Javier Jimenez-Cabas | Universidad de la Costa (original) (raw)
Papers by Javier Jimenez-Cabas
International Journal of Information Technology, 2024
The manuscript presents new methodologies for process characterization and control tuning for int... more The manuscript presents new methodologies for process characterization and control tuning for integrated systems. Integrative systems are widespread in the industrial environment. Some control systems for level, pressure, concentration, and temperature are examples. Although many papers have been published on the subject, no standard has been established, so this remains an open problem. The proposed characterization method consists of deriving the response of the integrating system and applying characterization techniques for self-regulated processes. The proposed tuning method is based on deducing tuning equations for a PD control from the λ tuning rules. The performance of the proposed methods is validated through simulation and experimental tests.
Sustainability, 2023
This article is an open access article distributed under the terms and conditions of the Creative... more This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY
Heliyon, 2023
A 2 3 factorial design was performed to analyze the performance of a mini-split air conditioning ... more A 2 3 factorial design was performed to analyze the performance of a mini-split air conditioning system under several psychrometric air conditions at the evaporator inlet, similar to Tropical Caribbean region conditions. In addition, a search for new energy-saving opportunities was performed. The results showed that interactions between the temperature of the air inlet, the humidity of the air inlet, and the fan speed level are significant in the mini-split energy performance under Caribbean climate conditions. Hence, working on an oriented energy savings control strategy is necessary. Therefore, this study recommends developing a fan speed control scheme, generating energy savings of around 10% in the air conditioning unit.
Mobile Networks and Applications, 2023
Due to advancements in information technology, the healthcare sector becomes beneficial and provi... more Due to advancements in information technology, the healthcare sector becomes beneficial and provides distinct methods of managing medical data and enhancing the quality of medical services. The advanced e-healthcare applications are mainly based on the Internet of Things (IoT) and cloud computing platforms. In IoT enabled healthcare sector, the IoT devices usually record the patient data and transfer it to the cloud for further processing. Energy efficiency and security are treated as critical problems in designing IoT networks in the healthcare environment. As IoT devices are limited to energy, designing an effective technique to reduce energy utilization is needed. At the same time, secure transmission of medical data also poses a major challenging design issue. This paper presents a novel artificial intelligence with a blockchain scheme for IoT healthcare systems named AIBS-IoTHS. The AIBS-IoTH model aims to achieve secure and energy-efficient data transmission in IoT networks. The IoT devices are primarily used to collect patients' medical data. The AIBS-IoTH model involves a metaheuristic-based modified sunflower optimization-based clustering (MSFOC) technique to achieve energy efficiency. Then, the blockchain empowered secure medical data transmission process is carried out for both inter-cluster and intracluster communication. At last, the Classification Enhancement Generative Adversarial Networks (CEGAN) model performs the diagnostic process on the secured medical data to determine the existence of the diseases. The design of MSFOC and CEGAN techniques shows the novelty of the work. An extensive experimental analysis of the benchmark dataset pointed out the superior performance of the proposed AIBS-IoTH model over the other compared methods.
IFAC-PapersOnLine, Jul 1, 2017
This article proposes an approach based on state observers to recursively estimate the friction o... more This article proposes an approach based on state observers to recursively estimate the friction of pipelines with an extraction. Two specific scenarios, associated with information availability, are treated herein: (1) pressure at the extraction is measurable, (2) extraction measurements are unavailable but the position is known. For both scenarios, measurement availability at the pipeline ends is assumed. The state observers were designed from Liénard type models that represent the fluid dynamics in a pipeline. Such models were extended with the incorporation of the friction factors into their state vectors, such that from the extended models, the observers were constructed. The proposed approach was tested by using data from the commercial software PipelineStudio and experimental data from a laboratory pipeline of water.
