Pub Date : 2024-06-18DOI: 10.1109/TLA.2024.10562258
Christian René Jiménez Román;Emmanuel Hernández-Mayoral
Today, and mainly in the academic environment, one of the fields of study that is receiving the most attention, in reference to electrical microgrids (MGs), is precisely how to integrate all the elements of the MGs to maintain a stable operation, resilient, reliable and quality. This can be achieved through power converters, which allow for the decentralization of electricity generation, but on the other hand, create the challenge of power quality. In this paper, a model of an MG based on the IEEE 14Bus distribution network is proposed for power quality studies when the MG operates in grid-connected mode. MG model is developed in the software MATLAB-Simulink and the results obtained are compared with the compatibility levels of the IEEE519 standard.
{"title":"Power Quality Analysis of a Hybrid Microgrid based on Renewable Energy Sources","authors":"Christian René Jiménez Román;Emmanuel Hernández-Mayoral","doi":"10.1109/TLA.2024.10562258","DOIUrl":"https://doi.org/10.1109/TLA.2024.10562258","url":null,"abstract":"Today, and mainly in the academic environment, one of the fields of study that is receiving the most attention, in reference to electrical microgrids (MGs), is precisely how to integrate all the elements of the MGs to maintain a stable operation, resilient, reliable and quality. This can be achieved through power converters, which allow for the decentralization of electricity generation, but on the other hand, create the challenge of power quality. In this paper, a model of an MG based on the IEEE 14Bus distribution network is proposed for power quality studies when the MG operates in grid-connected mode. MG model is developed in the software MATLAB-Simulink and the results obtained are compared with the compatibility levels of the IEEE519 standard.","PeriodicalId":55024,"journal":{"name":"IEEE Latin America Transactions","volume":"22 7","pages":"601-611"},"PeriodicalIF":1.3,"publicationDate":"2024-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10562258","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141424682","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-18DOI: 10.1109/TLA.2024.10562262
Shreya Tated;Garv Anand;Dharmendra Sadhwani
In this paper, we propose novel, simplified yet tight approximations of the error probability expressions of numerous digital modulation schemes over a popular alpha-kappa-mu fading channel. With the help of a suitable approximation of the Gaussian Q-function and utilization of Taylor's series expansion, we facilitate the cumbersome integrals which play a key role in simplification of the performance evaluation metrics like symbol error probability (SEP) of various digital modulation schemes. This facilitates cost effective receiver's design making the overall system economically viable. We further illustrate the accuracy of the proposed SEP expressions with the help of the relative error. An insight on the truncation error (and its upper bound) is also highlighted in this paper. We also compute the relative error in the upper bound of the truncation error to further justify the accuracy of the proposed integrals. Moreover, the asymptotic expressions for the integrals are also provided which gives an idea regarding diversity order of the wireless communication systems for large signal to noise ratios.
{"title":"Simplified SEP Approximations of Coherent Digital Modulation Schemes over alpha-kappa-mu Fading Channel","authors":"Shreya Tated;Garv Anand;Dharmendra Sadhwani","doi":"10.1109/TLA.2024.10562262","DOIUrl":"https://doi.org/10.1109/TLA.2024.10562262","url":null,"abstract":"In this paper, we propose novel, simplified yet tight approximations of the error probability expressions of numerous digital modulation schemes over a popular alpha-kappa-mu fading channel. With the help of a suitable approximation of the Gaussian Q-function and utilization of Taylor's series expansion, we facilitate the cumbersome integrals which play a key role in simplification of the performance evaluation metrics like symbol error probability (SEP) of various digital modulation schemes. This facilitates cost effective receiver's design making the overall system economically viable. We further illustrate the accuracy of the proposed SEP expressions with the help of the relative error. An insight on the truncation error (and its upper bound) is also highlighted in this paper. We also compute the relative error in the upper bound of the truncation error to further justify the accuracy of the proposed integrals. Moreover, the asymptotic expressions for the integrals are also provided which gives an idea regarding diversity order of the wireless communication systems for large signal to noise ratios.","PeriodicalId":55024,"journal":{"name":"IEEE Latin America Transactions","volume":"22 7","pages":"566-573"},"PeriodicalIF":1.3,"publicationDate":"2024-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10562262","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141422498","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-18DOI: 10.1109/TLA.2024.10562237
