Pub Date : 2023-01-01DOI: 10.1109/msmc.2022.3222673
Haibin Zhu
{"title":"Meet Our Volunteers [Meet Our Volunteers]","authors":"Haibin Zhu","doi":"10.1109/msmc.2022.3222673","DOIUrl":"https://doi.org/10.1109/msmc.2022.3222673","url":null,"abstract":"","PeriodicalId":43649,"journal":{"name":"IEEE Systems Man and Cybernetics Magazine","volume":"12 1","pages":""},"PeriodicalIF":3.2,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79451314","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 : 2023-01-01DOI: 10.1109/MSMC.2022.3208393
Arabinda Ghosh, A. Ray, Omkar Singh, M. Jamshidi
Ensuring stability and maintaining performances of the load frequency controller (LFC) are stimulating tasks. A state feedback controller (SFC) with a generalized range of operation satisfying the necessary and sufficient conditions for system stability along with optimized performances through the gravitational search algorithm (GSA) are proposed. The proposed range is dependent on the system parameters. The agent-based systems in the literature consider the dimension of an agent as per the number of decision variables of the problem. The proposed method reduces the number of decision variables to obtain the controller gains and to use in the optimization process. The proposed method is validated through extensive results for different objective functions, contemplating both the steady state and the transient requirements as well as a consideration of different perturbed system parameters and variations in the input disturbances. Results and comparative studies with popular control techniques and optimization algorithms testify that the proposed method maintains system stability and improves the system performances while considering different system parameters, parametric uncertainties, and variations in input disturbances.
{"title":"Optimized Load Frequency Controller Performances With a Reduced Number of Decision Variables: A Gravitational Search Algorithm-Based Method","authors":"Arabinda Ghosh, A. Ray, Omkar Singh, M. Jamshidi","doi":"10.1109/MSMC.2022.3208393","DOIUrl":"https://doi.org/10.1109/MSMC.2022.3208393","url":null,"abstract":"Ensuring stability and maintaining performances of the load frequency controller (LFC) are stimulating tasks. A state feedback controller (SFC) with a generalized range of operation satisfying the necessary and sufficient conditions for system stability along with optimized performances through the gravitational search algorithm (GSA) are proposed. The proposed range is dependent on the system parameters. The agent-based systems in the literature consider the dimension of an agent as per the number of decision variables of the problem. The proposed method reduces the number of decision variables to obtain the controller gains and to use in the optimization process. The proposed method is validated through extensive results for different objective functions, contemplating both the steady state and the transient requirements as well as a consideration of different perturbed system parameters and variations in the input disturbances. Results and comparative studies with popular control techniques and optimization algorithms testify that the proposed method maintains system stability and improves the system performances while considering different system parameters, parametric uncertainties, and variations in input disturbances.","PeriodicalId":43649,"journal":{"name":"IEEE Systems Man and Cybernetics Magazine","volume":"2 1","pages":"48-57"},"PeriodicalIF":3.2,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88329960","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 : 2023-01-01DOI: 10.1109/MSMC.2022.3211690
Sheng Hong, Tao Feng, Jun Hu, Xiao D Zhang
A wind turbine rotor system is a typical networked industrial control system. The security of its operation is very important to energy systems and users. In this article, the artificial intelligence algorithm is used to predict the security operation of a wind turbine rotor system, and a prediction method of system security monitoring based on a convolutional neural network (CNN) is proposed. First, the dynamic analysis of the operation principle of the wind turbine rotor system is carried out, and the industrial control model of the rotor system is established by using the relevant data of the wind turbine. The relevant data required for the security prediction of the wind turbine rotor system are obtained, and its dataset is established. Then, the CNN is trained with limited datasets, and the trained CNN is used to accurately predict the pitch angle. The residual information is obtained by comparing the predicted pitch angle with the real output pitch angle of the wind turbine rotor changing system. Finally, the security prediction results are obtained according to the residual and the decision index. The proposed security trend prediction method for wind turbine rotor systems can accurately and effectively predict the change of the fault amplitude, provide detection and estimate decision results, and improve the system security.
