600

Afiliación

Universidad de Cuenca, Cuenca, Ecuador
Universidad de Cuenca, Departamento de Ingeniería Eléctrica, Electrónica y Telecomunicaciones(DEET), Cuenca, Ecuador
Universidad de Cuenca, Facultad de Ingeniería

País

Ecuador

Organizational Units

Organizational Unit

Facultad de Ingeniería

La Facultad de Ingeniería, a inicios de los años 60, mediante resolución del Honorable Consejo Universitario, se formalizó la Facultad de Ingeniería de la Universidad de Cuenca, conformada por las escuelas de Ingeniería Civil y Topografía. Esta nueva estructura permitió una mayor especialización y fortalecimiento en áreas clave para el desarrollo regional. Cuenta con programas académicos reconocidos internacionalmente, que promueven y lideran actividades de investigación. Aplica un modelo educativo centrado en el estudiante y con procesos de mejora continua. Establece como prioridad una educación integra, la formación humanística es parte del programa de estudios que complementa a la sólida preparación científico-técnica. Las actividades culturales pertenecen a un programa permanente y activo al interior de nuestras dependencias, a la par de proyectos que desde el alumnado y bajo la supervisión de docentes cumplen con servicios de apoyo a nivel local y regional; promoviendo así una vinculación estrecha con la comunidad.

Job Title

Profesor (T)