Jinlong Ma;Runfeng Wang
Heterogeneous Information Networks (HINs) contain rich semantic information due to their involvement of multiple types of nodes and edges. Heterogeneous network embedding is used to analyze HINs by embedding network information in low-dimensional node representations. However, existing heterogeneous embedding methods either ignore the implicit topological relationships between distant nodes or neglect nodes features and meta-paths information disparities, which reflects that extracting HIN embeddings from a single view may lead to incomplete information extraction. In order to make the information extraction more complete, we propose a dual-view fusion heterogeneous information network embedding method (DFHE) for recommendation tasks. Specifically, it extracts effective features from HINs from both the remote topology view and the semantic aggregation view: the remote topology view uses a meta-graph-guided random walk to capture the topological relationships between remote nodes and learns embeddings through a graph convolutional network (GCN) encoder, while the semantic aggregation view uses an attention mechanism to learn the importance of different meta-paths, node relationships, and aggregates the semantic information of each meta-path. Experimental results on two real-world network datasets demonstrate an enhancement in recommendation task performance under the application of DFHE, compared to the baseline. This improvement persists even when some meta-paths are deleted, thereby verifying the methods effectiveness.
异构信息网络（HIN）包含丰富的语义信息，因为它们涉及多种类型的节点和边。异构网络嵌入通过将网络信息嵌入到低维节点表示中来分析 HIN。然而，现有的异构嵌入方法要么忽略了远节点之间隐含的拓扑关系，要么忽略了节点特征和元路径信息的差异性，这反映出从单一视图提取 HIN 嵌入可能会导致信息提取不完整。为了使信息提取更加完整，我们提出了一种针对推荐任务的双视图融合异构信息网络嵌入方法（DFHE）。具体来说，它从远程拓扑视图和语义聚合视图中提取异构信息网络的有效特征：远程拓扑视图使用元图引导的随机漫步来捕捉远程节点之间的拓扑关系，并通过图卷积网络（GCN）编码器学习嵌入；而语义聚合视图则使用注意力机制来学习不同元路径、节点关系的重要性，并聚合每个元路径的语义信息。在两个真实世界网络数据集上的实验结果表明，与基线相比，应用 DFHE 后的推荐任务性能有所提高。即使删除了一些元路径，这种改进依然存在，从而验证了该方法的有效性。
{"title":"Dual-View Fusion of Heterogeneous Information Network Embedding for Recommendation","authors":"Jinlong Ma;Runfeng Wang","doi":"10.1109/TLA.2024.10562237","DOIUrl":"https://doi.org/10.1109/TLA.2024.10562237","url":null,"abstract":"Heterogeneous Information Networks (HINs) contain rich semantic information due to their involvement of multiple types of nodes and edges. Heterogeneous network embedding is used to analyze HINs by embedding network information in low-dimensional node representations. However, existing heterogeneous embedding methods either ignore the implicit topological relationships between distant nodes or neglect nodes features and meta-paths information disparities, which reflects that extracting HIN embeddings from a single view may lead to incomplete information extraction. In order to make the information extraction more complete, we propose a dual-view fusion heterogeneous information network embedding method (DFHE) for recommendation tasks. Specifically, it extracts effective features from HINs from both the remote topology view and the semantic aggregation view: the remote topology view uses a meta-graph-guided random walk to capture the topological relationships between remote nodes and learns embeddings through a graph convolutional network (GCN) encoder, while the semantic aggregation view uses an attention mechanism to learn the importance of different meta-paths, node relationships, and aggregates the semantic information of each meta-path. Experimental results on two real-world network datasets demonstrate an enhancement in recommendation task performance under the application of DFHE, compared to the baseline. This improvement persists even when some meta-paths are deleted, thereby verifying the methods effectiveness.","PeriodicalId":55024,"journal":{"name":"IEEE Latin America Transactions","volume":"22 7","pages":"557-565"},"PeriodicalIF":1.3,"publicationDate":"2024-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10562237","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141424680","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-18DOI: 10.1109/TLA.2024.10562244
{"title":"Table of Contents July 2024","authors":"","doi":"10.1109/TLA.2024.10562244","DOIUrl":"https://doi.org/10.1109/TLA.2024.10562244","url":null,"abstract":"","PeriodicalId":55024,"journal":{"name":"IEEE Latin America Transactions","volume":"22 7","pages":"528-528"},"PeriodicalIF":1.3,"publicationDate":"2024-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10562244","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141422579","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-18DOI: 10.1109/TLA.2024.10562238
