Blocker tag attack is one of the denial-of-service(DoS)attacks that threatens the privacy and security of RFID systems.The attacker interferes with the blocked tag by simulating a fake tag with the same ID,thus causin...Blocker tag attack is one of the denial-of-service(DoS)attacks that threatens the privacy and security of RFID systems.The attacker interferes with the blocked tag by simulating a fake tag with the same ID,thus causing a collision of message replies.In many practical scenarios,the number of blocked tags may vary,or even be small.For example,the attacker may only block the important customers or high-value items.To avoid the disclosure of privacy and economic losses,it is of great importance to fast pinpoint these blocked ones.However,existing works do not take into account the impact of the number of blocked tags on the execution time and suffer from incomplete identification of blocked tags,long identification time or privacy leakage.To overcome these limits,we propose a cross layer blocked tag identification protocol(CLBI).CLBI consists of multiple rounds,in which it enables multiple unblocked tags to select one time slot and concurrently verify them by using tag estimation in physical layer.Benefiting from the utilization of most collision slots,the execution time can be greatly reduced.Furthermore,for efficient identification of blocked tags under different proportions,we propose a hybrid protocol named adaptive cross layer blocked tag identification protocol(A-CLBI),which estimates the remaining blocked tag in each round and adjusts the identification strategy accordingly.Extensive simulations show that our protocol outperforms state-of-the-art blocked tags identification protocol.展开更多
Radio Frequency Identification(RFID)technology has emerged as a promising solution for real-time tracking and monitoring in the petroleum industry.This study systematically reviews recent advancements in RFID applicat...Radio Frequency Identification(RFID)technology has emerged as a promising solution for real-time tracking and monitoring in the petroleum industry.This study systematically reviews recent advancements in RFID applications for petroleum asset management,logistics,and safety.The research is based on an extensive review of peer-reviewed literature,industry reports,and experimental case studies involving RFID deployment in refinery operations and pipeline monitoring.The study also examines practical implementation challenges,including signal interference due to metal surfaces,high initial costs associated with infrastructure setup,and integration complexities with existing digital systems such as SCADA and IoT platforms.Furthermore,issues related to data security and the potential for unauthorized access are discussed as critical concerns that need to be addressed for large-scale adoption.Despite these limitations,RFID technologydemonstrates significant potential in optimizing supply chain management,enhancing real-time asset tracking,and improving workplace safety in petroleum engineering.The ability to automate inventory management,reduce operational downtime,and enhance predictive maintenance further underscores its strategic importance.Future research should focus on overcoming technical barriers through the development of advanced RFIDtags with higher resistance to extreme environmental conditions and improved data encryption techniques.Additionally,cost-effective deployment strategies andinteroperability standards must be established to facilitate broader industry adoption.Collaborative efforts between researchers,technology developers,and industry stakeholders will be essential in driving innovation and ensuring the successful integration of RFID into the petroleum sector.展开更多
Radio frequency identification technology is one of the main technologies of Internet of Things(IoT).Through the transmission and reflection of wireless radio frequency signals,non-contact identification is realized,a...Radio frequency identification technology is one of the main technologies of Internet of Things(IoT).Through the transmission and reflection of wireless radio frequency signals,non-contact identification is realized,and multiple objects identification can be realized.However,when multiple tags communicate with a singleton reader simultaneously,collision will occur between the signals,which hinders the successful transmissions.To effectively avoid the tag collision problem and improve the reading performance of RFID systems,two advanced tag identification algorithms namely Adaptive M-ary tree slotted Aloha(AMTS)based on the characteristics of Aloha-based and Query tree-based algorithms are proposed.In AMTS,the reader firstly uses the framed slotted Aloha protocol to map the tag set to different time slots,and then identify the collided tags using binary search method based on collision factor or mapping table.Both performance analysis and extensive experimental results indicate that our proposed algorithms significantly outperforms most existing anti-collision approaches in tag dense RFID systems.展开更多
