Pub Date : 2023-07-27DOI: 10.1109/ICSSE58758.2023.10227200
Ushik Shrestha Khwakhali, Thanh Ngoc Nguyen, M. Dinh, L. Nguyen, Thanh Pham, Quang Tran
This paper explores the significant impact of smart production on human resource empowerment and opportunity seizing. Smart production is a technological transformation that integrates advanced technologies like computer aided manufacturing, artificial intelligence, machine learning, robotics, and the internet of things. The research findings provide empirical evidence that smart production can facilitate human resource empowerment which literally means providing employees with the necessary tools, skills, and knowledge to perform their jobs efficiently, increase their income and well-being, and reduce labour accidents. Smart production also open up new business opportunities, enabling businesses to find customers in other market segments.
{"title":"Leverage Smart Production for Opportunities Seizing and Employee Empowerment","authors":"Ushik Shrestha Khwakhali, Thanh Ngoc Nguyen, M. Dinh, L. Nguyen, Thanh Pham, Quang Tran","doi":"10.1109/ICSSE58758.2023.10227200","DOIUrl":"https://doi.org/10.1109/ICSSE58758.2023.10227200","url":null,"abstract":"This paper explores the significant impact of smart production on human resource empowerment and opportunity seizing. Smart production is a technological transformation that integrates advanced technologies like computer aided manufacturing, artificial intelligence, machine learning, robotics, and the internet of things. The research findings provide empirical evidence that smart production can facilitate human resource empowerment which literally means providing employees with the necessary tools, skills, and knowledge to perform their jobs efficiently, increase their income and well-being, and reduce labour accidents. Smart production also open up new business opportunities, enabling businesses to find customers in other market segments.","PeriodicalId":280745,"journal":{"name":"2023 International Conference on System Science and Engineering (ICSSE)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128648120","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 : 2023-07-27DOI: 10.1109/ICSSE58758.2023.10227177
V. Trương, Van Minh Nguyen Luong, Quang Thong Nguyen, Thanh-Hai Quach
In this paper presents a New Buck-Boost structure with high performance, suitable for practical applications. The performance is evaluated based on direct measurements of voltage and current in the circuit, minimizing errors and producing accurate results. The article compares the proposed Buck-Boost converter with two other converters, the Transformerless Buck-Boost Converter With Positive Output Voltage (Positive Step Buck-Boost - PSBB) and the Negative Output Buck-Boost Converter With Wide Conversion Ratio (Negative Step Buck-Boost - NSBB). The results show that the proposed converter outperforms the other two converters in terms of performance. To validate the proposed design, simulation results obtained using PSIM software are presented in the form of graphs.
{"title":"A New Buck-Boost Converter Structure With Improved Efficiency","authors":"V. Trương, Van Minh Nguyen Luong, Quang Thong Nguyen, Thanh-Hai Quach","doi":"10.1109/ICSSE58758.2023.10227177","DOIUrl":"https://doi.org/10.1109/ICSSE58758.2023.10227177","url":null,"abstract":"In this paper presents a New Buck-Boost structure with high performance, suitable for practical applications. The performance is evaluated based on direct measurements of voltage and current in the circuit, minimizing errors and producing accurate results. The article compares the proposed Buck-Boost converter with two other converters, the Transformerless Buck-Boost Converter With Positive Output Voltage (Positive Step Buck-Boost - PSBB) and the Negative Output Buck-Boost Converter With Wide Conversion Ratio (Negative Step Buck-Boost - NSBB). The results show that the proposed converter outperforms the other two converters in terms of performance. To validate the proposed design, simulation results obtained using PSIM software are presented in the form of graphs.","PeriodicalId":280745,"journal":{"name":"2023 International Conference on System Science and Engineering (ICSSE)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114668614","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 : 2023-07-27DOI: 10.1109/ICSSE58758.2023.10227220
Manh Tuyen Trinh, Van Tinh Nguyen
This paper presents an application of distributed nonlinear model predictive fault-tolerant controller (NMPFC) for leader- following formation tracking control in both free-fault and faulty case. The fault detection and diagnosis module integrated in each robot is based on an Extended Kalman filter (EKF) to estimate multiple faults occurring in that robot. The proposed solution is validated through simulation under Matlab-Simulink for mobile-robot systems.
