Dr. Oscar J. Suarez
Mechatronics Engineering Department, University of Pamplona, Pamplona, Norte de Santander, Colombia
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Academic Career Length
12Years (2015-Present)
(Calculated once Scilit publication data is synced: current year − year of first publication + 1)
Representative Publications
View All Publications1 February 2020 in Automatica
Journal Article
OSOscar J. Suarez
Oscar J. SuarezCVCarlos J. Vega
Carlos J. VegaESEdgar N. Sanchez
Edgar N. Sanchez
GCGuanrong Chen
Guanrong Chen
JEJose Santiago Elvira-Ceja
Jose Santiago Elvira-Ceja
DRDavid Rodriguez-Castellanos
David Rodriguez-Castellanos1 March 2020 in IEEE Transactions on Neural Networks and Learning Systems
Journal Article
CVCarlos J. Vega
Carlos J. VegaOSOscar J. Suarez
Oscar J. SuarezESEdgar N. Sanchez
Edgar N. SanchezGCGuanrong Chen
Guanrong ChenJEJosé Santiago Elvira
José Santiago ElviraDRDavid Rodriguez-Castellanos
David Rodriguez-CastellanosA new approach for trajectory tracking on uncertain complex networks is proposed. To achieve this goal, a neural controller is applied to a small fraction of nodes (pinned ones). Such controller is composed of an on-line identifier based on a recurrent high-order neural network, and an inverse optimal controller to track the desired trajectory; a complete stability analysis is also included. In order to verify the applicability and good performance of the proposed control scheme, a representative example is simulated, which consists of a complex network with each node described by a chaotic Lorenz oscillator.
10 May 2018 in IEEE Transactions on Automatic Control
Journal Article
CVCarlos J. Vega
Carlos J. VegaOSOscar J. Suarez
Oscar J. SuarezESEdgar N. Sanchez
Edgar N. SanchezGCGuanrong Chen
Guanrong ChenJCJose Santiago Elvira Ceja
Jose Santiago Elvira CejaDRDavid Rodriguez-Castellanos
David Rodriguez-CastellanosIn this technical note, a novel approach to trajectory tracking control of a complex network is presented, based on the idea and technique of inverse optimal pinning control. A control law which stabilizes the tracking error dynamics is developed. This controller allows different coupling strengths, and simultaneously minimizing an associated cost functional. Chaotic systems are considered to illustrate the applicability of the new methodology and the proposed controller effectiveness via simulations.
6 October 2016
Conference Paper
OSOscar J. Suarez
Oscar J. SuarezAGAldo Pardo Garcia
Aldo Pardo GarciaESEdgar Nelson Sanchez
Edgar Nelson Sanchez
This paper presents the development of a fuzzy controller for a synchronous generator by means of the exciter, fed by a voltage converter (DC/DC), controlled by pulse width modulation (PWM). The transfer function of the generator based on the data of the input voltages of the exciter and generator output voltage is determined; these data were obtained experimentally. Card data acquisition NI USB-6009* is used for communication with Matlab Simulink** and the implementation of the Fuzzy controller; the output of the controller closes the control loop voltage through port A of microcontroller PIC18F452***. The control system is based on voltage level comparison rule, which is injected into the exciter by means of a variable voltage source that depends on the load connected to the generator output.
28 August 2020 in Frontiers in Physiology
Journal Article
OSOscar J. Suarez
Oscar J. SuarezCVCarlos J. Vega
Carlos J. Vega
ESEdgar N. Sanchez
Edgar N. SanchezAGAna Elizabeth Gonzalez-Santiago
Ana Elizabeth Gonzalez-SantiagoOROtoniel Rodríguez-Jorge
Otoniel Rodríguez-Jorge
EHEsteban Hernandez-Vargas
Esteban Hernandez-Vargas +2
P53 regulates the cellular response to genotoxic damage and prevents carcinogenic events. Theoretical and experimental studies state that the p53-Mdm2 network constitutes the core module of regulatory interactions activated by cellular stress induced by a variety of signaling pathways. In this paper, a strategy to control the p53-Mdm2 network regulated by p14ARF is developed, based on the pinning control technique, which consists into applying local feedback controllers to a small number of nodes (pinned ones) in the network. Pinned nodes are selected on the basis of their importance level in a topological hierarchy, their degree of connectivity within the network, and the biological role they perform. In this paper, two cases are considered. For the first case, the oscillatory pattern under gamma-radiation is recovered; afterward, as the second case, increased expression of p53 level is taken into account. For both cases, the control law is applied to p14ARF (pinned node based on a virtual leader methodology), and overexpressed Mdm2-mediated p53 degradation condition is considered as carcinogenic initial behavior. The approach in this paper uses a computational algorithm, which opens an alternative path to understand the cellular responses to stress, doing it possible to model and control the gene regulatory network dynamics in two different biological contexts. As the main result of the proposed control technique, the two mentioned desired behaviors are obtained.
1 September 2019
Conference Paper
A discrete-time neural sliding-mode pinning controller for synchronization of uncertain complex networks with nonidentical nodes is proposed. To achieve synchronization, a neural control scheme constituted by a Recurrent High-Order Neural Network identifier trained with an extended Kalman algorithm, and a discrete-time sliding-mode controller is used in a small fraction of nodes. The applicability of the proposed scheme is illustrated via simulations, using a network constituted by 8-nodes with four different types of chaotic systems.
About Me
Oscar J. Suarez holds the position of Professor at the Universidad de Pamplona, Pamplona, Colombia, in the Mechatronics Engineering program. He obtained a Bachelor of Science in Electronic Engineering from the Universidad Pontificia Bolivariana in 2011, a Master of Science in Industrial Control from the Universidad de Pamplona in 2015, and a Doctor of Science in Electrical Engineering with a specialization in Automatic Control from the Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional (CINVESTAV) in 2019. In 2020, he was recognized as an international evaluator for ICACIT in Peru and as a peer reviewer by the Ministry of Science, Technology, and Innovation in Colombia. In 2023, he participated as an international evaluator in Chile by the international accreditation agency Acredita CI. In 2024, he was elected chair of the Colombian Chapter of the Computational Intelligence Society (CIS) of the Institute of Electrical and Electronics Engineers (IEEE).With over 12 years of international teaching experience, he has contributed to undergraduate and graduate programs at universities in Colombia and Mexico. He is the author or co-author of over 50 publications, including a research-based book and four book chapters, and he serves as editor for the Springer volume Applications of Computational Intelligence. His research primarily focuses on Automatic Control, Artificial Intelligence, Mechatronic Systems, Complex Networks, and Systems Biology.
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