In this paper, we present a power adjustment scheme to dynamically enlarge and shrink power coverage to speed up tag identification in an RFID system. By dividing a TDMA frame into time slots, the proposed power adjus...In this paper, we present a power adjustment scheme to dynamically enlarge and shrink power coverage to speed up tag identification in an RFID system. By dividing a TDMA frame into time slots, the proposed power adjustment scheme can adaptively increase or decrease the transmission power of a reader. Specifically, due to the contention for a TDMA slot from numerous tags, three states of a slot could exist;they are respectively referred to as successful, collided, and idle states. An adjustment factor based on the three states is designed to dynamically adjust the transmission power of a reader. The design of the adjustment factor considers two different aspects. When the number of idle state far exceeds the number of collided state, the first aspect will enlarge the power such that more tags within the coverage can be concurrently identified. On the other hand, when the number of idle state is much smaller than the number of collided state, the second aspect will shrink the power such that the number of tags within the coverage is significantly reduced. The proposed power adjustment scheme is simulated using NS-3. In the simulation, we design three different topologies which place tags in three distributions, uniform, random, and hotspot. From the simulation results, we demonstrate that the proposed power adjustment scheme can speed up the tag identification and save energy consumption, particularly when a large number of tags are placed in hotspot distribution.展开更多
Radio Frequency Identification(RFID)technology has been widely used to identify missing items.In many applications,rapidly pinpointing key tags that are attached to favorable or valuable items is critical.To realize t...Radio Frequency Identification(RFID)technology has been widely used to identify missing items.In many applications,rapidly pinpointing key tags that are attached to favorable or valuable items is critical.To realize this goal,interference from ordinary tags should be avoided,while key tags should be efficiently verified.Despite many previous studies,how to rapidly and dynamically filter out ordinary tags when the ratio of ordinary tags changes has not been addressed.Moreover,how to efficiently verify missing key tags in groups rather than one by one has not been explored,especially with varying missing rates.In this paper,we propose an Efficient and Robust missing Key tag Identification(ERKI)protocol that consists of a filtering mechanism and a verification mechanism.Specifically,the filtering mechanism adopts the Bloom filter to quickly filter out ordinary tags and uses the labeling vector to optimize the Bloom filter's performance when the key tag ratio is high.Furthermore,the verification mechanism can dynamically verify key tags according to the missing rates,in which an appropriate number of key tags is mapped to a slot and verified at once.Moreover,we theoretically analyze the parameters of the ERKI protocol to minimize its execution time.Extensive numerical results show that ERKI can accelerate the execution time by more than 2.14compared with state-of-the-art solutions.展开更多
Improving efficiency in roll grinding process is a critical issue in the steel mill.Each roll has to be grinded to a well-defined profile and then to be measured for quality check.However,the surface conditions are in...Improving efficiency in roll grinding process is a critical issue in the steel mill.Each roll has to be grinded to a well-defined profile and then to be measured for quality check.However,the surface conditions are inspected by using different on-line inspection probes equipped on the grinder.The roll number is a unique information which can be used to merge with a huge amount of measurement data so that the condition of each roll is fully monitored.One of the key factors that hinder the efficiency in such process is the errors and time consumption due to human intervention.In order to mitigate these issues and to realize the fully automatic grinding process,radio frequency identification technology（RFID） could be a solution and has been developed in this paper.It is well known that when an RFID tag is placed directly upon a metallic object,in the absence of a gap or a substrate,it functions rather poorly and even becomes totally dysfunctional.This limitation,in turn,poses a real barrier to the use of the RFID on metallic objects.This paper proposes a miniature RFID tag antenna design for application on roll number identification.The experimental tests show that the maximum read range of the proposed RFID tag placed on a roll is approximately 1.5m and the overall size is only 32×18×3.2 mm;.An RFID system for roll number identification was used in a roll shop and several remarkable improvements were achieved,including the completely automatic grinding process and the error-free identification,as well as the high personnel safety operation.展开更多
