Papers by Ruben Morales-Menendez
Advances in Data Mining. Applications and Theoretical Aspects, 2017
In today’s highly competitive global market, winning requires near-perfect quality. Although most... more In today’s highly competitive global market, winning requires near-perfect quality. Although most mature organizations operate their processes at very low defects per million opportunities, customers expect completely defect-free products. Therefore, the prompt detection of rare quality events has become an issue of paramount importance and an opportunity for manufacturing companies to move quality standards forward. This paper presents the learning process and pattern recognition strategy for a knowledge-based intelligent supervisory system; in which the main goal is the detection of rare quality events through binary classification. The proposed strategy is validated using data derived from an automotive manufacturing systems. The \(l_1\)-regularized logistic regression is used as the learning algorithm for the classification task and to select the features that contain the most relevant information about the quality of the process. According to experimental results, 100% of defects can be detected effectively.
Brain Informatics, 2020
Epilepsy is a serious chronic neurological disorder, can be detected by analyzing the brain signa... more Epilepsy is a serious chronic neurological disorder, can be detected by analyzing the brain signals produced by brain neurons. Neurons are connected to each other in a complex way to communicate with human organs and generate signals. The monitoring of these brain signals is commonly done using Electroencephalogram (EEG) and Electrocorticography (ECoG) media. These signals are complex, noisy, non-linear, non-stationary and produce a high volume of data. Hence, the detection of seizures and discovery of the brain-related knowledge is a challenging task. Machine learning classifiers are able to classify EEG data and detect seizures along with revealing relevant sensible patterns without compromising performance. As such, various researchers have developed number of approaches to seizure detection using machine learning classifiers and statistical features. The main challenges are selecting appropriate classifiers and features. The aim of this paper is to present an overview of the wid...
International Journal on Interactive Design and Manufacturing (IJIDeM), 2020
Problem-solving and critical thinking are critical skills that engineers need to develop to be co... more Problem-solving and critical thinking are critical skills that engineers need to develop to be competitive and meet the requirements of the future job market. The use of Active Learning (AL) strategies allows instructors to develop these skills in the students while completing the academic program contents. The purpose of this study is to design and implement AL self-regulated activities developed in Virtual Learning environments and supported by computer simulations for the instruction of numerical methods. Through the use of a real-life engineering problem, in this case, the analysis of a vehicle suspension system, the simulation-based activity provided an environment for the students to analyze the effect of the parameters of numerical methods used to solve a set of Ordinary Differential Equations (ODE). Students compared the solution obtained with numerical methods of different order and different levels of accuracy, both qualitatively and quantitatively. A control group and an experimental group were used to compare and assess the impact of the proposed learning strategy on the instruction of numerical methods. Students who participated in these activities showed a more profound comprehension and obtained higher grades. Through the use of technological tools for guided activities, students acquired and practiced varied technical concepts, compared different solutions, and analyzed how numerical methods could be used to solve complex engineering problems. In addition, the students showed improved engagement, satisfaction, and knowledge retention. Although the main objective of the proposed activity is for the students to acquire a particular competency (i.e., solution of ODE), the development of these kinds of activities (i.e., based on a technological platform) provides the additional advantage of training the students in a technical environment. This depends on the selection of the technological platform where the activity is designed; in this case, Matlab/Simulink, a software widely used in both industrial and academic settings, introduced the students to a real-world technological tool.
Frontiers in Materials, 2021
A methodology is proposed for designing a mathematical model for shock absorbers; the proposal is... more A methodology is proposed for designing a mathematical model for shock absorbers; the proposal is guided by characteristic diagrams of the shock absorbers. These characteristic diagrams (Force-Displacement, Velocity-Acceleration) are easily constructed from experimental data generated by standard tests. By analyzing the diagrams at different frequencies of interest, they can be classified into one of seven patterns, to guide the design of a model. Finally, the identification of the mathematical model can be obtained using conventional algorithms. This methodology has generated highly non-linear models for 2 degrees of freedom magneto-rheological dampers with high precision (2–10% errors).
