Pub Date : 2024-07-19DOI: 10.3390/electronics13142857
Taeho Yoo, Byoung Wook Choi
Robots in hazardous environments demand precise and advanced motion control, making extensive simulations crucial for verifying the safety of motion planning. This paper presents a simulation system that enables interactive path editing, allowing for motion planning in a simulated collaborative robot environment and its real-world application. The system includes a simulation host, a control board, and a robot. Unity 3D on a Windows platform provides the simulation environment, while a virtual Linux environment runs ROS2 for execution. Unity sends edited motion paths to ROS2 using the Unity ROS TCP Connector package. The ROS2 MoveIt framework generates trajectories, which are synchronized back to Unity for simulation and real-world validation. To control the six-axis Indy7 collaborative robot, we used the MIO5272 embedded board as an EtherCAT master. Verified trajectories are sent to the target board, synchronizing the robot with the simulation in position and speed. Data are relayed from the host to the MIO5272 using ROS2 and the Data Distribution Service (DDS) to control the robot via EtherCAT communication. The system enables direct simulation and control of various trajectories for robots in hazardous environments. It represents a major advancement by providing safe and optimized trajectories through efficient motion planning and repeated simulations, offering a clear improvement over traditional time-consuming and error-prone teach pendant methods.
{"title":"Interactive Path Editing and Simulation System for Motion Planning and Control of a Collaborative Robot","authors":"Taeho Yoo, Byoung Wook Choi","doi":"10.3390/electronics13142857","DOIUrl":"https://doi.org/10.3390/electronics13142857","url":null,"abstract":"Robots in hazardous environments demand precise and advanced motion control, making extensive simulations crucial for verifying the safety of motion planning. This paper presents a simulation system that enables interactive path editing, allowing for motion planning in a simulated collaborative robot environment and its real-world application. The system includes a simulation host, a control board, and a robot. Unity 3D on a Windows platform provides the simulation environment, while a virtual Linux environment runs ROS2 for execution. Unity sends edited motion paths to ROS2 using the Unity ROS TCP Connector package. The ROS2 MoveIt framework generates trajectories, which are synchronized back to Unity for simulation and real-world validation. To control the six-axis Indy7 collaborative robot, we used the MIO5272 embedded board as an EtherCAT master. Verified trajectories are sent to the target board, synchronizing the robot with the simulation in position and speed. Data are relayed from the host to the MIO5272 using ROS2 and the Data Distribution Service (DDS) to control the robot via EtherCAT communication. The system enables direct simulation and control of various trajectories for robots in hazardous environments. It represents a major advancement by providing safe and optimized trajectories through efficient motion planning and repeated simulations, offering a clear improvement over traditional time-consuming and error-prone teach pendant methods.","PeriodicalId":504598,"journal":{"name":"Electronics","volume":"111 37","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141822677","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-19DOI: 10.3390/electronics13142843
Qing Wang, Yisheng Chen, Yupeng Shen, Meng Li
Ground-penetrating radar (GPR) is often used to detect targets in a construction environment. Due to the different construction environments, the noise exhibits different characteristics on the GPR signal. When the noise is widely distributed on the GPR signal, and its spectrum and the spectrum of the active signal are aliased, it is difficult to separate and suppress the noise by traditional filtering methods. In this paper, we propose a deep learning GPR image noise suppression method based on a recursive guided and dual multi-scale self-attention mechanism neural network (RG-DMSA-NN), which uses a recursive guidance module and a dual multi-scale self-attention mechanism module to improve the feature extraction ability of the image and enhance the robustness and generalization ability in image noise suppression. Through the application of noise suppression on the synthesized test data and the GPR data actually collected by the Macao Science and Technology Museum, the advantages of this method over the traditional filtering, DnCNN and UNet noise suppression methods are demonstrated.