System identification is a data-driven modeling technique that originates from the control field.It constructs models from data to mimic the behavior of dynamic systems.However,in the network era,scenarios such as sen...System identification is a data-driven modeling technique that originates from the control field.It constructs models from data to mimic the behavior of dynamic systems.However,in the network era,scenarios such as sensor malfunctions,packet loss,cyber-attacks,and big data affect the quality,integrity,and security of the data.These data issues pose significant challenges to traditional system identification methods.This paper presents a comprehensive survey of the emergent challenges and advances in system identification in the network era.It explores cutting-edge methodologies to address data issues such as data loss,outliers,noise and nonlinear system identification for complex systems.To tackle the data loss,the methods based on imputation and likelihood-based inference(e.g.,expectation maximization)have been employed.For outliers and noise,methods like robust regression(e.g.,least median of squares,least trimmed squares)and lowrank matrix decomposition show progress in maintaining data integrity.Nonlinear system identification has advanced through kernel-based methods and neural networks,which can model complex data patterns.Finally,this paper provides valuable insights into potential directions for future research.展开更多
Dear Editor,This letter presents a novel approach to the data-driven control of unknown nonlinear systems.By leveraging online sparse identification based on the Koopman operator,a high-dimensional linear system model...Dear Editor,This letter presents a novel approach to the data-driven control of unknown nonlinear systems.By leveraging online sparse identification based on the Koopman operator,a high-dimensional linear system model approximating the actual system is obtained online.The upper bound of the discrepancy between the identified model and the actual system is estimated using real-time prediction error,which is then utilized in the design of a tube-based robust model predictive controller.The effectiveness of the proposed approach is validated by numerical simulation.展开更多
A state-of-the-art review is presented of mathematical manoeuvring models for surface ships and parameter estimation methods that have been used to build mathematical manoeuvring models for surface ships. In the first...A state-of-the-art review is presented of mathematical manoeuvring models for surface ships and parameter estimation methods that have been used to build mathematical manoeuvring models for surface ships. In the first part, the classical manoeuvring models, such as the Abkowitz model, MMG, Nomoto and their revised versions, are revisited and the model structure with the hydrodynamic coefficients is also presented.Then, manoeuvring tests, including both the scaled model tests and sea trials, are introduced with the fact that the test data is critically important to obtain reliable results using parameter estimation methods. In the last part, selected papers published in journals and international conferences are reviewed and the statistical analysis of the manoeuvring models, test data, system identification methods and environmental disturbances used in the paper is presented.展开更多
A novel parameter identification method for magnetic levitation bearing rotor systems is proposed,based on the modulation function method.The fundamental principle of the modulation function method for parameter ident...A novel parameter identification method for magnetic levitation bearing rotor systems is proposed,based on the modulation function method.The fundamental principle of the modulation function method for parameter identification is derived on the basis of the characteristics of the modulation function.The transformation of the differential equation model of a continuous system into a general algebraic equation model is effectively achieved,thereby avoiding the influence of errors introduced by the initial value and differential derivation of the system.Modulation function method parameter identification models have been established for single-degree-of-freedom and multi-degree-of-freedom magnetic levitation bearing rotor systems.The influence of different parameters of Hartley modulation function on the accuracy of system parameter identification has been investigated,thus providing a basis for the design of Hartley modulation function parameters.Simulation and experimental results demonstrate that the modulation function method can effectively identify system parameters despite the presence of system noise.展开更多