{"title":"An Observer-Based Distributed Nonlinear Model Predictive Fault-Tolerant Control for Leader-Following Formation Tracking Control","authors":"Manh Tuyen Trinh, Van Tinh Nguyen","doi":"10.1109/ICSSE58758.2023.10227220","DOIUrl":"https://doi.org/10.1109/ICSSE58758.2023.10227220","url":null,"abstract":"This paper presents an application of distributed nonlinear model predictive fault-tolerant controller (NMPFC) for leader- following formation tracking control in both free-fault and faulty case. The fault detection and diagnosis module integrated in each robot is based on an Extended Kalman filter (EKF) to estimate multiple faults occurring in that robot. The proposed solution is validated through simulation under Matlab-Simulink for mobile-robot systems.","PeriodicalId":280745,"journal":{"name":"2023 International Conference on System Science and Engineering (ICSSE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125800460","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 : 2023-07-27DOI: 10.1109/ICSSE58758.2023.10227214
Hoang Minh Vu Nguyen, Trieu Tan Phung, T. N. Le, N. A. Nguyen, Quang Tien Nguyen, Phuong Nam Nguyen
Making accurate load-shedding decisions helps to reduce losses for customers and the power system. This article proposes an improved Artificial Neural Network (ANN) application using the Bacteria Foraging optimization (BFO) algorithm. The proposed load-shedding model uses ANN to identify load-shedding/non-shedding events combined with optimized load-shedding calculations to ensure system stability within allowable limits. The proposed neural network has been experimented on the IEEE 37-bus system, and its performance is compared with conventional neural networks and those improved by other algorithms. The results show that BFO provides high data identification efficiency with minimal training time, making it a potential solution for load-shedding forecasting.
{"title":"Using an improved Neural Network with Bacterial Foraging Optimization algorithm for Load Shedding","authors":"Hoang Minh Vu Nguyen, Trieu Tan Phung, T. N. Le, N. A. Nguyen, Quang Tien Nguyen, Phuong Nam Nguyen","doi":"10.1109/ICSSE58758.2023.10227214","DOIUrl":"https://doi.org/10.1109/ICSSE58758.2023.10227214","url":null,"abstract":"Making accurate load-shedding decisions helps to reduce losses for customers and the power system. This article proposes an improved Artificial Neural Network (ANN) application using the Bacteria Foraging optimization (BFO) algorithm. The proposed load-shedding model uses ANN to identify load-shedding/non-shedding events combined with optimized load-shedding calculations to ensure system stability within allowable limits. The proposed neural network has been experimented on the IEEE 37-bus system, and its performance is compared with conventional neural networks and those improved by other algorithms. The results show that BFO provides high data identification efficiency with minimal training time, making it a potential solution for load-shedding forecasting.","PeriodicalId":280745,"journal":{"name":"2023 International Conference on System Science and Engineering (ICSSE)","volume":"110 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122593887","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 : 2023-07-27DOI: 10.1109/ICSSE58758.2023.10227153
Hai-Yen Pham, Van-Tinh Nguyen, T. Bui
This paper is concerned with a novel adaptive fault tolerant control (FTC) method for a wheeled mobile robot under actuator fault and dead zone to track a predefined trajectory. Prior knowledge of actuator fault and a dead zone is not needed. Although belonging to the passive category, the proposed FTC method does not require a robust component that causes a chattering phenomenon to overcome the actuator fault. Instead, the actuator fault is dealt with by a unique technique. The convergence of tracking errors is ensured by Lyapunov criterion. The merit and effectiveness of the proposed method are confirmed via simulation results.