Lecture Notes in Computer Science, 2022
The monitoring of control loops in industrial processes is of great importance, considering that ... more The monitoring of control loops in industrial processes is of great importance, considering that the correct operation of the productive procedures is related to the control loops that make up the system. Mostly, industrial processes are composed of a large amount of control loops that interact with each other, that means both are coupled, therefore, if one of the loops does not work properly it can negatively affect the system performance, leading the other loops into setpoints that were not designed for them. It has been found that many responsible causes for poor system performance can be identified by stochastic or deterministic performance indices. These performance indices, from a theoretical perspective, allow making relevant decisions, such as design parameters adjustment of the controllers or actuators maintenance. The most known are the stochastic performance index, it requires only normal operation and knowledge of the process. However, the performance analysis in a lot of cases is not conclusive and can present scale problems. On the contrary, deterministic performance index are easier to interpret, favoring the analysis and deduction of the operator. Nevertheless, it is necessary to perform invasive tests to get them, which makes it impractical.Therefore, this work obtains a deterministic index through a inferential model built with machine learning-based neural networks that use as input the stochastic index acquired throughout recollecting the normal operational data in closed loop and in the knowledge process. furthermore, count with a graphic interface that allows the operator interactively to get performance and robustness values represented in the deterministic indices. The strategy is put on test in a real study case of sensing levels for the industrial control process FESTO® MPS-PA Compact Workstation.
Model Predictive Control (MPC) is a useful tool when controlling processes that handle a large nu... more Model Predictive Control (MPC) is a useful tool when controlling processes that handle a large number of input and output variables. This study presents a comparison of different MPC strategies when they are subjected to control process variables directly. The strategies studied are IMC, GPC, MPC-D, MPC-DR, and DMC. Evaluation of the performance of the controlled loop was performed with the filtering and correlation analysis algorithm (FCOR). The methodology proposed is validated in a Continuous Stirred-Tank Reactor (CSTR) case study. Discrete predictive control demonstrated the best results in this study.El Control predictivo de modelos (MPC) es una herramienta útil para controlar procesos que manejan un gran número de variables de entrada y salida. Este estudio presenta una comparación de diferentes estrategias de MPC cuando son usadas para controlar directamente variables de proceso. Las estrategias estudiadas son IMC, GPC, MPC-D, MPC-DR y DMC. La evaluación del desempeño del laz...
Advances in Mechanics, Nov 10, 2021
Background and aim: Traditional and advanced development methods of prosthetic sockets for limb a... more Background and aim: Traditional and advanced development methods of prosthetic sockets for limb amputations has been well investigated in the literature but some issues still remain with these procedures: previous experience of the prosthetist, large amount of waste material and hardware and software costs. The aim of the technical note was to propose a low-cost method for digitizing the residual limb and generate its corresponded prosthetic socket; and where the physical presence of the amputee is not a requirement. Technique: Three photographs are required as input to generate 2D profiles of the contour of the residual limb, which define its geometric shape, a 3D model is generated using standard CAD operations; and then, the prosthetic socket is generated using a sculpting software. Discussion: Experimental tests validated the prosthetic socket fit in a real case application; the generated prosthetic socket was comparable with the prosthetic socket currently used by the patient. The proposed method presents a virtual prosthetic socket design procedure that use open-source software and CNC low-cost hardware that facilitates its manufacturing; it also opens the possibility to generate prosthetic socket remotely.
2017 IEEE 3rd Colombian Conference on Automatic Control (CCAC), 2017
This paper presents a novel method for diagnosing leaks in a pipeline. The method is based on a d... more This paper presents a novel method for diagnosing leaks in a pipeline. The method is based on a discrete-space version of a Lienard-type model, which describes the fluid behavior in a pipeline only in terms of the flow rate. This latter detail was very useful in designing our method, which was conceived to deal with pipelines solely equipped with flowmeters or in conjunction with pressure sensors, but which are temporarily out of service. The working principle of our methodology is the generation of a set of residuals (each one defined for a specific section of the pipeline) to estimate the position of a leak. The residual near zero will indicate the section where a leak is occurring. The main advantage of our approach is that it does not require pressure measurements, which occurs in most existing methodologies. Thus, to show its potential, we present the results of some tests carried out in simulation.