Accurate identification of unknown internal parameters in photovoltaic(PV)cells is crucial and significantly affects the subsequent system-performance analysis and control.However,noise,insufficient data acquisition,a...Accurate identification of unknown internal parameters in photovoltaic(PV)cells is crucial and significantly affects the subsequent system-performance analysis and control.However,noise,insufficient data acquisition,and loss of recorded data can deteriorate the extraction accuracy of unknown parameters.Hence,this study proposes an intelligent parameter-identification strategy that integrates artificial ecosystem optimization(AEO)and a Bayesian neural network(BNN)for PV cell parameter extraction.A BNN is used for data preprocessing,including data denoising and prediction.Furthermore,the AEO algorithm is utilized to identify unknown parameters in the single-diode model(SDM),double-diode model(DDM),and three-diode model(TDM).Nine other metaheuristic algorithms(MhAs)are adopted for an unbiased and comprehensive validation.Simulation results show that BNN-based data preprocessing com-bined with effective MhAs significantly improve the parameter-extraction accuracy and stability compared with methods without data preprocessing.For instance,under denoised data,the accuracies of the SDM,DDM,and TDM increase by 99.69%,99.70%,and 99.69%,respectively,whereas their accuracy improvements increase by 66.71%,59.65%,and 70.36%,respectively.展开更多
BACKGROUND The Asia-Pacific Colorectal Screening(APCS)score was designed with the purpose of distinguishing individuals at high risk(HR)for colorectal advanced neoplasia(AN).Traditional Chinese medicine(TCM)constituti...BACKGROUND The Asia-Pacific Colorectal Screening(APCS)score was designed with the purpose of distinguishing individuals at high risk(HR)for colorectal advanced neoplasia(AN).Traditional Chinese medicine(TCM)constitution was also linked with colorectal cancer(CRC).AIM To integrate the APCS score with TCM constitution identification as a new algorithm to screen for CRC.METHODS A cross-sectional multicenter study was carried out in three hospitals,enrolling 1430 patients who were asymptomatic and undergoing screening colonoscopy from 2022 to 2023.Patients were considered to have average risk,moderate risk,or HR with their APCS score.Odd ratios assessed the relationship between TCM constitution and disease progression.A TCM constitution risk score was created.The sensitivity and specificity of the new algorithm were calculated to evaluate diagnostic performance in detecting advanced adenoma(AA),CRC,and AN.RESULTS Of the 1430 patients,370(25.9%)were categorized as average risk,755(52.8%)as moderate risk,and 305(21.3%)as HR.Using the combined APCS score and the TCM constitution(damp-heat,qi-deficiency,yang-deficiency,phlegm-dampness,and inherited special constitution as positive)algorithm,72.2%of patients with AA and 73.7%of patients with AN were detected.Compared with the APCS score alone,the new algorithm significantly improved the sensitivity for screening AA[72.2%,95%confidence interval(CI):64.4%-80.0%vs 49.2%,95%CI:40.5%-57.9%]and AN(73.7%,95%CI:66.4%-81.1%vs 51.1%,95%CI:42.7%-59.5%).CONCLUSION The combination of APCS and TCM constitution identification questionnaires was valuable in identifying Chinese individuals who were asymptomatic for colorectal screening prioritization.展开更多
Synthetic aperture radar(SAR)radio frequency identification(RFID)localization is widely used for automated guided vehicles(AGVs)in the industrial internet of things(IIoT).However,the AGV’s speeds are limited by the p...Synthetic aperture radar(SAR)radio frequency identification(RFID)localization is widely used for automated guided vehicles(AGVs)in the industrial internet of things(IIoT).However,the AGV’s speeds are limited by the phase difference(PD)of two neighboring readers.In this paper,an inertial navigation system(INS)based SAR RFID localization method(ISRL)where AGV moves nonlinearly.To relax the speed limitation,a new phase-unwrapping method based on the similarity of PDs(PU-SPD)is proposed to deal with the PD ambiguity when the AGV speed exceeds 60km/h.In localization,the gauss-newton algorithm(GN)is employed and an initial value estimation scheme based on variable substitution(IVE-VS)is proposed to improve its positioning accuracy and the convergence rate.Thus,ISRL is a combination of IVE-VS and GN.Moreover,the Cramer-Rao lower bound(CRLB)and the speed limitation is derived.Simulation results show that the ISRL can converge after two iterations,and the positioning accuracy can achieve 7.50cm at a phase noise levelσ=0.18,which is 35%better than the Hyperbolic unbiased estimation localization(HyUnb).展开更多
基金This work was supported in part by the National Natural Science Foundation of China under project contracts Nos.61701082,61701116,61601093,61971113 and 61901095in part by National Key R&D Program under project Nos.2018YFB1802102 and 2018AAA0103203+3 种基金in part by Guangdong Provincial Research and Development Plan in Key Areas under project contract Nos.2019B010141001 and 2019B010142001in part by Sichuan Provincial Science and Technology Planning Program under project contracts Nos.2018HH0034,2019YFG0418,2019YFG0120 and 2018JY0246in part by the fundamental research funds for the Central Universities under project contract No.ZYGX2016J004in part by Science and Technology on Electronic Information Control Laboratory.