{"title":"Operation Security Prediction for Wind Turbines Using Convolutional Neural Networks: A Proposed Method","authors":"Sheng Hong, Tao Feng, Jun Hu, Xiao D Zhang","doi":"10.1109/MSMC.2022.3211690","DOIUrl":"https://doi.org/10.1109/MSMC.2022.3211690","url":null,"abstract":"A wind turbine rotor system is a typical networked industrial control system. The security of its operation is very important to energy systems and users. In this article, the artificial intelligence algorithm is used to predict the security operation of a wind turbine rotor system, and a prediction method of system security monitoring based on a convolutional neural network (CNN) is proposed. First, the dynamic analysis of the operation principle of the wind turbine rotor system is carried out, and the industrial control model of the rotor system is established by using the relevant data of the wind turbine. The relevant data required for the security prediction of the wind turbine rotor system are obtained, and its dataset is established. Then, the CNN is trained with limited datasets, and the trained CNN is used to accurately predict the pitch angle. The residual information is obtained by comparing the predicted pitch angle with the real output pitch angle of the wind turbine rotor changing system. Finally, the security prediction results are obtained according to the residual and the decision index. The proposed security trend prediction method for wind turbine rotor systems can accurately and effectively predict the change of the fault amplitude, provide detection and estimate decision results, and improve the system security.","PeriodicalId":43649,"journal":{"name":"IEEE Systems Man and Cybernetics Magazine","volume":"41 1","pages":"4-9"},"PeriodicalIF":3.2,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76685998","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 : 2023-01-01DOI: 10.1109/MSMC.2022.3217364
Mingyue Liu, Syazwina Binti Alias
Edge computing has been a promising framework to provide effective computing services for edge users in most industrial environments. Due to the limited resources at the edge, it is not suitable for massive requirements such as the virtual reality process, communication, and so on. Cloud computing can provide sufficient resources for those requirements, but it has some latency lags. Industrial edge clouds enable flexible service providers for industrial applications by merging edge and cloud computing. The virtual network function (VNF) is one approach, while placement is a dominant solution. However, this solution may increase the cost of communication as the nodes are more distant. In this article, we investigate the resource allocation problem for VNF placement in industrial edge systems. The aim is to minimize the overall cost of the whole placement procedure, including operating cost, communication cost, and placement cost. We formulate this VNF placement problem as an integer programming problem, and due to the complexity of the problem, we propose a heuristic method to solve it. Numerical simulation shows that our proposed method can significantly cut down the cost while meeting the multiple resource constraints.
{"title":"Cost-Efficient Virtual Network Function Placement in an Industrial Edge System: A Proposed Method","authors":"Mingyue Liu, Syazwina Binti Alias","doi":"10.1109/MSMC.2022.3217364","DOIUrl":"https://doi.org/10.1109/MSMC.2022.3217364","url":null,"abstract":"Edge computing has been a promising framework to provide effective computing services for edge users in most industrial environments. Due to the limited resources at the edge, it is not suitable for massive requirements such as the virtual reality process, communication, and so on. Cloud computing can provide sufficient resources for those requirements, but it has some latency lags. Industrial edge clouds enable flexible service providers for industrial applications by merging edge and cloud computing. The virtual network function (VNF) is one approach, while placement is a dominant solution. However, this solution may increase the cost of communication as the nodes are more distant. In this article, we investigate the resource allocation problem for VNF placement in industrial edge systems. The aim is to minimize the overall cost of the whole placement procedure, including operating cost, communication cost, and placement cost. We formulate this VNF placement problem as an integer programming problem, and due to the complexity of the problem, we propose a heuristic method to solve it. Numerical simulation shows that our proposed method can significantly cut down the cost while meeting the multiple resource constraints.","PeriodicalId":43649,"journal":{"name":"IEEE Systems Man and Cybernetics Magazine","volume":"49 1","pages":"10-17"},"PeriodicalIF":3.2,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85109039","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 : 2023-01-01DOI: 10.1109/MSMC.2022.3218424
Sheng Hong, Xiaochuan Duan, Yao Peng, Hao Liu, E. Zio
In this article, a novel method of deep learning based on wavelet transform and deep perceptron neural networks (DPNNs) is proposed to predict the remaining useful life (RUL) of bearings. The proposed approach first extracts from the recorded signals the energy features by the wavelet packet transform. After training on these data, the DPNN model can be used to predict the RUL of a bearing. To verify the model, the proposed DPNN based on wavelet packet transform is compared with a least-squares support vector machine (LS-SVM) and long short-term memory (LSTM). The experimental results illustrate that DPNN can effectively predict the RUL of the bearing and is superior to the LS-SVM and LSTM in terms of prediction performance.