International Journal of Systems Science, 2021
In this paper, we study the problem of controller design for one closed loop system with feedforw... more In this paper, we study the problem of controller design for one closed loop system with feedforward controller and feedback controller simultaneously. After parametrised these two controllers by two unknown parameter vectors, iterative correlation tuning control is proposed to design these unknown controller parameters through one process of finding roots with respect to one correlation function. As no identification process is needed for the unknown plant in iterative correlation tuning control, the unknown controller parameters are identified by using only input–output measured data. Through applying the adaptive idea to guarantee iterative parameter estimators converge to their true values, MIT rule is regarded as a gradient scheme for the constructed correlation in the parameter adjustment mechanism. Further, Lyapunov stability is applied to derive one parameter adjustment law satisfying the stability for the whole adaptive system. From the point of adaptive analysis, some new results about the sensitivity functions are derived for three types of disturbances to consider tracking and regulation with independent object. Generally, iterative correlation tuning control can design controllers directly without any knowledge about the unknown plant and adjust the unknown controller parameters adaptively through one established parameter adjustment mechanism. Finally two simulation examples are performed to demonstrate the effectiveness of the theories.
Advances in Mechanical Engineering, 2017
This work presents results from the project EvTec, which focus on the design, construction, and t... more This work presents results from the project EvTec, which focus on the design, construction, and testing of an electric vehicle with special features such as modular design, multimotor, power source, digital control, autonomy, and connectivity. The proposed architecture explores the use of the Android-based Control Ecosystem, which integrates the Operating System Android, as part of the open-source control of the vehicle. The objective of this work is to design a platform that enables connectivity with the cloud for monitoring and remote controlling purposes. Results are reported about the feasibility of sending and storing information and in general interacting with a remote server. Vehicle control signals and sensor data were shared remotely at a rate of 200 ms per cycle. The data sent for storage in the cloud reconstructed very well the signals, with no data loss, proving its potential for monitoring purposes. This work also presents a brief discussion about the weakness and stren...
International Journal on Interactive Design and Manufacturing (IJIDeM), 2020
Emerging Technologies (ET), consisting of advanced digital devices, tools, and innovations, poten... more Emerging Technologies (ET), consisting of advanced digital devices, tools, and innovations, potentiate the acceleration of changes and the improvements of many educational processes. In this research, the services offered by centers devoted to promoting the use of ET in their communities are discussed and compared. Mostla, a space devoted to exploring and working with the ETs that have the highest potential to create better educational experiences, is included in the analysis. Also, eight emerging technologies that, according to Mostla, are expected to impact education significantly are analyzed, and some examples of their practical uses are presented. Based on the experience, analysis, and review performed, we note that it is necessary to design memorable learning experiences with ETs to accomplish the development of competencies such as critical thinking, research, creativity, and innovative capacity. The acquisition of these competencies allows our future professionals to face the challenges of Industry 4.0 and confront the principal problems of society skilfully. Therefore, the development of educational strategies supported by ET is necessary to stimulate curiosity. This curiosity allows students to acquire knowledge and retain it better. Universities must keep in view that social and educational innovations should be developed collaboratively and supported by emerging technologies. They must challenge students to solve real problems; this is what develops and strengthens their competencies. Finally, universities must open their doors to society in general and offer their ET services to other public or private institutions, making these technologies accessible so that national education can be improved.