Last Name

Minchala Ávila

First Name

Luis Ismael

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Now showing 1 - 10 of 50

Lower limbs motion intention detection by using pattern recognition
(Institute of Electrical and Electronics Engineers Inc., 2018) Astudillo Palomeque, Felipe Emmanuel; Charry Ramírez, José Ricardo; Minchala Ávila, Luis Ismael; Wong de balzan , Sara Null
Electromyographic (EMG) signals processing allows to perform the detection of the intention of movement of the limbs of the human body in order to further use this decision to control wearable devices. For instance, robotic exoskeletons main objective consist of a human-robot interface capable of understanding the user’s intention and reacting appropriately to provide the required assistance in an opportune way. In this paper, we study the performance of superficial EMG intended to design a intent pattern recognition based on Artificial Neural Networks (ANN) trained by the Levenberg-Marquardt method. Experiments consisting in 231 EMG records corresponding to 13 lower limbs muscles from 21 healthy subjects were considered. The EMG signals were randomly divided into the following sets: 70 % for training, 15 % for validation and 15 % for evaluation. The ANN-based pattern recognition was evaluated sample per sample with the movement intention annotations (target) and after the traininig operation end, the performance was evaluated in relation to the events (number of steps). The results show an accuracy of 90,96% sample per sample and 94,88% for an based on events evaluation. These findings motivates the use of this methodology for the classification of the motion intention detection in subjects with pathologies in the lower limbs.
Comparison of the performance and energy consumption index of model-based controllers
(INSTITUTE OF ELECTRICAL AND ELECTRONICS ENGINEERS INC., 2016-10-12) Minchala Ávila, Luis Ismael; Palacio Baus, Kenneth Samuel; Ortiz, J.P; Valladolid, J.D
This paper presents a comparison of the performance of different control algorithms in two types of systems; one exhibiting fast dynamics and the other slow dynamics. The first control system regulates the speed of a DC motor, while the second control system regulates the temperature of an electrical heater. This systems' performance comparison pretends to evaluate the energy consumption, as well as the controllers' transient response in order to identify the best control strategy for each system. System models are obtained through the responses to a pseudorandom binary signal (PRBS) and the least squares fit method using an auto-regressive model with an exogenous variable (ARX). The implemented control algorithms used in this study are: Pole placement regulator (state-space controller) with integral error processing, auto-tunable proportional-integral-derivative (PID) controller, neural PID controller, unconstrained model predictive control (MPC), fuzzy PID controller, neuro-fuzzy controller, bayesian controller and an optimal quadratic regulator (LQR). A detailed analysis of the performance and energy consumption index is performed, that allow the categorization of the control strategies in accordance with their performance.
Blade stress monitoring in a small wind turbine by using Arduino microcontroller
(Institute of Electrical and Electronics Engineers Inc., 2019) Mejía Mayancela, Carlos Eduardo; Salazar Llivisaca, Christian Mateo; Minchala Ávila, Luis Ismael; Gonzalez Morales, Luis Gerardo; González Redrován, Javier
This work presents the design and development of a remote monitoring system for the blades' strain in a small wind turbine (SWT). The monitoring system allows real-time transmission of the stress to a remote client which processes the information in order to suggest further control actions to guarantee a reliable wind turbine operation. Experimental results show an increased axial strain of the blade when the rotational speed of the wind turbine is increased. Additionally, an efficient transmission of the stress measurements is achieved by two communication approaches (wired and wireless) to a remote station, which logs and processes the information.
A simple mapping methodology of gait biomechanics for walking control of a biped robot
(Institute of Electrical and Electronics Engineers Inc., 2018) Minchala Ávila, Luis Ismael; Astudillo Salinas, Darwin Fabián; Vázquez Rodas, Andrés Marcelo; Astudillo Salinas, Darwin Fabián
This research presents a simple mapping methodology for gait biomechanics of a human being into joint angles of a 10 degrees of freedom (DOF) biped robot. The joint angles are mapped by considering the zero moment point (ZMP) criterion. The walking control of the robot is performed by an optimal state feedback controller. The walking trajectories are planned in the sagittal plane, and they are generated in compliance with the ZMP of the robot - keeping the robot within the support polygon - by dividing the control process in two stages: unique support and double support. A linear inverted pendulum model (LIPM) is used as an approximate single mass model of the robot during gait. Results of this research include simulation-based analysis and real-time implementation results, which show accurate robot movements with limited robustness under slippery platforms. Â© 2018 IEEE.
Proposal for modeling electric vehicle battery using experimental data and considering temperature effects
(Institute of Electrical and Electronics Engineers Inc., 2019) Patiño, Diego; Minchala Ávila, Luis Ismael; Ortiz Gonzalez, Juan Paul; Gruosso, Giambattista; Valladolid Quitoisaca, Juan Diego
This paper presents details on the development of two mathematical models of lithium polymers batteries used in electric vehicles (EVs). These models describe the battery state of charge (SOC), and the output voltage of the batteries by using experimental data gathered during the driving of the EV on pre-established routes. The first model estimates the SOC based on temperature data, while the second model replaces the RC network of the traditional Thevenin model by a battery transfer function where the variables of temperature and current are used instead. To determine the performance of these models, simulations are conducted in the MATLAB/Simulink platform. Simulation results are compared with data measured from the EV by using the mean square error index (MSE) for each estimator. The second modeling approach shows a better performance than the battery empirical model obtained from Nernst model.