{"title":"Construction Environment Noise Suppression of Ground-Penetrating Radar Signals Based on an RG-DMSA Neural Network","authors":"Qing Wang, Yisheng Chen, Yupeng Shen, Meng Li","doi":"10.3390/electronics13142843","DOIUrl":"https://doi.org/10.3390/electronics13142843","url":null,"abstract":"Ground-penetrating radar (GPR) is often used to detect targets in a construction environment. Due to the different construction environments, the noise exhibits different characteristics on the GPR signal. When the noise is widely distributed on the GPR signal, and its spectrum and the spectrum of the active signal are aliased, it is difficult to separate and suppress the noise by traditional filtering methods. In this paper, we propose a deep learning GPR image noise suppression method based on a recursive guided and dual multi-scale self-attention mechanism neural network (RG-DMSA-NN), which uses a recursive guidance module and a dual multi-scale self-attention mechanism module to improve the feature extraction ability of the image and enhance the robustness and generalization ability in image noise suppression. Through the application of noise suppression on the synthesized test data and the GPR data actually collected by the Macao Science and Technology Museum, the advantages of this method over the traditional filtering, DnCNN and UNet noise suppression methods are demonstrated.","PeriodicalId":504598,"journal":{"name":"Electronics","volume":"106 13","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141820614","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-19DOI: 10.3390/electronics13142853
Junda Zhu, S. Barmada, A. Musolino, Luca Sani
This study introduces a new method for real-time efficiency tracking and stable output power of Dynamic Wireless Power Transfer (DWPT) systems using variable capacitors. A preliminary detailed discussion and an analysis of the DWPT system are carried out to show how the system can optimize power transmission and efficiency when the relative positions of transmitter and receiver change using a dynamic real-time control of the variable capacitors belonging to the compensation networks. This paper shows a detailed model of the DWPT system, including magnetic coupling analysis, circuit dynamics analysis, and efficiency characteristics analysis, in order to modify the control input values as needed. By utilizing a group optimization strategy, the transmission efficiency can be quickly maximized without using a position detection module. Simulation results demonstrate the effectiveness of the proposed method under various dynamic conditions, achieving significant improvements in energy efficiency and transmission reliability of the DWPT system. This research provides a powerful method to increase the overall performances of DWPT systems, which will help the development of future wireless charging technology.
{"title":"Maintain Power Transmission and Efficiency Tracking Using Variable Capacitors for Dynamic WPT Systems","authors":"Junda Zhu, S. Barmada, A. Musolino, Luca Sani","doi":"10.3390/electronics13142853","DOIUrl":"https://doi.org/10.3390/electronics13142853","url":null,"abstract":"This study introduces a new method for real-time efficiency tracking and stable output power of Dynamic Wireless Power Transfer (DWPT) systems using variable capacitors. A preliminary detailed discussion and an analysis of the DWPT system are carried out to show how the system can optimize power transmission and efficiency when the relative positions of transmitter and receiver change using a dynamic real-time control of the variable capacitors belonging to the compensation networks. This paper shows a detailed model of the DWPT system, including magnetic coupling analysis, circuit dynamics analysis, and efficiency characteristics analysis, in order to modify the control input values as needed. By utilizing a group optimization strategy, the transmission efficiency can be quickly maximized without using a position detection module. Simulation results demonstrate the effectiveness of the proposed method under various dynamic conditions, achieving significant improvements in energy efficiency and transmission reliability of the DWPT system. This research provides a powerful method to increase the overall performances of DWPT systems, which will help the development of future wireless charging technology.","PeriodicalId":504598,"journal":{"name":"Electronics","volume":"122 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141822191","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Large language models (LLMs) have gained immense attention and are being increasingly applied in various domains. However, this technological leap forward poses serious security and privacy concerns. This paper explores a novel approach to data stealing attacks by introducing an adaptive method to extract private training data from pre-trained LLMs via backdooring. Our method mainly focuses on the scenario of model customization and is conducted in two phases, including backdoor training and backdoor activation, which allow for the extraction of private information without prior knowledge of the model’s architecture or training data. During the model customization stage, attackers inject the backdoor into the pre-trained LLM by poisoning a small ratio of the training dataset. During the inference stage, attackers can extract private information from the third-party knowledge database by incorporating the pre-defined backdoor trigger. Our method leverages the customization process of LLMs, injecting a stealthy backdoor that can be triggered after deployment to retrieve private data. We demonstrate the effectiveness of our proposed attack through extensive experiments, achieving a notable attack success rate. Extensive experiments demonstrate the effectiveness of our stealing attack in popular LLM architectures, as well as stealthiness during normal inference.