{"title":"An Adaptive Fault Tolerant Control for a Wheeled Mobile Robot under Actuator Fault and Dead Zone*","authors":"Hai-Yen Pham, Van-Tinh Nguyen, T. Bui","doi":"10.1109/ICSSE58758.2023.10227153","DOIUrl":"https://doi.org/10.1109/ICSSE58758.2023.10227153","url":null,"abstract":"This paper is concerned with a novel adaptive fault tolerant control (FTC) method for a wheeled mobile robot under actuator fault and dead zone to track a predefined trajectory. Prior knowledge of actuator fault and a dead zone is not needed. Although belonging to the passive category, the proposed FTC method does not require a robust component that causes a chattering phenomenon to overcome the actuator fault. Instead, the actuator fault is dealt with by a unique technique. The convergence of tracking errors is ensured by Lyapunov criterion. The merit and effectiveness of the proposed method are confirmed via simulation results.","PeriodicalId":280745,"journal":{"name":"2023 International Conference on System Science and Engineering (ICSSE)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125594192","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 : 2023-07-27DOI: 10.1109/ICSSE58758.2023.10227209
D. C. Huynh, Loc D. Ho, M. Dunnigan, Corina Barbalata
Exploitation and utilization of electrical energy from solar energy have become popular under the strong technological development of solar photovoltaic (SPV) cells. However, during the power generation process of an SPV array, the efficiency of converting solar energy into electrical energy is significantly affected by natural conditions such as irradiation variation, partial shading, snow, ice, and dust. This paper proposes an advanced artificial bee colony (ABC) algorithm-based reconfiguration approach to overcome these effects as well as to ensure optimal power generation. The proposal-based achievements are compared with those using a genetic algorithm (GA), a particle swarm optimization (PSO) algorithm, and an ABC algorithm to validate the effectiveness of the proposed reconfiguration approach in the performance improvement of the SPV array-based power generation.
{"title":"Solar Photovoltaic Array Reconfiguration for Optimizing Harvested Power Using an Advanced Artificial Bee Colony Algorithm","authors":"D. C. Huynh, Loc D. Ho, M. Dunnigan, Corina Barbalata","doi":"10.1109/ICSSE58758.2023.10227209","DOIUrl":"https://doi.org/10.1109/ICSSE58758.2023.10227209","url":null,"abstract":"Exploitation and utilization of electrical energy from solar energy have become popular under the strong technological development of solar photovoltaic (SPV) cells. However, during the power generation process of an SPV array, the efficiency of converting solar energy into electrical energy is significantly affected by natural conditions such as irradiation variation, partial shading, snow, ice, and dust. This paper proposes an advanced artificial bee colony (ABC) algorithm-based reconfiguration approach to overcome these effects as well as to ensure optimal power generation. The proposal-based achievements are compared with those using a genetic algorithm (GA), a particle swarm optimization (PSO) algorithm, and an ABC algorithm to validate the effectiveness of the proposed reconfiguration approach in the performance improvement of the SPV array-based power generation.","PeriodicalId":280745,"journal":{"name":"2023 International Conference on System Science and Engineering (ICSSE)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129995287","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 : 2023-07-27DOI: 10.1109/ICSSE58758.2023.10227075
Van‐Phong Vu, T. Nguyen, Xuan-Sang Nguyen, Van-Tung Le, V. Ngo, D. Pham, Hoang Kim Uyen
In this paper, the problems related to cooperative control for the multiple mobile robot system (MMRS) is presented. The LIDAR sensor is employed to obtain the 2D map of the indoor space. The formation control and the leader-following algorithm are applied to control the MMRS moving in a specific formation. Additionally, this paper considers the scenario that the MMRS has to move to several targets in the indoor space with many obstacles. Therefore, the indoor travelling salesman problem-based Ant Colony Optimization (ACO) is studied in this work to determine the optimal moving path of the MMRS. To prove the effectiveness and merit of the proposed methods, the simulation results are provided in this article.