ANA ISABEL NARVAEZ VILLOTA;ARMANDO JAIME USTARIZ FARFAN;LUIS FERNANDO DIAZ CADAVID
A simulation strategy that enables data transmission between the modeled components of a Smart Grid is proposed in this paper. The proposed simulation strategy, referred to as the connectivity strategy, enables the integration of a physical communication network into Smart Grids simulations. The connectivity strategy comprises three steps: selection of Smart Grids functionality, data transmission over a TCP/IP network, and connectivity strategy evaluation. Each step is described to ensure transparency and reproducibility in Smart Grid simulations, addressing the limitations associated with the lack of specifications when a communication network is implemented into power systems simulations. Furthermore, a Hardware-in-the-loop (HIL) approach is presented for developing and evaluating the proposed connectivity strategy using the HIL technique. Through this approach, the strategy is validated by establishing the communication between simulation and embedded systems via a physical Ethernet network. In a case study, the use of the connectivity strategy to simulate a distribution system automation (DA) functionality is demonstrated. This simulation allows the evaluation of protection schemes in a Smart Grid using MATLAB/Simulink and a Texas Instruments development kit. Results show that the proposed connectivity strategy could estimate the communication delays for different simulation scenarios.
{"title":"A Connectivity Strategy for the Evaluation of Smart Grid Models Based on the Ethernet Technology","authors":"ANA ISABEL NARVAEZ VILLOTA;ARMANDO JAIME USTARIZ FARFAN;LUIS FERNANDO DIAZ CADAVID","doi":"10.1109/TLA.2024.10562238","DOIUrl":"https://doi.org/10.1109/TLA.2024.10562238","url":null,"abstract":"A simulation strategy that enables data transmission between the modeled components of a Smart Grid is proposed in this paper. The proposed simulation strategy, referred to as the connectivity strategy, enables the integration of a physical communication network into Smart Grids simulations. The connectivity strategy comprises three steps: selection of Smart Grids functionality, data transmission over a TCP/IP network, and connectivity strategy evaluation. Each step is described to ensure transparency and reproducibility in Smart Grid simulations, addressing the limitations associated with the lack of specifications when a communication network is implemented into power systems simulations. Furthermore, a Hardware-in-the-loop (HIL) approach is presented for developing and evaluating the proposed connectivity strategy using the HIL technique. Through this approach, the strategy is validated by establishing the communication between simulation and embedded systems via a physical Ethernet network. In a case study, the use of the connectivity strategy to simulate a distribution system automation (DA) functionality is demonstrated. This simulation allows the evaluation of protection schemes in a Smart Grid using MATLAB/Simulink and a Texas Instruments development kit. Results show that the proposed connectivity strategy could estimate the communication delays for different simulation scenarios.","PeriodicalId":55024,"journal":{"name":"IEEE Latin America Transactions","volume":"22 7","pages":"581-590"},"PeriodicalIF":1.3,"publicationDate":"2024-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10562238","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141422497","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-18DOI: 10.1109/TLA.2024.10562261
José Raúl Castro;David Rosales;Carlos Calderon-Cordova
The objective of the present study is to compare three control approaches: ON/OFF control, fuzzy logic, and convolutional neural networks (CNN) implemented in Python for controlling the real-time trajectory tracking of a six-axis industrial robotic arm. This analysis has significant applications in fields that require a high level of precision, such as automated welding and surgical interventions in the medical domain. To evaluate the performance and adaptability of the control models, we will analyze the results using metrics such as Mean Squared Error (MSE), Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), as well as metrics including Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index (SSIM), Jaccard Index, and Pearson's correlation coefficient. The results obtained reveal valuable information about the advantages and limitations of each control approach, highlighting the effectiveness of CNNs in visual perception and trajectory tracking. The ability of CNNs to interpret visual complexities is presented as a key factor for their success in industrial robotics and automation applications, suggesting a promising future for these technologies in dynamic environments.