Advances in Mechanics, Mar 31, 2021
The goal of this research is to look into how undergraduate students used social media and video ... more The goal of this research is to look into how undergraduate students used social media and video apps for online learning during the Covid-19 lockdown. In Andhra Pradesh, online learning is a relatively new phenomenon. Theoretical concepts of Communities of Inquiry (COI) such as cognitive, social and teaching presences were applied to online learning during the pandemic. Survey questionnaire and focus interviews were used to assess online learning. 188 undergraduate students were administered the google forms and 10 undergraduate students provided focus interviews. Using SPSS, crosstabulation and Chi Square tests were done to look for significance. Major findings were that students’ attitude towards critical thinking and triggering debates prove that there is teaching presence. Students were encouraged to question and be critical. 82% approval of students that lecturer possesses knowledge show that students trust teachers as knowledge givers. Lecturers used WhatsApp to share class notes and Zoom app for conducting formal classes. Though one third of the students had lower Internet connectivity, still they were able to connect to their lecturers, though it is a lacuna to be rectified. The lecturers were forced to learn a new paradigm to deal with a new developing context and the lecturers became adequate to the task entrusted to them
Advances in Mechanics, Sep 9, 2021
Control loops are the most critical components in many production processes. In this process, the... more Control loops are the most critical components in many production processes. In this process, the economic yield is strongly linked to the performance of the control loops since aspects such as safety conditions, process quality, and energy and raw material consumption depend on this. However, experience has shown that most of the control loops can be improved by identifying and correcting the causes of the poor performance. The indices to evaluate the performance of the control loops can be divided into two groups, stochastic and deterministic. The most known of the former is the minimum variance index. Stochastic indices only require data collected under normal operating conditions and minimum knowledge of the process, making it possible to evaluate performance online. However, some disadvantages, such as scale and span problems, make performance analysis difficult. The deterministic indices (rise time, settling time, overshoot, phase and gain margins, etc.) are easy to interpret, facilitating the analysis; however, invasive plant tests are necessary to estimate them, making them impractical. Is it possible to link these two approaches? With that question in mind, in this work, it is proposed to build a model to estimate deterministic indices (to evaluate robustness and performance of control loops), considering stochastic indices and some process information as model inputs. This paper shows the procedure to build the inferential model by using machine learning techniques.
Procedia Computer Science, 2020
Buñuelos are a traditional food not only in Colombia but in several parts of the world. They are ... more Buñuelos are a traditional food not only in Colombia but in several parts of the world. They are prepared mainly with cassava starch, cornstarch, cheese, water or milk. The purpose of this work is to determine which factors (trademark, time, temperature, serving size) or interactions between them are important to achieve a major volume of the buñuelos. Thus, a 2 k design is proposed to analyze the factors on the growth rate of buñuelos. The growth rate is calculated taking into account the buñuelos diameter before fried and after fried. The results indicate that the serving size has the principal effect on the response variable but followed by the trademark and some interactions between time and temperature.
Computational Science and Its Applications – ICCSA 2020, 2020
This article describes the primary characteristics of a tool developed to perform a control loop ... more This article describes the primary characteristics of a tool developed to perform a control loop performance assessment, named SELC due to its name in Spanish. With this tool, we expect to increase the reliability and efficiency of productive processes in Colombia’s industry. A brief description of SELC’s functionality and a literature review about the different techniques integrated is presented. Finally, the results and conclusions of the testing phase were presented, performed with both simulated and real data. The actual data comes from an online industrial repository provided by the South African Council for Automation and Control (SACAC).
Model Predictive Control (MPC) is a useful tool when controlling processes that handle a large nu... more Model Predictive Control (MPC) is a useful tool when controlling processes that handle a large number of input and output variables. This study presents a comparison of different MPC strategies when they are subjected to control process variables directly. The strategies studied are IMC, GPC, MPC-D, MPC-DR, and DMC. Evaluation of the performance of the controlled loop was performed with the filtering and correlation analysis algorithm (FCOR). The methodology proposed is validated in a Continuous Stirred-Tank Reactor (CSTR) case study. Discrete predictive control demonstrated the best results in this study.