{"title":"Data Stealing Attacks against Large Language Models via Backdooring","authors":"Jiaming He, Guanyu Hou, Xinyue Jia, Yangyang Chen, Wenqi Liao, Yinhang Zhou, Rang Zhou","doi":"10.3390/electronics13142858","DOIUrl":"https://doi.org/10.3390/electronics13142858","url":null,"abstract":"Large language models (LLMs) have gained immense attention and are being increasingly applied in various domains. However, this technological leap forward poses serious security and privacy concerns. This paper explores a novel approach to data stealing attacks by introducing an adaptive method to extract private training data from pre-trained LLMs via backdooring. Our method mainly focuses on the scenario of model customization and is conducted in two phases, including backdoor training and backdoor activation, which allow for the extraction of private information without prior knowledge of the model’s architecture or training data. During the model customization stage, attackers inject the backdoor into the pre-trained LLM by poisoning a small ratio of the training dataset. During the inference stage, attackers can extract private information from the third-party knowledge database by incorporating the pre-defined backdoor trigger. Our method leverages the customization process of LLMs, injecting a stealthy backdoor that can be triggered after deployment to retrieve private data. We demonstrate the effectiveness of our proposed attack through extensive experiments, achieving a notable attack success rate. Extensive experiments demonstrate the effectiveness of our stealing attack in popular LLM architectures, as well as stealthiness during normal inference.","PeriodicalId":504598,"journal":{"name":"Electronics","volume":"111 46","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141822672","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-19DOI: 10.3390/electronics13142842
Georgios Kostopoulos, Gregory Davrazos, S. Kotsiantis
This survey article provides a comprehensive overview of the evolving landscape of Explainable Artificial Intelligence (XAI) in Decision Support Systems (DSSs). As Artificial Intelligence (AI) continues to play a crucial role in decision-making processes across various domains, the need for transparency, interpretability, and trust becomes paramount. This survey examines the methodologies, applications, challenges, and future research directions in the integration of explainability within AI-based Decision Support Systems. Through an in-depth analysis of current research and practical implementations, this article aims to guide researchers, practitioners, and decision-makers in navigating the intricate landscape of XAI-based DSSs. These systems assist end-users in their decision-making, providing a full picture of how a decision was made and boosting trust. Furthermore, a methodical taxonomy of the current methodologies is proposed and representative works are presented and discussed. The analysis of recent studies reveals that there is a growing interest in applying XDSSs in fields such as medical diagnosis, manufacturing, and education, to name a few, since they smooth down the trade-off between accuracy and explainability, boost confidence, and also validate decisions.
{"title":"Explainable Artificial Intelligence-Based Decision Support Systems: A Recent Review","authors":"Georgios Kostopoulos, Gregory Davrazos, S. Kotsiantis","doi":"10.3390/electronics13142842","DOIUrl":"https://doi.org/10.3390/electronics13142842","url":null,"abstract":"This survey article provides a comprehensive overview of the evolving landscape of Explainable Artificial Intelligence (XAI) in Decision Support Systems (DSSs). As Artificial Intelligence (AI) continues to play a crucial role in decision-making processes across various domains, the need for transparency, interpretability, and trust becomes paramount. This survey examines the methodologies, applications, challenges, and future research directions in the integration of explainability within AI-based Decision Support Systems. Through an in-depth analysis of current research and practical implementations, this article aims to guide researchers, practitioners, and decision-makers in navigating the intricate landscape of XAI-based DSSs. These systems assist end-users in their decision-making, providing a full picture of how a decision was made and boosting trust. Furthermore, a methodical taxonomy of the current methodologies is proposed and representative works are presented and discussed. The analysis of recent studies reveals that there is a growing interest in applying XDSSs in fields such as medical diagnosis, manufacturing, and education, to name a few, since they smooth down the trade-off between accuracy and explainability, boost confidence, and also validate decisions.","PeriodicalId":504598,"journal":{"name":"Electronics","volume":" 1249","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141822836","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In recent years, with the rapid development of unmanned aerial vehicle (UAV) technology, multi-view 3D reconstruction has once again become a hot spot in computer vision. Incremental Structure From Motion (SFM) is currently the most prevalent reconstruction pipeline, but it still faces challenges in reconstruction efficiency, accuracy, and feature matching. In this paper, we use deep learning algorithms for feature matching to obtain more accurate matching point pairs. Moreover, we adopted the improved Gauss–Newton (GN) method, which not only avoids numerical divergence but also accelerates the speed of bundle adjustment (BA). Then, the sparse point cloud reconstructed by SFM and the original image are used as the input of the depth estimation network to predict the depth map of each image. Finally, the depth map is fused to complete the reconstruction of dense point clouds. After experimental verification, the reconstructed dense point clouds have rich details and clear textures, and the integrity, overall accuracy, and reconstruction efficiency of the point clouds have been improved.