{"title":"Optimal Multi-Target Path Planing Control for Multiple Mobile Robot System","authors":"Van‐Phong Vu, T. Nguyen, Xuan-Sang Nguyen, Van-Tung Le, V. Ngo, D. Pham, Hoang Kim Uyen","doi":"10.1109/ICSSE58758.2023.10227075","DOIUrl":"https://doi.org/10.1109/ICSSE58758.2023.10227075","url":null,"abstract":"In this paper, the problems related to cooperative control for the multiple mobile robot system (MMRS) is presented. The LIDAR sensor is employed to obtain the 2D map of the indoor space. The formation control and the leader-following algorithm are applied to control the MMRS moving in a specific formation. Additionally, this paper considers the scenario that the MMRS has to move to several targets in the indoor space with many obstacles. Therefore, the indoor travelling salesman problem-based Ant Colony Optimization (ACO) is studied in this work to determine the optimal moving path of the MMRS. To prove the effectiveness and merit of the proposed methods, the simulation results are provided in this article.","PeriodicalId":280745,"journal":{"name":"2023 International Conference on System Science and Engineering (ICSSE)","volume":"42 4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133203921","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 : 2023-07-27DOI: 10.1109/ICSSE58758.2023.10227198
D. Tran, Tan Luc Nguyen, Thien Tranh Ha, Hung Hoang
This paper mentions two synchronous control algorithms for a dual 3-degree-of-freedom (3-DOF) manipulator robot based on the CAN BUS network, including the master-slave approach (MSA) and cross-coupling control (CCC) algorithms. In the MSA synchronization algorithm, the set trajectory of the master robot is the desired set trajectory, and the set trajectory of the slave robot is the output position of the master robot. In the CCC synchronization algorithm, the set trajectories of the dual arm manipulators ensure stability and synchronize their movements while maintaining the desired trajectory. In this paper, the robot model is designed using SolidWorks software. Then the data is transferred to Simscape software combined with MATLAB Simulink to simulate and evaluate the two synchronous control methods mentioned. An experimental model of a dual 3-DOF manipulator is being constructed to evaluate the practical effectiveness of these two methods, which use the CAN BUS protocol for communication between them. The study utilizes 2-level distributed control based on the CAN BUS protocol. At level 1, this protocol is applied to communicate with the microcontroller, which controls the joints of the two robotic arms. At level 2, this protocol is applied to interface with the microcontroller, which controls the dual 3-DOF manipulator. Finally, the simulation results and experimental models based on the CAN-BUS protocol are used to evaluate the synchronization effect of the two proposed methods.
{"title":"Design Model and Synchronous Controllers for a Dual 3-DOF Manipulator based on CAN Network","authors":"D. Tran, Tan Luc Nguyen, Thien Tranh Ha, Hung Hoang","doi":"10.1109/ICSSE58758.2023.10227198","DOIUrl":"https://doi.org/10.1109/ICSSE58758.2023.10227198","url":null,"abstract":"This paper mentions two synchronous control algorithms for a dual 3-degree-of-freedom (3-DOF) manipulator robot based on the CAN BUS network, including the master-slave approach (MSA) and cross-coupling control (CCC) algorithms. In the MSA synchronization algorithm, the set trajectory of the master robot is the desired set trajectory, and the set trajectory of the slave robot is the output position of the master robot. In the CCC synchronization algorithm, the set trajectories of the dual arm manipulators ensure stability and synchronize their movements while maintaining the desired trajectory. In this paper, the robot model is designed using SolidWorks software. Then the data is transferred to Simscape software combined with MATLAB Simulink to simulate and evaluate the two synchronous control methods mentioned. An experimental model of a dual 3-DOF manipulator is being constructed to evaluate the practical effectiveness of these two methods, which use the CAN BUS protocol for communication between them. The study utilizes 2-level distributed control based on the CAN BUS protocol. At level 1, this protocol is applied to communicate with the microcontroller, which controls the joints of the two robotic arms. At level 2, this protocol is applied to interface with the microcontroller, which controls the dual 3-DOF manipulator. Finally, the simulation results and experimental models based on the CAN-BUS protocol are used to evaluate the synchronization effect of the two proposed methods.","PeriodicalId":280745,"journal":{"name":"2023 International Conference on System Science and Engineering (ICSSE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130168496","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 : 2023-07-27DOI: 10.1109/ICSSE58758.2023.10227206
Vo Thi Thanh Ha, Tran Ngoc Tu, Nguyen Trung Dung, Trinh Luong Mien, Chu Thị Thu Thủy
This paper presents the design of an intelligent controller applying reinforcement learning using a deep Q-network (DQN) algorithm for autonomous vehicles. The deep Q-network (DQN) algorithm is an online, model-free reinforcement learning approach. A DQN agent is a value-based reinforcement learning agent that teaches a critic to predict future rewards or returns. Deep Q-network is to replace the action-state Q table with a neural network. This solution applies to building a self-propelled agent capable of correcting static and moving obstacles according to the physical environment. As a result, the autonomous vehicle can move and avoid collisions with obstacles. The correctness of the theory is demonstrated through MATLAB simulation.