文摘Blocker tag attack is one of the denial-of-service(DoS)attacks that threatens the privacy and security of RFID systems.The attacker interferes with the blocked tag by simulating a fake tag with the same ID,thus causing a collision of message replies.In many practical scenarios,the number of blocked tags may vary,or even be small.For example,the attacker may only block the important customers or high-value items.To avoid the disclosure of privacy and economic losses,it is of great importance to fast pinpoint these blocked ones.However,existing works do not take into account the impact of the number of blocked tags on the execution time and suffer from incomplete identification of blocked tags,long identification time or privacy leakage.To overcome these limits,we propose a cross layer blocked tag identification protocol(CLBI).CLBI consists of multiple rounds,in which it enables multiple unblocked tags to select one time slot and concurrently verify them by using tag estimation in physical layer.Benefiting from the utilization of most collision slots,the execution time can be greatly reduced.Furthermore,for efficient identification of blocked tags under different proportions,we propose a hybrid protocol named adaptive cross layer blocked tag identification protocol(A-CLBI),which estimates the remaining blocked tag in each round and adjusts the identification strategy accordingly.Extensive simulations show that our protocol outperforms state-of-the-art blocked tags identification protocol.
文摘Radio Frequency Identification(RFID)technology has emerged as a promising solution for real-time tracking and monitoring in the petroleum industry.This study systematically reviews recent advancements in RFID applications for petroleum asset management,logistics,and safety.The research is based on an extensive review of peer-reviewed literature,industry reports,and experimental case studies involving RFID deployment in refinery operations and pipeline monitoring.The study also examines practical implementation challenges,including signal interference due to metal surfaces,high initial costs associated with infrastructure setup,and integration complexities with existing digital systems such as SCADA and IoT platforms.Furthermore,issues related to data security and the potential for unauthorized access are discussed as critical concerns that need to be addressed for large-scale adoption.Despite these limitations,RFID technologydemonstrates significant potential in optimizing supply chain management,enhancing real-time asset tracking,and improving workplace safety in petroleum engineering.The ability to automate inventory management,reduce operational downtime,and enhance predictive maintenance further underscores its strategic importance.Future research should focus on overcoming technical barriers through the development of advanced RFIDtags with higher resistance to extreme environmental conditions and improved data encryption techniques.Additionally,cost-effective deployment strategies andinteroperability standards must be established to facilitate broader industry adoption.Collaborative efforts between researchers,technology developers,and industry stakeholders will be essential in driving innovation and ensuring the successful integration of RFID into the petroleum sector.
基金supported by The People’s Republic of China Ministry of Science and Technology[2018YFF0213606-03(Mu Y.,Hu T.L.,Gong H.,Li S.J.and Sun Y.H.)http://www.most.gov.cn]the Science and Technology Department of Jilin Province[20160623016TC,20170204017NY,20170204038NY,20200402006NC(Mu Y.,Hu T.L.,Gong H.and Li S.J.)http://kjt.jl.gov.cn]the Science and Technology Bureau of Changchun City[18DY021(Mu Y.,Hu T.L.,Gong H.,and Sun Y.H.)http://kjj.changchun.gov.cn].