{"title":"Incremental SFM 3D Reconstruction Based on Deep Learning","authors":"Lei Liu, Congzheng Wang, Chuncheng Feng, Wanqi Gong, Lingyi Zhang, Libin Liao, Chang Feng","doi":"10.3390/electronics13142850","DOIUrl":"https://doi.org/10.3390/electronics13142850","url":null,"abstract":"In recent years, with the rapid development of unmanned aerial vehicle (UAV) technology, multi-view 3D reconstruction has once again become a hot spot in computer vision. Incremental Structure From Motion (SFM) is currently the most prevalent reconstruction pipeline, but it still faces challenges in reconstruction efficiency, accuracy, and feature matching. In this paper, we use deep learning algorithms for feature matching to obtain more accurate matching point pairs. Moreover, we adopted the improved Gauss–Newton (GN) method, which not only avoids numerical divergence but also accelerates the speed of bundle adjustment (BA). Then, the sparse point cloud reconstructed by SFM and the original image are used as the input of the depth estimation network to predict the depth map of each image. Finally, the depth map is fused to complete the reconstruction of dense point clouds. After experimental verification, the reconstructed dense point clouds have rich details and clear textures, and the integrity, overall accuracy, and reconstruction efficiency of the point clouds have been improved.","PeriodicalId":504598,"journal":{"name":"Electronics","volume":"120 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141820932","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-19DOI: 10.3390/electronics13142848
W. Tarng, Yu-Jung Wu, Li-Yuan Ye, Chun-Wei Tang, Yun-Chen Lu, Tzu-Ling Wang, Chien-Lung Li
Robotics includes complex mathematical calculations and coordinate transformations in forward and inverse kinematics, path planning, and robot dynamics. Students may experience a high cognitive load and lose learning motivation because robotics can be complex and challenging to understand. This study applied virtual reality (VR) technology in robotics education to simplify and visualize complex robot kinematics, aiming to increase learning motivation and reduce cognitive load. This study incorporated real and virtual robot control to develop an integrated robot learning system. This system enables learners to control the digital twin of a physical robot and observe the synchronized motion of both the virtual and physical robots. Users can operate the virtual robot to achieve the target position by setting joint parameters or using values calculated from inverse kinematics. They can also understand the principle of digital twins by observing the synchronous motion of both robots. A teaching experiment was conducted to explore the performance of applying VR in robotics education and its impacts on cognitive load and learning motivation. The system was improved based on user responses to facilitate subsequent promotional activities. VR can transform complex robotics into easily understandable learning experiences and provide an interactive user interface, making the system a suitable learning tool for STEM education.
{"title":"Application of Virtual Reality in Developing the Digital Twin for an Integrated Robot Learning System","authors":"W. Tarng, Yu-Jung Wu, Li-Yuan Ye, Chun-Wei Tang, Yun-Chen Lu, Tzu-Ling Wang, Chien-Lung Li","doi":"10.3390/electronics13142848","DOIUrl":"https://doi.org/10.3390/electronics13142848","url":null,"abstract":"Robotics includes complex mathematical calculations and coordinate transformations in forward and inverse kinematics, path planning, and robot dynamics. Students may experience a high cognitive load and lose learning motivation because robotics can be complex and challenging to understand. This study applied virtual reality (VR) technology in robotics education to simplify and visualize complex robot kinematics, aiming to increase learning motivation and reduce cognitive load. This study incorporated real and virtual robot control to develop an integrated robot learning system. This system enables learners to control the digital twin of a physical robot and observe the synchronized motion of both the virtual and physical robots. Users can operate the virtual robot to achieve the target position by setting joint parameters or using values calculated from inverse kinematics. They can also understand the principle of digital twins by observing the synchronous motion of both robots. A teaching experiment was conducted to explore the performance of applying VR in robotics education and its impacts on cognitive load and learning motivation. The system was improved based on user responses to facilitate subsequent promotional activities. VR can transform complex robotics into easily understandable learning experiences and provide an interactive user interface, making the system a suitable learning tool for STEM education.","PeriodicalId":504598,"journal":{"name":"Electronics","volume":" 16","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141823052","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-19DOI: 10.3390/electronics13142859