{"title":"Trajectory control based on On/Off, Fuzzy Logic and Convolutional Neural Networks for an Industrial Robot Arm: an experimental comparison","authors":"José Raúl Castro;David Rosales;Carlos Calderon-Cordova","doi":"10.1109/TLA.2024.10562261","DOIUrl":"https://doi.org/10.1109/TLA.2024.10562261","url":null,"abstract":"The objective of the present study is to compare three control approaches: ON/OFF control, fuzzy logic, and convolutional neural networks (CNN) implemented in Python for controlling the real-time trajectory tracking of a six-axis industrial robotic arm. This analysis has significant applications in fields that require a high level of precision, such as automated welding and surgical interventions in the medical domain. To evaluate the performance and adaptability of the control models, we will analyze the results using metrics such as Mean Squared Error (MSE), Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), as well as metrics including Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index (SSIM), Jaccard Index, and Pearson's correlation coefficient. The results obtained reveal valuable information about the advantages and limitations of each control approach, highlighting the effectiveness of CNNs in visual perception and trajectory tracking. The ability of CNNs to interpret visual complexities is presented as a key factor for their success in industrial robotics and automation applications, suggesting a promising future for these technologies in dynamic environments.","PeriodicalId":55024,"journal":{"name":"IEEE Latin America Transactions","volume":"22 7","pages":"529-538"},"PeriodicalIF":1.3,"publicationDate":"2024-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10562261","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141422514","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-18DOI: 10.1109/TLA.2024.10562259
David R. López-Flores;Pedro R. Acosta-Cano-de-los-Rios;Pedro R. Márquez-Gutierrez;José E. Acosta-Cano-de-los-Rios;Rogelio E. Baray-Arana;Graciela Ramirez-Alonso
This paper proposes an efficient and fast maximum power point tracking (MPPT) algorithm for a wind turbine (WT) connected to a battery bank via a permanent magnet synchronous generator, a three-phase diode rectifier, and a dc-dc boost converter. The algorithm is based on the Takagi-Sugeno (TS) fuzzy system and optimal relation methods and is called TS-MPPT. The fuzzy system computes the converter duty cycle using an input that combines the error and its rate of change. The error is the difference between the reference current computed from the optimal relation and the rectifier current. The methods used in the algorithm resulted in a five-rule TS fuzzy system, which contributed to a fast algorithm in terms of its total execution time (TET): 89.12 s on the F28069M board. The TET attained enabled a synchronized operation of the algorithm with the converter switching frequency. Additionally, the results based on the processor-in-the-loop simulation approach show that the TS-MPPT algorithm achieves an effective MPP tracking process with an energy conversion efficiency of 99.43% and behaves properly when evaluated over the typical WT power curve. Furthermore, the effectiveness and performance of the proposed algorithm are demonstrated against others using the proportional-integral controller, the Mamdani fuzzy method, and a TS fuzzy model from the literature.