{"title":"Deep Q-Network (DQN) Approach for Automatic Vehicles Applied in the Intelligent Transportation System (ITS)","authors":"Vo Thi Thanh Ha, Tran Ngoc Tu, Nguyen Trung Dung, Trinh Luong Mien, Chu Thị Thu Thủy","doi":"10.1109/ICSSE58758.2023.10227206","DOIUrl":"https://doi.org/10.1109/ICSSE58758.2023.10227206","url":null,"abstract":"This paper presents the design of an intelligent controller applying reinforcement learning using a deep Q-network (DQN) algorithm for autonomous vehicles. The deep Q-network (DQN) algorithm is an online, model-free reinforcement learning approach. A DQN agent is a value-based reinforcement learning agent that teaches a critic to predict future rewards or returns. Deep Q-network is to replace the action-state Q table with a neural network. This solution applies to building a self-propelled agent capable of correcting static and moving obstacles according to the physical environment. As a result, the autonomous vehicle can move and avoid collisions with obstacles. The correctness of the theory is demonstrated through MATLAB simulation.","PeriodicalId":280745,"journal":{"name":"2023 International Conference on System Science and Engineering (ICSSE)","volume":"60 8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114137421","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 : 2023-07-27DOI: 10.1109/ICSSE58758.2023.10227216
Hung Ly, N. X. Doan, Chau-Duy Le, Phuoc Loc Nguyen, Duc Hung Nguyen, D. Pham
This article proposes a distributed consensus-based control algorithm based on the voltage shifting method for the secondary control layer of the hierarchical control structure in DC microgrids to attain both precise proportional power sharing and DC bus voltage restoration when the microgrid is isolated from the utility grid. The proposed algorithm implemented two unity gain integrators for each distributed controller, one is for ensuring proportional power sharing and the other is for restoring local DC bus voltage, and a low-bandwidth communication network to transfer information between converters. For the proposed strategy, each converter only needs to broadcast its p.u value, which is characterized by the relation between the current output power and the converter rated output power, and receive the voltage measurement from the nearest measure station on the DC bus. Voltage shifting terms will be calculated locally by distributed controllers, reducing the risk of having a single point of failure in the system as opposed to a centralized algorithm. When all converter p.u values converged to a universal value, proportional power sharing will be attained. The stability and effectiveness of the proposed algorithm will be evaluated using PLECS simulations and tested with an experimental DC microgrid setup.
{"title":"Improvement in Proportional Energy Sharing and DC Bus Voltage Restoring for DC Microgrid in the Islanded Operation Mode","authors":"Hung Ly, N. X. Doan, Chau-Duy Le, Phuoc Loc Nguyen, Duc Hung Nguyen, D. Pham","doi":"10.1109/ICSSE58758.2023.10227216","DOIUrl":"https://doi.org/10.1109/ICSSE58758.2023.10227216","url":null,"abstract":"This article proposes a distributed consensus-based control algorithm based on the voltage shifting method for the secondary control layer of the hierarchical control structure in DC microgrids to attain both precise proportional power sharing and DC bus voltage restoration when the microgrid is isolated from the utility grid. The proposed algorithm implemented two unity gain integrators for each distributed controller, one is for ensuring proportional power sharing and the other is for restoring local DC bus voltage, and a low-bandwidth communication network to transfer information between converters. For the proposed strategy, each converter only needs to broadcast its p.u value, which is characterized by the relation between the current output power and the converter rated output power, and receive the voltage measurement from the nearest measure station on the DC bus. Voltage shifting terms will be calculated locally by distributed controllers, reducing the risk of having a single point of failure in the system as opposed to a centralized algorithm. When all converter p.u values converged to a universal value, proportional power sharing will be attained. The stability and effectiveness of the proposed algorithm will be evaluated using PLECS simulations and tested with an experimental DC microgrid setup.","PeriodicalId":280745,"journal":{"name":"2023 International Conference on System Science and Engineering (ICSSE)","volume":"141 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114540780","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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