文摘Radio frequency identification technology is one of the main technologies of Internet of Things(IoT).Through the transmission and reflection of wireless radio frequency signals,non-contact identification is realized,and multiple objects identification can be realized.However,when multiple tags communicate with a singleton reader simultaneously,collision will occur between the signals,which hinders the successful transmissions.To effectively avoid the tag collision problem and improve the reading performance of RFID systems,two advanced tag identification algorithms namely Adaptive M-ary tree slotted Aloha(AMTS)based on the characteristics of Aloha-based and Query tree-based algorithms are proposed.In AMTS,the reader firstly uses the framed slotted Aloha protocol to map the tag set to different time slots,and then identify the collided tags using binary search method based on collision factor or mapping table.Both performance analysis and extensive experimental results indicate that our proposed algorithms significantly outperforms most existing anti-collision approaches in tag dense RFID systems.
文摘In this paper, we present a power adjustment scheme to dynamically enlarge and shrink power coverage to speed up tag identification in an RFID system. By dividing a TDMA frame into time slots, the proposed power adjustment scheme can adaptively increase or decrease the transmission power of a reader. Specifically, due to the contention for a TDMA slot from numerous tags, three states of a slot could exist;they are respectively referred to as successful, collided, and idle states. An adjustment factor based on the three states is designed to dynamically adjust the transmission power of a reader. The design of the adjustment factor considers two different aspects. When the number of idle state far exceeds the number of collided state, the first aspect will enlarge the power such that more tags within the coverage can be concurrently identified. On the other hand, when the number of idle state is much smaller than the number of collided state, the second aspect will shrink the power such that the number of tags within the coverage is significantly reduced. The proposed power adjustment scheme is simulated using NS-3. In the simulation, we design three different topologies which place tags in three distributions, uniform, random, and hotspot. From the simulation results, we demonstrate that the proposed power adjustment scheme can speed up the tag identification and save energy consumption, particularly when a large number of tags are placed in hotspot distribution.
基金This work was supported in part by the National Natural Science Foundation of China under project contracts No.61971113 and 61901095in part by National Key R&D Program under project contract No.2018AAA0103203+5 种基金in part by Guangdong Provincial Research and Development Plan in Key Areas under project contract No.2019B010141001 and 2019B010142001in part by Sichuan Provincial Science and Technology Planning Program under project contracts No.2020YFG0039,No.2021YFG0013 and No.2021YFH0133in part by Ministry of Education China Mobile Fund Program under project contract No.MCM20180104in part by Yibin Science and Technology Program-Key Projects under project contract No.2018ZSF001 and 2019GY001in part by Central University Business Fee Program under project contract No.A03019023801224the Central Universities under Grant ZYGX2019Z022.
文摘Radio Frequency Identification(RFID)technology has been widely used to identify missing items.In many applications,rapidly pinpointing key tags that are attached to favorable or valuable items is critical.To realize this goal,interference from ordinary tags should be avoided,while key tags should be efficiently verified.Despite many previous studies,how to rapidly and dynamically filter out ordinary tags when the ratio of ordinary tags changes has not been addressed.Moreover,how to efficiently verify missing key tags in groups rather than one by one has not been explored,especially with varying missing rates.In this paper,we propose an Efficient and Robust missing Key tag Identification(ERKI)protocol that consists of a filtering mechanism and a verification mechanism.Specifically,the filtering mechanism adopts the Bloom filter to quickly filter out ordinary tags and uses the labeling vector to optimize the Bloom filter's performance when the key tag ratio is high.Furthermore,the verification mechanism can dynamically verify key tags according to the missing rates,in which an appropriate number of key tags is mapped to a slot and verified at once.Moreover,we theoretically analyze the parameters of the ERKI protocol to minimize its execution time.Extensive numerical results show that ERKI can accelerate the execution time by more than 2.14compared with state-of-the-art solutions.
