David Sotelo

• Tecnológico de Monterrey

Model Predictive Control (MPC) has been a popular control strategy over recent years due to the possibility of ensuring optimal control while dealing with constraints. However, Nonlinear Model Predictive Control (NMPC) suffers from high computational complexity, resulting in long optimization times. This has restricted NMPC to nonlinear systems tha...

In the extraction and purification of crude oil, natural gas obtained at high pressure is sent through turbines. The fuel in the turbines is then combusted, and the power generated feeds further processes. However, to prevent the formation of liquid droplets and turbine erosion due to sudden gas expansion, the gas pressure must be reduced by a cond...

Modeling and control are challenging in unmanned aerial vehicles, especially in quadrotors where there exists high coupling between the position and the orientation dynamics. In simulations, conventional control strategies such as the use of a proportional–integral–derivative (PID) controller under different configurations are typically employed du...

Artificial intelligence stands for an excellent alternative to be considered in development of new adaptive high-efficiency control design methodologies for uncertain modern complex engineering systems driven by electric motors. In this sense, artificial neural networks can be embedded within innovative nonlinear control design strategies to add ca...

Purpose This article aims to present the results of an exploratory pilot study that demonstrates the validity of a self-created implementation methodology to develop the students' level of perceived achievement of the social entrepreneurship competency and explain how this is equally valid in developing the perceived achievement of the complex thin...

An on-line estimation technique of multiple-frequency oscillatory forces combined with the Hilbert–Huang transform for an important class of actively controlled, forced vibrating mechanical systems with nonlinear stiffness forces is proposed. Polynomial parametric nonlinearities are incorporated in the significantly perturbed vibrating system dynam...

A new adaptive-like neural control strategy for motion reference trajectory tracking for a nonlinear electromagnetic suspension dynamic system is introduced. Artificial neural networks, differential flatness and sliding modes are strategically integrated in the presented adaptive neural network control design approach. The robustness and efficiency...

The objective of this paper is to present the results of the implementation process of the Lab-Tec@Home kit, an educational innovation that allows students to set up home laboratories to test and validate basic control engineering concepts. Specifically, the purpose of this study is to measure the acquisition and development of students’ perceived...

Controlling an automotive suspension system using an actuator is a complex nonlinear problem that requires both fast and precise solutions in order to achieve optimal performance. In this work, the nonlinear model of a quarter-car active suspension is expressed in terms of a flat output and its derivatives in order to embed the nonlinearities of th...

This paper presents a path-following and collision avoidance system for autonomous surface vehicles based on nonlinear model predictive control. The proposed strategy is capable of following a desired path while maintaining a commanded velocity, whereas it can diverge from the references to safely perform maneuvers to elude unexpected obstacles. A...

Embedded controllers for multivariable processes have become a powerful tool in industrial implementations. Here, the Model Predictive Control offers higher performances than standard control methods. However, they face low computational resources, which reduces their processing capabilities. Based on pipelining concept, this paper presents a new e...

It is widely recognized that a hands-on laboratory experience is useful in control engineering education. Herein, the students overcome the main gaps between theoretical knowledge and experimental setups. Nowadays, in times of crisis due to the COVID-19 pandemic, virtual and remote laboratories are emerging as primary educational resources. However...

The active suspension system of a vehicle manipulated using electro-hydraulic actuators is a challenging nonlinear control problem. In this research work, a novel Linear Parameter Varying (LPV) State-Space (SS) model with a fictional input is proposed to represent a nonlinear half-car active suspension system. Four different scheduling parameters a...

This paper presents a path following control scheme for an autonomous surface vehicle under uncertainties and external disturbances. A guidance scheme based on nonlinear model predictive control takes into consideration the sideslip angle to overcome disturbances and generates the heading reference signal. The high-performance software package acad...

The control of an automotive suspension system by means of a hydraulic actuator is a complex nonlinear control problem. In this work, a linear parameter varying (LPV) model is proposed to reduce the complexity of the system while preserving the nonlinear behavior. In terms of control, a dual controller consisting of a model predictive control (MPC)...

Most of the mechanical dynamic systems are subjected to parametric uncertainty, unmodeled dynamics, and undesired external vibrating disturbances while are motion controlled. In this regard, new adaptive and robust, advanced control theories have been developed to efficiently regulate the motion trajectories of these dynamic systems while dealing w...

Considering that two-thirds of world oil production receive a treatment after extraction to remove water and salt contents, one of the most important processes to avoid operational problems in refinery plants corresponds to the dehydration and desalting unit. Here, live crude oil at high temperatures and pressures is processed and stabilized. Hence...

https://www.yumpu.com/en/document/read/65237340/massive-flexible-digital-masterclass-model MFDM is a hybrid-flexible teaching-learning model that satisfies the need for a digital course that guarantees continuous academic and learning activities without sacrificing the quality and attention to the students. Enabled by different digital tools and a...

In recent years, energy consumption has notably been increasing. This poses a challenge to the power grid operators due to the management and control of the energy supply and consumption. Here, energy commitment is an index criterion useful to specify the quality level and the development of human life. Henceforth, continuity of long-term access to...

In recent decades, many optimization algorithms have been proposed by researchers to solve optimization problems in various branches of science. Optimization algorithms are designed based on various phenomena in nature, the laws of physics, the rules of individual and group games, the behaviors of animals, plants and other living things. Implementa...

The Model Predictive Control technique is widely used for optimizing the performance of constrained multi-input multi-output processes. However, due to its mathematical complexity and heavy computation effort, it is mainly suitable in processes with slow dynamics. Based on the Exact Penalization Theorem, this paper presents a discrete-time state-sp...

A new dynamic output feedback control scheme for planned motion reference tracking on nonlinear permanent‐magnet synchronous motors in presence of uncertainty is proposed. Parametric uncertainty, unmodeled dynamics, and variable mechanical load torque are considered as time‐varying unknown signals to be suppressed actively by control voltage inputs...

Petroleum subproducts are obtained in a crude oil distillation plant. Here, due to the chemical properties of the crude oil, a series of complex reactions occurs, and measurements are not always feasible. This poses a challenge to analyse the outcome of the process under real operating conditions. To overcome these difficulties, this paper presents...

This paper proposes a novel finite dimensional discrete-time Nonlinear Model Predictive Control. This technique is based on discrete-time state-space models, Taylor series expansion for prediction and performance index optimization. Furthermore, the technique extends the concept of the Lie derivative for the discrete time case using Euler backwards...

Oil fields around the world produce petroleum that is often accompanied by significant amounts of water and salt. Therefore, to avoid operational problems, dehydration/desalting plants are installed in crude oil production units to remove water-soluble salts from an oil stream. In this paper, a well-designed dehydration/desalting plant of crude oil...

In recent years, interest for petrochemical processes has been increasing, especially in refinement area. However, the high variability in the dynamic characteristics present in the atmospheric distillation column poses a challenge to obtain quality products. To improve distillates quality in spite of the changes in the input crude oil composition,...