Design of model-based controllers applied to a solid-state low voltage dc breaker
(INSTITUTE OF ELECTRICAL AND ELECTRONICS ENGINEERS INC., 2015-10-05) Minchala Ávila, Luis Ismael
This paper presents the methodology of design of model-based sliding mode control (SMC) algorithms applied to power electronic dc-dc converters, which are part of the components of a solid-state low voltage dc breaker (SLVDB). The power converters used in the tested schemes of the SLVDB are the boost and sepic dc-dc converters. Accurate disconnection times, user-configured, are achieved with the proposed controllers, as well as a complete minimization of the transient recovery voltage (TRV) in the breaker terminals. Details of the performance of two SLVDB configurations are analyzed and compared in order to establish the best design comprising complexity vs. performance. MATLAB simulations support the results and provide a reasonable picture of the operation of the SLVDB.
Trajectory tracking of a quadrotor using sliding mode control
(IEEE COMPUTER SOCIETY, 2016-05-01) Reinoso, M; Astudillo Salinas, Darwin Fabián; Minchala Ávila, Luis Ismael
This paper presents the design of a sliding mode control (SMC) for trajectory tracking of an unmanned aerial vehicle (UAV), quadrotor. A simplified model of the quadrotor is used for the controller design. The robustness of the controller is verified through simulations, and also through data analysis from the experiments in the 3DR Arducopter platform. The SMC algorithms are implemented in a microcontroller that communicates with a human machine interface (HMI), which monitors the behavior and stability of the state variables. The results show effectiveness of the control technique for maintaining stability in the quadrotor under different operating scenarios.
Adapted D∗Lite to Improve Guidance, Navigation and Control of a Tail-Actuated Underwater Vehicle in Unknown Environments
(2023) Minchala Ávila, Luis Ismael
Biomimetic Autonomous Underwater Vehicles (BAUVs) navigate aquatic environments by mimicking natural propellants from fish species. These vehicles move part(s) of their bodies using various mechanisms to propel and swim forward or laterally. Their main goal is to follow and adjust defined paths to reach a target autonomously. Local path planning is of paramount importance during navigation tasks due to unexpected obstacles. Moreover, path planning strategies should consider the environment's information obtained by the vehicle during its mission, as well as its dynamics and mechanical limitations, to define new routes properly. This article presents the development of a waypoint generator based on the D*Lite algorithm. The proposed planner considers a frontal-short-sighted and tail-actuated BAUV with motion constraints to adjust the vehicle's path towards a target coordinate. By identifying obstacles, the planner adjusts and defines inner waypoints inside the vehicle's vision range by considering closeness to obstacles found and BAUV's current position. The developed strategy reduces collision risks due to the discrimination of nodes near obstacles, prioritizing broad hallways and safer swimming distances between the vehicle's current position and inner waypoints. The effectiveness of the proposed algorithm is simulated using the BAUV's hydrodynamics model and by adding a waypoint tracking controller to correct the vehicle's swimming performance inside three scenarios. The vehicle can reach the goal by properly defining inner waypoints while safely avoiding collisions, narrow hallways, and sharp turns.
Self-Optimizing Control System to Maximize Power Extraction and Minimize Loads on the Blades of a Wind Turbine
(2023) Rivas Vásquez, Carlos Eduardo; Malo Méndez, Gilson Daniel; Minchala Ávila, Luis Ismael
This research proposes a methodology for designing and testing a self-optimizing control (SOC) algorithm applied to a wind energy conversion system (WECS). The SOC maximizes WECS power output and reduces the mechanical stress of the wind turbine (WT) blades by optimizing a multiobjective cost function. The cost function computation uses a combined blade element momentum (BEM) and thin-wall beam (TWB) model for calculating wind the turbine power output and blades’ stress. The SOC deployment implies a low computational cost due to an optimization space reduction via a matrix projection applied to a measurement vector, based on a prior offline calculation of a projection matrix, (Formula presented.). Furthermore, the SOC optimizes the operation of the WECS in the presence of uncertainty associated with the wind speed variation by controlling a linear combination of measured variables to a set point. A MATLAB simulation of a wind turbine model allows us to compare the WECS operating with the SOC, a baseline classic control system (BCS), and a nonlinear model predictive controller (NMPC). The SOC algorithm is evaluated in terms of power output, blades’ stress, and computational cost against the BCS and NMPC. The power output and blades’ stress performance of the SOC algorithm are compared with that of the BCS and NMPC, showing a significant improvement in both cases. The simulation results demonstrate that the proposed SOC can effectively optimize a WECS operation in real time with minimal computational costs.
Design and Implementation of a Smart Meter with Demand Response Capabilities
(ELSEVIER LTD, 2016-04-19) Minchala Ávila, Luis Ismael; Armijos, J; Pesántez, D; Minchala Ávila, Luis Ismael
This paper presents the design of a smart meter (SM) with demand response (DR) capabilities. The SM design is tested in a simulation that implements an advanced measurement infrastructure (AMI), which allows a bidirectional communication between the household smart meters and the distribution management system (DMS). The DMS deploys an energy management system (EMS) that runs a simple demand response program (DRP) based on time of use (TOU), consisting in peak and off-peak rates. Results from the simulation and the data collected from the SM show significant improvements in energy consumption during peak hours thanks to the load curtailment strategies.