Advances in Science, Technology and Engineering Systems Journal, 2020
Nowadays, process automation and smart systems have gained increasing importance in a wide variet... more Nowadays, process automation and smart systems have gained increasing importance in a wide variety of sectors, and robotics have a fundamental role in it. Therefore, it has attracted greater research interests; among them, Underactuated Mechanical Systems (UMS) have been the subject of many studies, due to their application capabilities in different disciplines. Nevertheless, control of UMS is remarkably more difficult compared to other mechanical systems, owing to their non-linearities caused by the presence of fewer independent control actuators with respect to the degrees of freedom of the mechanism (which characterizes the UMS). Among them, the Furuta Pendulum has been frequently listed as an ideal showcase for different controller models, controlled often through non-lineal controllers like Sliding-Mode and Model Reference Adaptive controllers (SMC and MRAC respectively). In the case of SMC the chattering is the price to be paid, meanwhile issues regarding the coupling between control and the adaptation loops are the main drawbacks for MRAC approaches; coupled with the obvious complexity of implementation of both controllers. Hence, recovering the best features of the MRAC, an Artificial Neural Network (ANN) is implemented in this work, in order to take advantage of their classification capabilities for non-linear systems, their low computational cost and therefore, their suitability for simple implementations. The proposal in this work, shows an improved behavior for the stabilization of the system in the upright position, compared to a typical MRAC-PID structure, managing to keep the pendulum in the desired position with reduced oscillations. This work, is oriented to the real implementation of the embedded controller system for the Furuta pendulum, through a Microcontroller Unit (MCU). Results in this work, shows an average 58.39% improvement regarding the error through time and the effort from the controller.
Manufacturing Letters, 2019
Process Monitoring for Quality is a big data-driven quality philosophy aimed at defect detection ... more Process Monitoring for Quality is a big data-driven quality philosophy aimed at defect detection through binary classification. The l 1-regularized Logistic Regression learning algorithm has been successfully applied in manufacturing systems for rare quality event detection. Since the optimal value of the regularization parameter is not known in advance, many models should be created and tested to find the final model to be deployed at the plant. In this context, model selection becomes a critical step in the process of developing a manufacturing functional model. Since most mature organizations generate only a few Defects Per Million of Opportunities, a three-dimensional model selection criterion (3D À LR) was initially introduced aimed at analyzing highly/ultra unbalanced binary data structures. The 3D À LR criterion combines three of the most important attributes-prediction, separability, complexity-of each candidate model and map them into a three dimensional space to select the best one. In this letter, the 3D À LR is improved; the fit attribute is replaced by a novel separability index that takes into consideration the classification threshold to reward for robustness of predictions. Updated criterion, 3D À LRI, is an improved version of the initial concept.
Manufacturing Letters, 2018
Since most manufacturing systems generate only a few defects per million of opportunities, rare q... more Since most manufacturing systems generate only a few defects per million of opportunities, rare quality event detection is one of the main applications of the Process Monitoring for Quality philosophy. Single-hidden-layer feed-forward neural networks have been successfully applied to perform this task. However, since the best network structure is not known in advance, many models need to be learned and tested to select a final model with the right number of hidden neurons. A new three-dimensional model selection criterion (3D − N N) is introduced for the application of shallow neural networks to highly/ultra unbalanced binary data structures. Proposed criterion combines three of the most important attributesprediction, fit, complexity-of a network structure and map them into a three dimensional space to select the best one. It is simple, intuitive and more stable than widely used criteria-Akaike information criterion, Bayesian information criterion and validation cross-entropy error-when dealing with these data structures.
IFAC-PapersOnLine, 2018
An H ∞ observer for the Semi-Active (SA) force of an Electro-Rheological (ER) damper in a Quarter... more An H ∞ observer for the Semi-Active (SA) force of an Electro-Rheological (ER) damper in a Quarter of Vehicle (QoV) model is proposed. This robust observer is designed in the H ∞ framework to minimize the effect of the unknown road disturbance on the force estimation and includes the damper nonlinearities and its dynamic behavior. Simulation and experimental rig tests results using a 1/5 scale car using easily accessible measurements for the observer, such as acceleration sensors, which are relatively cheap and easy to implement in a real environment. The estimated damper force could be used in a state feedback control strategy to improve comfort and road holding performance of a vehicle with a reduced number of sensors.
Advances in Mechanical Engineering, 2018
In today's highly competitive global market, winning requires near-perfect quality. Although most... more In today's highly competitive global market, winning requires near-perfect quality. Although most mature organizations operate their processes at very low defects per million opportunities, customers expect completely defect-free products. Therefore, the prompt detection of rare quality events has become an issue of paramount importance and an opportunity for manufacturing companies to move quality standards forward. This article presents the learning process and pattern recognition strategy for a knowledge-based intelligent supervisory system, in which the main goal is the detection of rare quality events. Defect detection is formulated as a binary classification problem. The l 1-regularized logistic regression is used as the learning algorithm for the classification task and to select the features that contain the most relevant information about the quality of the process. The proposed strategy is supported by the novelty of a hybrid feature elimination algorithm and optimal classification threshold search algorithm. According to experimental results, 100% of defects can be detected effectively.