Applied Condition Monitoring, 2017
This chapter presents the implementation of optimization algorithms to build auxiliary signals th... more This chapter presents the implementation of optimization algorithms to build auxiliary signals that can be injected as inputs into a pipeline in order to estimate—by using state observers—physical parameters such as the friction or the wave speed. For the design of the state observers, we propose to incorporate the parameters to be estimated into the state vector of Lienard-type models of a pipeline such that the observers can be constructed from the modified models. The proposed optimization algorithms guarantee a prescribed observability degree of the modified models by building an optimal input for the identification. The optimality of the input is defined with respect to the minimization of the input energy, whereas the observability through a lower bound for the observability Gramian, which is constructed from the Lienard-type models of the pipeline. The proposed approach to construct auxiliary inputs was experimentally tested by using real data obtained from a laboratory pipeline.
This paper presents a novel non-invasive monitoring method, based on a Liénard-type model (LTM) t... more This paper presents a novel non-invasive monitoring method, based on a Liénard-type model (LTM) to diagnose single and sequential leaks in liquid pipelines. The LTM describes the fluid behavior in a pipeline and is given only in terms of the flow rate. Our method was conceived to be applied in pipelines mono-instrumented with flowmeters or in conjunction with pressure sensors that are temporarily unavailable. The approach conception starts with the discretization of the LTM spatial domain into a prescribed number of sections. Such discretization is performed to obtain a lumped model capable of providing a solution (an internal flow rate) for every section. From this lumped model, a set of algebraic equations (known as residuals) are deduced as the difference between the internal discrete flows and the nominal flow (the mean of the flow rate calculated before the leak). Once the residuals are calculated a principal component analysis (PCA) is carried out to detect a leak occurrence. ...
Computational Science and Its Applications – ICCSA 2020, 2020
This article presents the design of robust control system for the Ball and Beam system, as well a... more This article presents the design of robust control system for the Ball and Beam system, as well as the comparison of their performances with classic control techniques. Two controllers were designed based on Algebraic Riccati Equations for the synthesis of H2 and H∞ controllers and a third one based on Linear Matrix Inequalities techniques for the design of H∞ controllers. The results show that H∞ controllers offer better performance.
Data in Brief, 2020
The dataset presented in this article was collected in a laboratory flow circuit, which was desig... more The dataset presented in this article was collected in a laboratory flow circuit, which was designed to investigate highviscosity flows. The data set is composed of 1200 s (equivalent to 12,0 0 0 samples) of mass flow and pressure measurements taken at five points along the pipeline. The first 300 s were recorded when the flow in the loop was composed only of glycerol. The remaining data were acquired when the flow was composed of a water-glycerol mixture. During the data acquisition, two extractions were produced. The research reported in [1] uses 160 s of the data provided here. This article explains in detail the experimental setup and the principal instruments used for obtaining the dataset. The dataset is in the form of seven columns: Time, Mass Flow, Pressure 1, Pressure 2, Pressure 3, Pressure 4, Pressure 5, in supplementary Excel and Matlab files.
Journal of Marine Science and Engineering, 2020
The purpose of this paper is to provide a structural review of the progress made on the detection... more The purpose of this paper is to provide a structural review of the progress made on the detection and localization of leaks in pipelines by using approaches based on the Kalman filter. To the best of the author’s knowledge, this is the first review on the topic. In particular, it is the first to try to draw the attention of the leak detection community to the important contributions that use the Kalman filter as the core of a computational pipeline monitoring system. Without being exhaustive, the paper gathers the results from different research groups such that these are presented in a unified fashion. For this reason, a classification of the current approaches based on the Kalman filter is proposed. For each of the existing approaches within this classification, the basic concepts, theoretical results, and relations with the other procedures are discussed in detail. The review starts with a short summary of essential ideas about state observers. Then, a brief history of the use of...
International Journal of Information Technology, 2024
The manuscript presents new methodologies for process characterization and control tuning for int... more The manuscript presents new methodologies for process characterization and control tuning for integrated systems. Integrative systems are widespread in the industrial environment. Some control systems for level, pressure, concentration, and temperature are examples. Although many papers have been published on the subject, no standard has been established, so this remains an open problem. The proposed characterization method consists of deriving the response of the integrating system and applying characterization techniques for self-regulated processes. The proposed tuning method is based on deducing tuning equations for a PD control from the λ tuning rules. The performance of the proposed methods is validated through simulation and experimental tests.
