Oscar Sanchez

• Doctor of Engineering
• Profesor at University of Guadalajara

This work introduces a novel and practical metaheuristic algorithm, the Gaslike Social Motility (GSM) algorithm, designed for optimization and image thresholding segmentation. Inspired by a deterministic model that replicates social behaviors using gaslike particles, GSM is characterized by its simplicity, minimal parameter requirements, and emerge...

This work introduces an impulsive neural control algorithm designed to mitigate the spread of epidemic diseases. The objective of this paper is the development of a vaccination strategy based on a PIN-type impulsive controller based on an online-trained neural identifier to control the spread of infectious diseases under a complex network approach...

This paper presents an online model-free sensor fault-tolerant control scheme capable of tolerating the most common faults affecting an induction motor. This approach involves using neural networks for fault detection to provide the controller with sufficient information to counteract adverse consequences due to sensor faults, such as degradation i...

In complex dynamical networks, pinning control techniques are often applied to control a small fraction of the nodes in order to stabilize the network with reduced control effort and energy, facilitating adequate development of the complex network. Selecting the controlled nodes is a key challenge to achieving optimal performance. Theoretical analy...

Time series classification is a challenging and exciting problem in data mining. Some diseases are classified and diagnosed based on time series. Such is the case for diabetes mellitus, which can be analyzed based on data from the oral glucose tolerance test (OGTT). Prompt diagnosis of diabetes mellitus is essential for disease management. Diabetes...

This paper presents the design of a new fault-tolerant control methodology based on a model-free neural technique. For an unknown nonlinear dynamical system, a recurrent neural network is proposed to design an on-line identifier to develop an adaptive mathematical model that captures the dynamics of the system using only available measurements of i...

Induction motors can be modeled in different ways for correct operation and control, one of these is the α - β representation, this model has six state variables that can be monitored: rotor position, rotor speed, α flux, β flux, α current and β current. Usually, only three of these variables can be measured directly with sensors. These sensors are...

The main steps involved in a fault-tolerant control (FTC) scheme are the detection of failures, isolation and reconfiguration of control. Fault detection and isolation (FDI) is a topic of interest due to its importance for the controller, since it provides the necessary information to adjust and mitigate the effects of the fault. Generally, the mos...

Complex dynamical networks with time-varying connections have characteristics that allow a better representation of real-world complex systems, especially interest in their not static behavior and topology. Their applications reach areas such as communication systems, electrical systems, medicine, robotic, and more. Both continuous and discrete-tim...

Support systems for healthcare decisions play an important role in the treatment of diabetes mellitus, particularly the information provided by a continuous glucose monitoring (CGM) system, which could be taken advantage of online to forecast risk states such as hypoglycemia or hyperglycemia. This work uses deep neural networks to predict glucose l...

In this paper, we present an impulsive pinning control algorithm for discrete-time complex networks with different node dynamics, using a linear algebra approach and a neural network as an identifier, to synthesize a learning control law. The model of the complex network used in the analysis has unknown node self-dynamics, linear connections betwee...

Glucose-insulin models, testing glucose sensors and support systems for health care decisions play an important role in synthesis of glucose control algorithms. In this work we propose an online glucose-insulin identification using the Recurrent High Order Neural Network (RHONN). Then, the model obtained is used to predict n-steps forward of glucos...

Wind energy is one of the most promising alternatives as energy sources; however, to obtain the best results, producers need to forecast the wind speed, generated power and energy price in order to provide the appropriate tools for optimal operation, planning, control and marketing both for isolated wind systems and for those that are interconnecte...

The effect of meal on blood glucose concentration is a key issue in diabetes mellitus because its estimation could be very useful in therapy decisions. In the case of type 1 diabetes mellitus (T1DM), the therapy based on automatic insulin delivery requires a closed-loop control system to maintain euglycaemia even in the postprandial state. Thus, th...