IEEE Access, 2018
Chatter is an obstacle for achieving high-quality machining process and high production rate in i... more Chatter is an obstacle for achieving high-quality machining process and high production rate in industries. Chatter is an unstable self-exciting phenomenon that leads to tool wear, poor surface finish, and downgrade the milling operations. A novel active control strategy to attenuate the chatter vibration is proposed. PD/PID controllers in combination with Type-2 Fuzzy logic were utilized as a control strategy. The main control actions were generated by PD/PID controllers, whereas the Type-2 Fuzzy logic system was used to compensate the involved nonlinearities. The Lyapunov stability analysis was utilized to validate the stability of Fuzzy PD/PID controllers. The theoretical concepts and results are proved using numerical simulations. Although PD/PID controllers have been used for chatter control in machining process, the importance of stability along with the implementation of Type-2 Fuzzy logic system for nonlinearity compensation was the main contribution. In addition, active control using an Active Vibration Damper placed in an effective position is entirely a new approach with promising practical results.
Mechatronics, 2017
In recent years there has been an increasing interest in improving vehicle characteristics throug... more In recent years there has been an increasing interest in improving vehicle characteristics through the use of Vehicle Control Systems (VCS). In particular, VCS for the lateral (steering) and longitudinal (velocity) dynamics are used to improve the handling properties of a vehicle. Nonetheless, the introduction of the additional elements required for implementing these control systems also increases the possibility of faults. This problem can be mitigated by using Fault Tolerant Control(FTC) systems. The most common approach for steering FTC design is based on the use of a linear Bicycle Model (BM). Using this model decentralized steering controllers can be designed. However, the BM lacks significant lateral and longitudinal cross-coupling dynamics. In fact, the steering and velocity control problem could be viewed as a multivariable cross-coupled problem. In this article VCS for the steering and velocity are designed. The resulting controllers are decentralized and capable of practically eliminating the cross-coupling. A further problem, which has not been widely reported, is the propagation of the failure of one subsystem to other subsystems. It is shown that when the Velocity Control System (VelCS) fails, then the steering subsystem has a degraded performance due to cross-coupling. The main contribution of this article consists in showing that it is possible to detect and accommodate a failure of the VelCS within the steering control system, i.e. without requiring communication among subsystems. This enables a fully independent operation even if faults occur, that is a Decentralized Fault-Tolerant Control Scheme.
Revista Iberoamericana de Automática e Informática Industrial RIAI, 2016
Un nuevo controlador tolerante a fallas (FTC por sus siglas en inglés, Fault Tolerant Controller)... more Un nuevo controlador tolerante a fallas (FTC por sus siglas en inglés, Fault Tolerant Controller) activo es propuesto para una suspensión automotriz semi-activa, considerando un modelo de un cuarto de vehículo. El diseño está compuesto por: (1) un controlador no-lineal robusto utilizado para aislar las vibraciones en el vehículo causadas por perturbaciones externas y (2) un mecanismo de compensación usado para acomodar fallas aditivas en la fuerza de amortiguamiento. El mecanismo de compensación utiliza un módulo de detección y estimación de fallas robusto, basado en ecuaciones de paridad, para reconstruir la falla; esta información permite calcular la señal de compensación por medio de un modelo inverso del amortiguador para reducir el efecto de la falla en la dinámica vertical de la suspensión. Mientras que el controlador no-lineal, basado en la técnica de control de parámetros variantes lineales (LPV por sus siglas en inglés, Linear Parameter-Varying) está diseñado para aumentar el confort del pasajero y mantener el contacto llanta-suelo. Ante una falla en la fuerza de amortiguamiento, el FTC activo debe asegurar los desempeños de confort y seguridad utilizando la interacción entre el controlador LPV y el compensador. Resultados de simulación en CarSim TM muestran la efectividad del FTC activo respecto a un FTC pasivo y un amortiguador no controlado; el FTC pasivo depende del diseño para su capacidad tolerante, mientras que el FTC activo propuesto mejoró un 50.4 % en confort y un 42.4 % en agarre de superficie cuando ocurre una falla, en contraste con el amortiguador no-controlado que pierde totalmente su efectividad.