{"title":"Bearing Degradation Prediction by WPD and DPNN: Introducing a Novel Deep Learning Method","authors":"Sheng Hong, Xiaochuan Duan, Yao Peng, Hao Liu, E. Zio","doi":"10.1109/MSMC.2022.3218424","DOIUrl":"https://doi.org/10.1109/MSMC.2022.3218424","url":null,"abstract":"In this article, a novel method of deep learning based on wavelet transform and deep perceptron neural networks (DPNNs) is proposed to predict the remaining useful life (RUL) of bearings. The proposed approach first extracts from the recorded signals the energy features by the wavelet packet transform. After training on these data, the DPNN model can be used to predict the RUL of a bearing. To verify the model, the proposed DPNN based on wavelet packet transform is compared with a least-squares support vector machine (LS-SVM) and long short-term memory (LSTM). The experimental results illustrate that DPNN can effectively predict the RUL of the bearing and is superior to the LS-SVM and LSTM in terms of prediction performance.","PeriodicalId":43649,"journal":{"name":"IEEE Systems Man and Cybernetics Magazine","volume":"15 1","pages":"18-24"},"PeriodicalIF":3.2,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78139058","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 : 2023-01-01DOI: 10.1109/MSMC.2022.3179800
Yuxin Liu, Jinsong Gui, N. Xiong
There will exist a growing interest in deploying data-intensive and content-rich applications on mobile smart devices. Also, ultrareliable and low-latency communications will be the critical requirements for obtaining good quality of experience for users of smart devices. However, the existing cellular architectures hardly provide a rich and stable spectrum supply to support ultrareliable and low-latency communications. Although future wireless networks are expected to effectively exploit the terahertz frequency band, it is difficult to obtain stable, ultrareliable, and low-latency communications due to the immaturity of both propagation models and radio interface technologies in such a high-frequency band. Therefore, this article introduces cognitive network brokers based on a data-driven cognitive network architecture to integrate and make full use of various resources to provide good network services for users, including an engine for spectrum and device cognition and an engine for cognitive network service construction.
{"title":"Cognitive Network Architecture Systems to Provide Intelligent Services: An Intelligent Self-Organization Approach With a Game-Based Incentive Mechanism","authors":"Yuxin Liu, Jinsong Gui, N. Xiong","doi":"10.1109/MSMC.2022.3179800","DOIUrl":"https://doi.org/10.1109/MSMC.2022.3179800","url":null,"abstract":"There will exist a growing interest in deploying data-intensive and content-rich applications on mobile smart devices. Also, ultrareliable and low-latency communications will be the critical requirements for obtaining good quality of experience for users of smart devices. However, the existing cellular architectures hardly provide a rich and stable spectrum supply to support ultrareliable and low-latency communications. Although future wireless networks are expected to effectively exploit the terahertz frequency band, it is difficult to obtain stable, ultrareliable, and low-latency communications due to the immaturity of both propagation models and radio interface technologies in such a high-frequency band. Therefore, this article introduces cognitive network brokers based on a data-driven cognitive network architecture to integrate and make full use of various resources to provide good network services for users, including an engine for spectrum and device cognition and an engine for cognitive network service construction.","PeriodicalId":43649,"journal":{"name":"IEEE Systems Man and Cybernetics Magazine","volume":"61 1","pages":"25-36"},"PeriodicalIF":3.2,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80289038","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 : 2023-01-01DOI: 10.1109/msmc.2022.3222675
V. Marík, T. Strasser, Milena Zeithamlova
{"title":"2022 IEEE International Conference on Systems, Man, and Cybernetics [Conference Report]","authors":"V. Marík, T. Strasser, Milena Zeithamlova","doi":"10.1109/msmc.2022.3222675","DOIUrl":"https://doi.org/10.1109/msmc.2022.3222675","url":null,"abstract":"","PeriodicalId":43649,"journal":{"name":"IEEE Systems Man and Cybernetics Magazine","volume":"11 1","pages":""},"PeriodicalIF":3.2,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87199950","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 : 2023-01-01DOI: 10.1109/MSMC.2022.3209833
K. Mitsugi, Ryo Chikaraishi, M. Deng, Y. Noge
Recently, power conversion devices have been increasingly becoming more efficient at facilitating the electrification of vehicles and saving energy. To evaluate and design power conversion equipment, it is necessary to measure the power loss of the equipment with a high degree of accuracy. Power loss is generally determined from the difference between the input power and output power using a wattmeter. However, as a power conversion device becomes more efficient, the ratio of the power loss to the measured input and output power is smaller, and the error in the measuring device becomes nonnegligible. A solution to this problem is to determine the power loss using the quantity of heat radiated from the power conversion equipment. This method is called a calorimetric method. In the previous study, the calorimeter using a Peltier element was proposed. In this article, a nonlinear temperature control system that adapts to changes in the heat capacity of the measured object is designed based on operator theory and adaptive control theory. Since the adaptive control theory requires the control system to satisfy passivity, a feedback control system that guarantees passivity is designed based on isomorphism. Furthermore, experiments are performed to confirm the effectiveness of the proposed control system.