Thomas F. Arciuolo, M. Faezipour, Xingguo Xiong
In the not-too-distant future, humans will return to the Moon and step foot for the first time on Mars. Eventually, humanity will colonize these celestial bodies, where living and working will be commonplace. Energy is fundamental to all life. The energy that people use to sustain themselves on Earth, and in particular on these other worlds, is the integrated, safe production of electrical power, day and night. This paper proposes a radically new solution to this problem: Solar Tracking by day and a Solar Rechargeable Calcium Oxide Chemical Thermoelectric Reactor by night. Called the “Robotic End Effector for Lunar and Martian Geological Exploration of Space” (REEGES) Day/Night Power Generator Station, this form of thermoelectric power generation is mathematically modeled, simulation is performed, and a concept model design is demonstrated in this paper. The results of the presented simulation show the maximum total system output capability is 9.89 V, 6.66 A, and 65.9 W, with an operating time of up to 12 h, through a scalable design. This research provides instructions to the Space Research Community on a complete and novel development methodology for creating fully customized, configurable, safe, and reliable solar/thermoelectric day/night power generators, specifically meant for use on the Moon and Mars, using the Proportional-Integral-Derivative++ (PID++) Humanoid Motion Control Algorithm for its operation on a computationally lightweight microcontroller.
{"title":"Day/Night Power Generator Station: A New Power Generation Approach for Lunar and Martian Space Exploration","authors":"Thomas F. Arciuolo, M. Faezipour, Xingguo Xiong","doi":"10.3390/electronics13142859","DOIUrl":"https://doi.org/10.3390/electronics13142859","url":null,"abstract":"In the not-too-distant future, humans will return to the Moon and step foot for the first time on Mars. Eventually, humanity will colonize these celestial bodies, where living and working will be commonplace. Energy is fundamental to all life. The energy that people use to sustain themselves on Earth, and in particular on these other worlds, is the integrated, safe production of electrical power, day and night. This paper proposes a radically new solution to this problem: Solar Tracking by day and a Solar Rechargeable Calcium Oxide Chemical Thermoelectric Reactor by night. Called the “Robotic End Effector for Lunar and Martian Geological Exploration of Space” (REEGES) Day/Night Power Generator Station, this form of thermoelectric power generation is mathematically modeled, simulation is performed, and a concept model design is demonstrated in this paper. The results of the presented simulation show the maximum total system output capability is 9.89 V, 6.66 A, and 65.9 W, with an operating time of up to 12 h, through a scalable design. This research provides instructions to the Space Research Community on a complete and novel development methodology for creating fully customized, configurable, safe, and reliable solar/thermoelectric day/night power generators, specifically meant for use on the Moon and Mars, using the Proportional-Integral-Derivative++ (PID++) Humanoid Motion Control Algorithm for its operation on a computationally lightweight microcontroller.","PeriodicalId":504598,"journal":{"name":"Electronics","volume":"4 11","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141822371","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-19DOI: 10.3390/electronics13142854
Renxi Gong, Tao Liu, Yan Qin, Jiawei Xu, Zhihuan Wei
The single-phase photovoltaic energy storage inverter represents a pivotal component within photovoltaic energy storage systems. Its operational dynamics are often intricate due to its inherent characteristics and the prevalent usage of nonlinear switching elements, leading to nonlinear characteristic bifurcation such as bifurcation and chaos. In this paper, a deep investigation of a single-phase H-bridge photovoltaic energy storage inverter under proportional–integral (PI) control is made, and a sinusoidal delayed feedback control (SDFC) strategy to mitigate the nonlinear characteristics is proposed. A frequency domain mapping model of the system is established, then, by analyzing the Jacobian matrix and equilibrium points, the bifurcation diagram is formed, and finally, the stable operational domains are determined under double and triple bifurcation parameters. Through simulation experiments, the efficacy of this strategy is validated. The findings show that through the control strategy, the stable operational envelope of the inverter can be greatly expanded and the nonlinear dynamic phenomena can be notably suppressed.