Sustainability, 2023
This article is an open access article distributed under the terms and conditions of the Creative... more This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY
Heliyon, 2023
A 2 3 factorial design was performed to analyze the performance of a mini-split air conditioning ... more A 2 3 factorial design was performed to analyze the performance of a mini-split air conditioning system under several psychrometric air conditions at the evaporator inlet, similar to Tropical Caribbean region conditions. In addition, a search for new energy-saving opportunities was performed. The results showed that interactions between the temperature of the air inlet, the humidity of the air inlet, and the fan speed level are significant in the mini-split energy performance under Caribbean climate conditions. Hence, working on an oriented energy savings control strategy is necessary. Therefore, this study recommends developing a fan speed control scheme, generating energy savings of around 10% in the air conditioning unit.
Mobile Networks and Applications, 2023
Due to advancements in information technology, the healthcare sector becomes beneficial and provi... more Due to advancements in information technology, the healthcare sector becomes beneficial and provides distinct methods of managing medical data and enhancing the quality of medical services. The advanced e-healthcare applications are mainly based on the Internet of Things (IoT) and cloud computing platforms. In IoT enabled healthcare sector, the IoT devices usually record the patient data and transfer it to the cloud for further processing. Energy efficiency and security are treated as critical problems in designing IoT networks in the healthcare environment. As IoT devices are limited to energy, designing an effective technique to reduce energy utilization is needed. At the same time, secure transmission of medical data also poses a major challenging design issue. This paper presents a novel artificial intelligence with a blockchain scheme for IoT healthcare systems named AIBS-IoTHS. The AIBS-IoTH model aims to achieve secure and energy-efficient data transmission in IoT networks. The IoT devices are primarily used to collect patients' medical data. The AIBS-IoTH model involves a metaheuristic-based modified sunflower optimization-based clustering (MSFOC) technique to achieve energy efficiency. Then, the blockchain empowered secure medical data transmission process is carried out for both inter-cluster and intracluster communication. At last, the Classification Enhancement Generative Adversarial Networks (CEGAN) model performs the diagnostic process on the secured medical data to determine the existence of the diseases. The design of MSFOC and CEGAN techniques shows the novelty of the work. An extensive experimental analysis of the benchmark dataset pointed out the superior performance of the proposed AIBS-IoTH model over the other compared methods.
IFAC-PapersOnLine, Jul 1, 2017
This article proposes an approach based on state observers to recursively estimate the friction o... more This article proposes an approach based on state observers to recursively estimate the friction of pipelines with an extraction. Two specific scenarios, associated with information availability, are treated herein: (1) pressure at the extraction is measurable, (2) extraction measurements are unavailable but the position is known. For both scenarios, measurement availability at the pipeline ends is assumed. The state observers were designed from Liénard type models that represent the fluid dynamics in a pipeline. Such models were extended with the incorporation of the friction factors into their state vectors, such that from the extended models, the observers were constructed. The proposed approach was tested by using data from the commercial software PipelineStudio and experimental data from a laboratory pipeline of water.
Lecture Notes in Computer Science, 2022
The monitoring of control loops in industrial processes is of great importance, considering that ... more The monitoring of control loops in industrial processes is of great importance, considering that the correct operation of the productive procedures is related to the control loops that make up the system. Mostly, industrial processes are composed of a large amount of control loops that interact with each other, that means both are coupled, therefore, if one of the loops does not work properly it can negatively affect the system performance, leading the other loops into setpoints that were not designed for them. It has been found that many responsible causes for poor system performance can be identified by stochastic or deterministic performance indices. These performance indices, from a theoretical perspective, allow making relevant decisions, such as design parameters adjustment of the controllers or actuators maintenance. The most known are the stochastic performance index, it requires only normal operation and knowledge of the process. However, the performance analysis in a lot of cases is not conclusive and can present scale problems. On the contrary, deterministic performance index are easier to interpret, favoring the analysis and deduction of the operator. Nevertheless, it is necessary to perform invasive tests to get them, which makes it impractical.Therefore, this work obtains a deterministic index through a inferential model built with machine learning-based neural networks that use as input the stochastic index acquired throughout recollecting the normal operational data in closed loop and in the knowledge process. furthermore, count with a graphic interface that allows the operator interactively to get performance and robustness values represented in the deterministic indices. The strategy is put on test in a real study case of sensing levels for the industrial control process FESTO® MPS-PA Compact Workstation.