{"title":"A Design Based on Operator Theory and Isomorphism: Operator-Based Nonlinear Adaptive Control for a Calorimetric Power Loss Measurement System Using a Peltier Element","authors":"K. Mitsugi, Ryo Chikaraishi, M. Deng, Y. Noge","doi":"10.1109/MSMC.2022.3209833","DOIUrl":"https://doi.org/10.1109/MSMC.2022.3209833","url":null,"abstract":"Recently, power conversion devices have been increasingly becoming more efficient at facilitating the electrification of vehicles and saving energy. To evaluate and design power conversion equipment, it is necessary to measure the power loss of the equipment with a high degree of accuracy. Power loss is generally determined from the difference between the input power and output power using a wattmeter. However, as a power conversion device becomes more efficient, the ratio of the power loss to the measured input and output power is smaller, and the error in the measuring device becomes nonnegligible. A solution to this problem is to determine the power loss using the quantity of heat radiated from the power conversion equipment. This method is called a calorimetric method. In the previous study, the calorimeter using a Peltier element was proposed. In this article, a nonlinear temperature control system that adapts to changes in the heat capacity of the measured object is designed based on operator theory and adaptive control theory. Since the adaptive control theory requires the control system to satisfy passivity, a feedback control system that guarantees passivity is designed based on isomorphism. Furthermore, experiments are performed to confirm the effectiveness of the proposed control system.","PeriodicalId":43649,"journal":{"name":"IEEE Systems Man and Cybernetics Magazine","volume":"6 1","pages":"58-68"},"PeriodicalIF":3.2,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89982214","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 : 2023-01-01DOI: 10.1109/MSMC.2022.3201365
F. Mohammadi, M. Saif
Blockchain is a distributed decentralized peer-to-peer network, which is used for sharing data across a large number of entities in a trusted and secure way. Blockchain utilizes different mechanisms, such as hash functions, consensus algorithms, etc., for data verification and validation. In modern power systems, blockchain technology is used for balancing supply and demand, contributing to the demand-side management programs, and mainly, transitioning consumers to prosumers to trade electricity and reduce operational costs. This article aims at providing an in-depth discussion on energy transition and digitalization in power systems and investigating the role of blockchain technology in modern power systems. In addition, opportunities, challenges, and limitations of blockchain technology in modern power systems are discussed.
{"title":"Blockchain Technology in Modern Power Systems: A Systematic Review","authors":"F. Mohammadi, M. Saif","doi":"10.1109/MSMC.2022.3201365","DOIUrl":"https://doi.org/10.1109/MSMC.2022.3201365","url":null,"abstract":"Blockchain is a distributed decentralized peer-to-peer network, which is used for sharing data across a large number of entities in a trusted and secure way. Blockchain utilizes different mechanisms, such as hash functions, consensus algorithms, etc., for data verification and validation. In modern power systems, blockchain technology is used for balancing supply and demand, contributing to the demand-side management programs, and mainly, transitioning consumers to prosumers to trade electricity and reduce operational costs. This article aims at providing an in-depth discussion on energy transition and digitalization in power systems and investigating the role of blockchain technology in modern power systems. In addition, opportunities, challenges, and limitations of blockchain technology in modern power systems are discussed.","PeriodicalId":43649,"journal":{"name":"IEEE Systems Man and Cybernetics Magazine","volume":"24 1","pages":"37-47"},"PeriodicalIF":3.2,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78767119","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 : 2023-01-01DOI: 10.1109/msmc.2022.3224355
Jiehan Zhou, Haisheng Yu, Zhixiong Chen, Yongzhi Wang
{"title":"Special Section on Next-Generation Networks for Industry 4.0: Using Cutting-Edge Technologies to Connect, Communicate, and Compute [Editorial]","authors":"Jiehan Zhou, Haisheng Yu, Zhixiong Chen, Yongzhi Wang","doi":"10.1109/msmc.2022.3224355","DOIUrl":"https://doi.org/10.1109/msmc.2022.3224355","url":null,"abstract":"","PeriodicalId":43649,"journal":{"name":"IEEE Systems Man and Cybernetics Magazine","volume":"305 1","pages":""},"PeriodicalIF":3.2,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79829306","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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