Mathematical Problems in Engineering, 2015
A novelGlobal Chassis Control(GCC) system based on a multilayer architecture with three levels: t... more A novelGlobal Chassis Control(GCC) system based on a multilayer architecture with three levels: top: decision layer, middle: control layer, and bottom: system layer is presented. The main contribution of this work is the development of a data-based classification and coordination algorithm, into a single control problem. Based on a clustering technique, the decision layer classifies the current driving condition. Afterwards, heuristic rules are used to coordinate the performance of the considered vehicle subsystems (suspension, steering, and braking) using local controllers hosted in the control layer. The control allocation system uses fuzzy logic controllers. The performance of the proposed GCC system was evaluated under different standard tests. Simulation results illustrate the effectiveness of the proposed system compared to an uncontrolled vehicle and a vehicle with a noncoordinated control. The proposed system decreases by 14% the braking distance in the hard braking test wit...
Shock and Vibration, 2015
Several methods have been proposed to estimate the force of a semiactive damper, particularly of ... more Several methods have been proposed to estimate the force of a semiactive damper, particularly of amagnetorheologicaldamper because of its importance in automotive and civil engineering. Usually, all models have been proposed assuming experimental data in nominal operating conditions and some of them are estimated for control purposes. Because dampers are prone to fail, fault estimation is useful to design adaptive vibration controllers to accommodate the malfunction in the suspension system. This paper deals with the diagnosis and estimation of faults in an automotivemagnetorheologicaldamper. A robust LPV observer is proposed to estimate the lack of force caused by a damper leakage in a vehicle corner. Once the faulty damper is isolated in the vehicle and the fault is estimated, anAdaptive Vibration Control Systemis proposed to reduce the fault effect using compensation forces from the remaining healthy dampers. To fulfill the semiactive damper constraints in the fault adaptation, a...
Proceedings of the IEEE, 2004
This paper shows how state-of-the-art state estimation techniques can be used to provide efficien... more This paper shows how state-of-the-art state estimation techniques can be used to provide efficient solutions to the difficult problem of real-time diagnosis in mobile robots. The power of the adopted estimation techniques resides in our ability to combine particle filters with classical algorithms, such as Kalman filters. We demonstrate these techniques in two scenarios: a mobile waiter robot and planetary rovers designed by NASA for Mars exploration.
IFAC-PapersOnLine
Abstract Current advances in Information Technology have allowed the development of high performa... more Abstract Current advances in Information Technology have allowed the development of high performance communication systems in automatic control applications, as well as high fidelity manufacturing system simulators. A hybrid proposal that combines virtual and remote laboratories approaches for teaching industrial automation courses is presented. Several competencies and skills based on different challenges and active learning techniques are promoted. The proposal requires low investment and operating costs, in addition to being easily scalable. Some elements that influence the teaching/learning process are analyzed. Early results have been successful and can serve as a guide to improve teaching/learning process in experimental automation courses.
Applied Sciences
In this work, four different semi-active controllers for a quarter of vehicle and full vehicles a... more In this work, four different semi-active controllers for a quarter of vehicle and full vehicles are evaluated and compared when used in internal combustion engine (ICE) vehicles vs electric vehicles (EVs) with in-wheel motor configuration as a way to explore the use of semi-active suspension systems in this kind of EVs. First, the quarter of vehicle vertical dynamics is analyzed and then a full vehicle approach explores the effectiveness of the control strategies and the effects of the traction in the vertical Control performances. Aspects like the relation between traction and suspension performances, and the resonance frequencies are also discussed.
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Papers by Ruben Morales-Menendez