Model Predictive Control (MPC) is a useful tool when controlling processes that handle a large nu... more Model Predictive Control (MPC) is a useful tool when controlling processes that handle a large number of input and output variables. This study presents a comparison of different MPC strategies when they are subjected to control process variables directly. The strategies studied are IMC, GPC, MPC-D, MPC-DR, and DMC. Evaluation of the performance of the controlled loop was performed with the filtering and correlation analysis algorithm (FCOR). The methodology proposed is validated in a Continuous Stirred-Tank Reactor (CSTR) case study. Discrete predictive control demonstrated the best results in this study.El Control predictivo de modelos (MPC) es una herramienta útil para controlar procesos que manejan un gran número de variables de entrada y salida. Este estudio presenta una comparación de diferentes estrategias de MPC cuando son usadas para controlar directamente variables de proceso. Las estrategias estudiadas son IMC, GPC, MPC-D, MPC-DR y DMC. La evaluación del desempeño del laz...
Advances in Mechanics, Nov 10, 2021
Background and aim: Traditional and advanced development methods of prosthetic sockets for limb a... more Background and aim: Traditional and advanced development methods of prosthetic sockets for limb amputations has been well investigated in the literature but some issues still remain with these procedures: previous experience of the prosthetist, large amount of waste material and hardware and software costs. The aim of the technical note was to propose a low-cost method for digitizing the residual limb and generate its corresponded prosthetic socket; and where the physical presence of the amputee is not a requirement. Technique: Three photographs are required as input to generate 2D profiles of the contour of the residual limb, which define its geometric shape, a 3D model is generated using standard CAD operations; and then, the prosthetic socket is generated using a sculpting software. Discussion: Experimental tests validated the prosthetic socket fit in a real case application; the generated prosthetic socket was comparable with the prosthetic socket currently used by the patient. The proposed method presents a virtual prosthetic socket design procedure that use open-source software and CNC low-cost hardware that facilitates its manufacturing; it also opens the possibility to generate prosthetic socket remotely.
2017 IEEE 3rd Colombian Conference on Automatic Control (CCAC), 2017
This paper presents a novel method for diagnosing leaks in a pipeline. The method is based on a d... more This paper presents a novel method for diagnosing leaks in a pipeline. The method is based on a discrete-space version of a Lienard-type model, which describes the fluid behavior in a pipeline only in terms of the flow rate. This latter detail was very useful in designing our method, which was conceived to deal with pipelines solely equipped with flowmeters or in conjunction with pressure sensors, but which are temporarily out of service. The working principle of our methodology is the generation of a set of residuals (each one defined for a specific section of the pipeline) to estimate the position of a leak. The residual near zero will indicate the section where a leak is occurring. The main advantage of our approach is that it does not require pressure measurements, which occurs in most existing methodologies. Thus, to show its potential, we present the results of some tests carried out in simulation.