{"title":"Efficient and Fast Wind Turbine MPPT Algorithm Using TS Fuzzy Logic and Optimal Relation Methods","authors":"David R. López-Flores;Pedro R. Acosta-Cano-de-los-Rios;Pedro R. Márquez-Gutierrez;José E. Acosta-Cano-de-los-Rios;Rogelio E. Baray-Arana;Graciela Ramirez-Alonso","doi":"10.1109/TLA.2024.10562259","DOIUrl":"https://doi.org/10.1109/TLA.2024.10562259","url":null,"abstract":"This paper proposes an efficient and fast maximum power point tracking (MPPT) algorithm for a wind turbine (WT) connected to a battery bank via a permanent magnet synchronous generator, a three-phase diode rectifier, and a dc-dc boost converter. The algorithm is based on the Takagi-Sugeno (TS) fuzzy system and optimal relation methods and is called TS-MPPT. The fuzzy system computes the converter duty cycle using an input that combines the error and its rate of change. The error is the difference between the reference current computed from the optimal relation and the rectifier current. The methods used in the algorithm resulted in a five-rule TS fuzzy system, which contributed to a fast algorithm in terms of its total execution time (TET): 89.12 s on the F28069M board. The TET attained enabled a synchronized operation of the algorithm with the converter switching frequency. Additionally, the results based on the processor-in-the-loop simulation approach show that the TS-MPPT algorithm achieves an effective MPP tracking process with an energy conversion efficiency of 99.43% and behaves properly when evaluated over the typical WT power curve. Furthermore, the effectiveness and performance of the proposed algorithm are demonstrated against others using the proportional-integral controller, the Mamdani fuzzy method, and a TS fuzzy model from the literature.","PeriodicalId":55024,"journal":{"name":"IEEE Latin America Transactions","volume":"22 7","pages":"612-619"},"PeriodicalIF":1.3,"publicationDate":"2024-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10562259","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141424679","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-15DOI: 10.1109/TLA.2024.10500718
Jose Anibal Arias-Aguilar;Efrén López-Jimenez;Oscar D. Ramírez-Cárdenas;J. Carlos Herrera-Lozada;Nidiyare Hevia-Montiel
In the Yucatan Peninsula, there is a rich diversity of mangroves, notably including Rhizophora mangle, Avicennia germinans, and Laguncularia racemosa. These mangroves contribute to the recovery of degraded natural areas caused by human activities. Additionally, they serve as natural habitats for various animal and plant species. Studies have highlighted the significance of preserving and restoring these species through traditional methods. More recently, the integration of remote sensing and deep learning techniques has allowed for the automated detection and quantification of mangroves. In this study, we explore the application of deep neural network techniques to address computer vision challenges in the field of remote sensing. Specifically, we focus on the detection and quantification of mangroves in remote image sensing, employing transfer learning and fine-tuning with three distinct deep neural network architectures: SegNet-VGG16, U-Net, and Fully Convolutional Network (R-FCN), with the latter two based on the ResNet network. To evaluate the performance of each architecture, we applied key evaluation metrics, including Intersection over Union (IoU), Dice Coefficient, Precision, Sensitivity, and Accuracy. Our results indicate that SegNet-VGG16 exhibited the highest levels of Precision (98.03%) and Accuracy (97.03%), while U-Net outperformed in terms of IoU(96.97%), Dice Coefficient (92.20%), and Sensitivity (96.81%).
{"title":"Mangrove semantic segmentation on aerial images","authors":"Jose Anibal Arias-Aguilar;Efrén López-Jimenez;Oscar D. Ramírez-Cárdenas;J. Carlos Herrera-Lozada;Nidiyare Hevia-Montiel","doi":"10.1109/TLA.2024.10500718","DOIUrl":"https://doi.org/10.1109/TLA.2024.10500718","url":null,"abstract":"In the Yucatan Peninsula, there is a rich diversity of mangroves, notably including Rhizophora mangle, Avicennia germinans, and Laguncularia racemosa. These mangroves contribute to the recovery of degraded natural areas caused by human activities. Additionally, they serve as natural habitats for various animal and plant species. Studies have highlighted the significance of preserving and restoring these species through traditional methods. More recently, the integration of remote sensing and deep learning techniques has allowed for the automated detection and quantification of mangroves. In this study, we explore the application of deep neural network techniques to address computer vision challenges in the field of remote sensing. Specifically, we focus on the detection and quantification of mangroves in remote image sensing, employing transfer learning and fine-tuning with three distinct deep neural network architectures: SegNet-VGG16, U-Net, and Fully Convolutional Network (R-FCN), with the latter two based on the ResNet network. To evaluate the performance of each architecture, we applied key evaluation metrics, including Intersection over Union (IoU), Dice Coefficient, Precision, Sensitivity, and Accuracy. Our results indicate that SegNet-VGG16 exhibited the highest levels of Precision (98.03%) and Accuracy (97.03%), while U-Net outperformed in terms of IoU(96.97%), Dice Coefficient (92.20%), and Sensitivity (96.81%).","PeriodicalId":55024,"journal":{"name":"IEEE Latin America Transactions","volume":"22 5","pages":"379-386"},"PeriodicalIF":1.3,"publicationDate":"2024-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10500718","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140555879","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-15DOI: 10.1109/TLA.2024.10500761