单相光伏储能逆变器是光伏储能系统中的关键部件。由于其固有特性和非线性开关元件的普遍使用，其运行动力学往往错综复杂，从而导致分岔和混沌等非线性特性分岔。本文对比例积分（PI）控制下的单相 H 桥光伏储能逆变器进行了深入研究，并提出了一种正弦延迟反馈控制（SDFC）策略来缓解非线性特性。建立了系统的频域映射模型，然后通过分析雅各布矩阵和平衡点，形成了分岔图，最后确定了双分岔和三分岔参数下的稳定工作域。通过模拟实验，验证了这一策略的有效性。研究结果表明，通过该控制策略，逆变器的稳定工作包络线可以大大扩展，非线性动态现象也会得到明显抑制。
{"title":"A Novel Chaos Control Strategy for a Single-Phase Photovoltaic Energy Storage Inverter","authors":"Renxi Gong, Tao Liu, Yan Qin, Jiawei Xu, Zhihuan Wei","doi":"10.3390/electronics13142854","DOIUrl":"https://doi.org/10.3390/electronics13142854","url":null,"abstract":"The single-phase photovoltaic energy storage inverter represents a pivotal component within photovoltaic energy storage systems. Its operational dynamics are often intricate due to its inherent characteristics and the prevalent usage of nonlinear switching elements, leading to nonlinear characteristic bifurcation such as bifurcation and chaos. In this paper, a deep investigation of a single-phase H-bridge photovoltaic energy storage inverter under proportional–integral (PI) control is made, and a sinusoidal delayed feedback control (SDFC) strategy to mitigate the nonlinear characteristics is proposed. A frequency domain mapping model of the system is established, then, by analyzing the Jacobian matrix and equilibrium points, the bifurcation diagram is formed, and finally, the stable operational domains are determined under double and triple bifurcation parameters. Through simulation experiments, the efficacy of this strategy is validated. The findings show that through the control strategy, the stable operational envelope of the inverter can be greatly expanded and the nonlinear dynamic phenomena can be notably suppressed.","PeriodicalId":504598,"journal":{"name":"Electronics","volume":"105 22","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141820658","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Given power fluctuations from near-land offshore wind farms, this article designs a coordinated control strategy for cascaded hybrid DC transmission. To suppress the frequency disturbances when wind power varies, supplementary active power control schemes are proposed, in which the coordinated DC voltage control strategy is also considered in order to keep DC voltage stable when the supplementary control prompts a voltage-sourced converter overload. Simultaneously, to further improve wind farm-side AC voltage stability, a dynamic limiter is added in the coordinated control, which can make a voltage-sourced converter release more reactive power when a fault happens. Thereby, the stability of DC-side voltage and active power and AC-side frequency and voltage can all be enhanced through the proposed coordinated scheme. Finally, the electromagnetic transient model of the hybrid high-voltage direct current with renewable power is established using PSCAD X4.6.2 software, and the simulation example is carried out with the model to verify the scheme proposed in this article.
{"title":"An AC-DC Coordinated Scheme for Cascaded Hybrid High-Voltage Direct Current to Suppress Wind Power Fluctuations","authors":"Tingshan Zhou, Qian Li, Yufeng Xu, Yizheng Zhao, Deming Liu, Dong Liu","doi":"10.3390/electronics13142847","DOIUrl":"https://doi.org/10.3390/electronics13142847","url":null,"abstract":"Given power fluctuations from near-land offshore wind farms, this article designs a coordinated control strategy for cascaded hybrid DC transmission. To suppress the frequency disturbances when wind power varies, supplementary active power control schemes are proposed, in which the coordinated DC voltage control strategy is also considered in order to keep DC voltage stable when the supplementary control prompts a voltage-sourced converter overload. Simultaneously, to further improve wind farm-side AC voltage stability, a dynamic limiter is added in the coordinated control, which can make a voltage-sourced converter release more reactive power when a fault happens. Thereby, the stability of DC-side voltage and active power and AC-side frequency and voltage can all be enhanced through the proposed coordinated scheme. Finally, the electromagnetic transient model of the hybrid high-voltage direct current with renewable power is established using PSCAD X4.6.2 software, and the simulation example is carried out with the model to verify the scheme proposed in this article.","PeriodicalId":504598,"journal":{"name":"Electronics","volume":" 11","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141822528","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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