Advances in Mechanics, Mar 31, 2021
The goal of this research is to look into how undergraduate students used social media and video ... more The goal of this research is to look into how undergraduate students used social media and video apps for online learning during the Covid-19 lockdown. In Andhra Pradesh, online learning is a relatively new phenomenon. Theoretical concepts of Communities of Inquiry (COI) such as cognitive, social and teaching presences were applied to online learning during the pandemic. Survey questionnaire and focus interviews were used to assess online learning. 188 undergraduate students were administered the google forms and 10 undergraduate students provided focus interviews. Using SPSS, crosstabulation and Chi Square tests were done to look for significance. Major findings were that students’ attitude towards critical thinking and triggering debates prove that there is teaching presence. Students were encouraged to question and be critical. 82% approval of students that lecturer possesses knowledge show that students trust teachers as knowledge givers. Lecturers used WhatsApp to share class notes and Zoom app for conducting formal classes. Though one third of the students had lower Internet connectivity, still they were able to connect to their lecturers, though it is a lacuna to be rectified. The lecturers were forced to learn a new paradigm to deal with a new developing context and the lecturers became adequate to the task entrusted to them
Advances in Mechanics, Sep 9, 2021
Control loops are the most critical components in many production processes. In this process, the... more Control loops are the most critical components in many production processes. In this process, the economic yield is strongly linked to the performance of the control loops since aspects such as safety conditions, process quality, and energy and raw material consumption depend on this. However, experience has shown that most of the control loops can be improved by identifying and correcting the causes of the poor performance. The indices to evaluate the performance of the control loops can be divided into two groups, stochastic and deterministic. The most known of the former is the minimum variance index. Stochastic indices only require data collected under normal operating conditions and minimum knowledge of the process, making it possible to evaluate performance online. However, some disadvantages, such as scale and span problems, make performance analysis difficult. The deterministic indices (rise time, settling time, overshoot, phase and gain margins, etc.) are easy to interpret, facilitating the analysis; however, invasive plant tests are necessary to estimate them, making them impractical. Is it possible to link these two approaches? With that question in mind, in this work, it is proposed to build a model to estimate deterministic indices (to evaluate robustness and performance of control loops), considering stochastic indices and some process information as model inputs. This paper shows the procedure to build the inferential model by using machine learning techniques.
Procedia Computer Science, 2020
Buñuelos are a traditional food not only in Colombia but in several parts of the world. They are ... more Buñuelos are a traditional food not only in Colombia but in several parts of the world. They are prepared mainly with cassava starch, cornstarch, cheese, water or milk. The purpose of this work is to determine which factors (trademark, time, temperature, serving size) or interactions between them are important to achieve a major volume of the buñuelos. Thus, a 2 k design is proposed to analyze the factors on the growth rate of buñuelos. The growth rate is calculated taking into account the buñuelos diameter before fried and after fried. The results indicate that the serving size has the principal effect on the response variable but followed by the trademark and some interactions between time and temperature.
Computational Science and Its Applications – ICCSA 2020, 2020
This article describes the primary characteristics of a tool developed to perform a control loop ... more This article describes the primary characteristics of a tool developed to perform a control loop performance assessment, named SELC due to its name in Spanish. With this tool, we expect to increase the reliability and efficiency of productive processes in Colombia’s industry. A brief description of SELC’s functionality and a literature review about the different techniques integrated is presented. Finally, the results and conclusions of the testing phase were presented, performed with both simulated and real data. The actual data comes from an online industrial repository provided by the South African Council for Automation and Control (SACAC).
Model Predictive Control (MPC) is a useful tool when controlling processes that handle a large nu... more Model Predictive Control (MPC) is a useful tool when controlling processes that handle a large number of input and output variables. This study presents a comparison of different MPC strategies when they are subjected to control process variables directly. The strategies studied are IMC, GPC, MPC-D, MPC-DR, and DMC. Evaluation of the performance of the controlled loop was performed with the filtering and correlation analysis algorithm (FCOR). The methodology proposed is validated in a Continuous Stirred-Tank Reactor (CSTR) case study. Discrete predictive control demonstrated the best results in this study.
Applied Condition Monitoring, 2017
This chapter presents the implementation of optimization algorithms to build auxiliary signals th... more This chapter presents the implementation of optimization algorithms to build auxiliary signals that can be injected as inputs into a pipeline in order to estimate—by using state observers—physical parameters such as the friction or the wave speed. For the design of the state observers, we propose to incorporate the parameters to be estimated into the state vector of Lienard-type models of a pipeline such that the observers can be constructed from the modified models. The proposed optimization algorithms guarantee a prescribed observability degree of the modified models by building an optimal input for the identification. The optimality of the input is defined with respect to the minimization of the input energy, whereas the observability through a lower bound for the observability Gramian, which is constructed from the Lienard-type models of the pipeline. The proposed approach to construct auxiliary inputs was experimentally tested by using real data obtained from a laboratory pipeline.