Simon Valencia Lozano;Roger Alexander Martínez Ciro;Francisco Eugenio López Giraldo
Visible light communication (VLC) technology allows data to be transmitted using the optical power emitted by light-emitting diodes (LEDs). The optical receiver usually employs light sensors such as photodiodes, image sensors, photoresistors or solar panel. In the last decades, VLC technology has explored the use of solar panels as data receivers, since they offer the service of power generation, in addition to, a larger surface area to capture the light beam. In this paper, we present the performance evaluation of a VLC system based on solar panel and automatic gain control (AGC) with application in access control systems. Three experiments are proposed to evaluate the uses of the solar panel as information receiver in VLC systems: bandwidth (BW) estimation, VLC system performance and panel viewing angle variation. As a result, we were able to determine a BW of 10 kHz and 190 kHz considering the panel without AGC and with AGC. In the context of digital modulation, a RS-232 module of an Arduino UNO development system was used in order to execute the technique of intensity modulation and direct detection IM/DD. The NRZ line code of the serial interface was used to modulate the electric current of the LED with a maximum symbol rate of 38400 baud with a data effectiveness of 91%. Furthermore, we found that AGC improves the dynamic range of the solar panel's viewing angle and the performance of the VLC system.
{"title":"Evaluation of an AGC for a Solar Panel as a Receiver in a VLC System Applied to Access Control","authors":"Simon Valencia Lozano;Roger Alexander Martínez Ciro;Francisco Eugenio López Giraldo","doi":"10.1109/TLA.2024.10500761","DOIUrl":"https://doi.org/10.1109/TLA.2024.10500761","url":null,"abstract":"Visible light communication (VLC) technology allows data to be transmitted using the optical power emitted by light-emitting diodes (LEDs). The optical receiver usually employs light sensors such as photodiodes, image sensors, photoresistors or solar panel. In the last decades, VLC technology has explored the use of solar panels as data receivers, since they offer the service of power generation, in addition to, a larger surface area to capture the light beam. In this paper, we present the performance evaluation of a VLC system based on solar panel and automatic gain control (AGC) with application in access control systems. Three experiments are proposed to evaluate the uses of the solar panel as information receiver in VLC systems: bandwidth (BW) estimation, VLC system performance and panel viewing angle variation. As a result, we were able to determine a BW of 10 kHz and 190 kHz considering the panel without AGC and with AGC. In the context of digital modulation, a RS-232 module of an Arduino UNO development system was used in order to execute the technique of intensity modulation and direct detection IM/DD. The NRZ line code of the serial interface was used to modulate the electric current of the LED with a maximum symbol rate of 38400 baud with a data effectiveness of 91%. Furthermore, we found that AGC improves the dynamic range of the solar panel's viewing angle and the performance of the VLC system.","PeriodicalId":55024,"journal":{"name":"IEEE Latin America Transactions","volume":"22 5","pages":"428-434"},"PeriodicalIF":1.3,"publicationDate":"2024-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10500761","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140555843","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-15DOI: 10.1109/TLA.2024.10500713
Javier Blanco Rico;Basil Mohammed Al-Hadithi
Event-triggered Control is a modification for digital based control systems that has gain popularity in recent years. This alteration in control algorithms offers advantages like reductions in computation times or even in the requirements of system's hardware bay reducing its processing and communications to the minimum required; allowing for less computation and communication time needed to perform control actions and making them relevant for environments with shared communication mediums or hardware handling multiple processes simultaneously. In this work, a comparison is presented between a classic control scheme and its event triggered counterpart when controlling a Power Source for a simple Lithium Battery Charger. The event triggered versions of the current programmed control and the voltage Proportional-Integral-Derivative controllers are designed to adhere to the maximum admissible errors of the system (voltage and current output ripple) and results are presented to show how the modifications manage to obtain equivalent results to thous of their classic continuous counterparts while minimizing control loop actuation and therefore improve computation and communications performance without hindering system efficiency. This results are specially relevant for such ubiquitous devices in complex systems like electric vehicles or portable consumer electronics, allowing for computation time to be dedicated to other tasks and freeing communication channels for other devices.
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