This paper presents a novel non-invasive monitoring method, based on a Liénard-type model (LTM) t... more This paper presents a novel non-invasive monitoring method, based on a Liénard-type model (LTM) to diagnose single and sequential leaks in liquid pipelines. The LTM describes the fluid behavior in a pipeline and is given only in terms of the flow rate. Our method was conceived to be applied in pipelines mono-instrumented with flowmeters or in conjunction with pressure sensors that are temporarily unavailable. The approach conception starts with the discretization of the LTM spatial domain into a prescribed number of sections. Such discretization is performed to obtain a lumped model capable of providing a solution (an internal flow rate) for every section. From this lumped model, a set of algebraic equations (known as residuals) are deduced as the difference between the internal discrete flows and the nominal flow (the mean of the flow rate calculated before the leak). Once the residuals are calculated a principal component analysis (PCA) is carried out to detect a leak occurrence. ...
Computational Science and Its Applications – ICCSA 2020, 2020
This article presents the design of robust control system for the Ball and Beam system, as well a... more This article presents the design of robust control system for the Ball and Beam system, as well as the comparison of their performances with classic control techniques. Two controllers were designed based on Algebraic Riccati Equations for the synthesis of H2 and H∞ controllers and a third one based on Linear Matrix Inequalities techniques for the design of H∞ controllers. The results show that H∞ controllers offer better performance.
Data in Brief, 2020
The dataset presented in this article was collected in a laboratory flow circuit, which was desig... more The dataset presented in this article was collected in a laboratory flow circuit, which was designed to investigate highviscosity flows. The data set is composed of 1200 s (equivalent to 12,0 0 0 samples) of mass flow and pressure measurements taken at five points along the pipeline. The first 300 s were recorded when the flow in the loop was composed only of glycerol. The remaining data were acquired when the flow was composed of a water-glycerol mixture. During the data acquisition, two extractions were produced. The research reported in [1] uses 160 s of the data provided here. This article explains in detail the experimental setup and the principal instruments used for obtaining the dataset. The dataset is in the form of seven columns: Time, Mass Flow, Pressure 1, Pressure 2, Pressure 3, Pressure 4, Pressure 5, in supplementary Excel and Matlab files.
Journal of Marine Science and Engineering, 2020
The purpose of this paper is to provide a structural review of the progress made on the detection... more The purpose of this paper is to provide a structural review of the progress made on the detection and localization of leaks in pipelines by using approaches based on the Kalman filter. To the best of the author’s knowledge, this is the first review on the topic. In particular, it is the first to try to draw the attention of the leak detection community to the important contributions that use the Kalman filter as the core of a computational pipeline monitoring system. Without being exhaustive, the paper gathers the results from different research groups such that these are presented in a unified fashion. For this reason, a classification of the current approaches based on the Kalman filter is proposed. For each of the existing approaches within this classification, the basic concepts, theoretical results, and relations with the other procedures are discussed in detail. The review starts with a short summary of essential ideas about state observers. Then, a brief history of the use of...
This chapter presents the implementation of optimization algorithms to build auxiliary signals th... more This chapter presents the implementation of optimization algorithms to build auxiliary signals that can be injected as inputs into a pipeline in order to estimate —by using state observers— physical parameters such as the friction or the wave speed. For the design of the state observers, we propose to incorporate the parameters to be estimated into the state vector of Liénard-type models of a pipeline such that the observers can be constructed from the modified models. The proposed optimization algorithms guarantee a prescribed observability degree of the modified models by building an optimal input for the identification. The optimality of the input is defined with respect to the minimization of the input energy, whereas the observability through a lower bound for the observability Gramian, which is constructed from the Liénard-type models of the pipeline. The proposed approach to construct auxiliary inputs was experimentally tested by using real data obtained from a laboratory pipeline.