文摘Improving efficiency in roll grinding process is a critical issue in the steel mill.Each roll has to be grinded to a well-defined profile and then to be measured for quality check.However,the surface conditions are inspected by using different on-line inspection probes equipped on the grinder.The roll number is a unique information which can be used to merge with a huge amount of measurement data so that the condition of each roll is fully monitored.One of the key factors that hinder the efficiency in such process is the errors and time consumption due to human intervention.In order to mitigate these issues and to realize the fully automatic grinding process,radio frequency identification technology（RFID） could be a solution and has been developed in this paper.It is well known that when an RFID tag is placed directly upon a metallic object,in the absence of a gap or a substrate,it functions rather poorly and even becomes totally dysfunctional.This limitation,in turn,poses a real barrier to the use of the RFID on metallic objects.This paper proposes a miniature RFID tag antenna design for application on roll number identification.The experimental tests show that the maximum read range of the proposed RFID tag placed on a roll is approximately 1.5m and the overall size is only 32×18×3.2 mm;.An RFID system for roll number identification was used in a roll shop and several remarkable improvements were achieved,including the completely automatic grinding process and the error-free identification,as well as the high personnel safety operation.
基金supported in part by the National Natural Science Foundation of China(62373060)the BNU Talent seed fund,and the Guangdong Provincial Key Laboratory IRADS for Data Science(2022B1212010006)Recommended by Associate Editor Zhengcai Cao.(Corresponding author:Liang Zhang.)。
文摘System identification is a data-driven modeling technique that originates from the control field.It constructs models from data to mimic the behavior of dynamic systems.However,in the network era,scenarios such as sensor malfunctions,packet loss,cyber-attacks,and big data affect the quality,integrity,and security of the data.These data issues pose significant challenges to traditional system identification methods.This paper presents a comprehensive survey of the emergent challenges and advances in system identification in the network era.It explores cutting-edge methodologies to address data issues such as data loss,outliers,noise and nonlinear system identification for complex systems.To tackle the data loss,the methods based on imputation and likelihood-based inference(e.g.,expectation maximization)have been employed.For outliers and noise,methods like robust regression(e.g.,least median of squares,least trimmed squares)and lowrank matrix decomposition show progress in maintaining data integrity.Nonlinear system identification has advanced through kernel-based methods and neural networks,which can model complex data patterns.Finally,this paper provides valuable insights into potential directions for future research.
基金supported by the National Natural Science Foundation of China(62473020).
文摘Dear Editor,This letter presents a novel approach to the data-driven control of unknown nonlinear systems.By leveraging online sparse identification based on the Koopman operator,a high-dimensional linear system model approximating the actual system is obtained online.The upper bound of the discrepancy between the identified model and the actual system is estimated using real-time prediction error,which is then utilized in the design of a tube-based robust model predictive controller.The effectiveness of the proposed approach is validated by numerical simulation.
基金the Strategic Research Plan of the Centre for Marine Technology and Ocean Engineeringfinanced by the Portuguese Foundation for Science and Technology (Fundacao para a Ciência e Tecnologia-FCT) under contract UIDB/UIDP/00134/2020。
文摘A state-of-the-art review is presented of mathematical manoeuvring models for surface ships and parameter estimation methods that have been used to build mathematical manoeuvring models for surface ships. In the first part, the classical manoeuvring models, such as the Abkowitz model, MMG, Nomoto and their revised versions, are revisited and the model structure with the hydrodynamic coefficients is also presented.Then, manoeuvring tests, including both the scaled model tests and sea trials, are introduced with the fact that the test data is critically important to obtain reliable results using parameter estimation methods. In the last part, selected papers published in journals and international conferences are reviewed and the statistical analysis of the manoeuvring models, test data, system identification methods and environmental disturbances used in the paper is presented.
基金supported by the National Science and Technology Major Project(Grant No.J2019-Ⅳ-0003-0070).
文摘A novel parameter identification method for magnetic levitation bearing rotor systems is proposed,based on the modulation function method.The fundamental principle of the modulation function method for parameter identification is derived on the basis of the characteristics of the modulation function.The transformation of the differential equation model of a continuous system into a general algebraic equation model is effectively achieved,thereby avoiding the influence of errors introduced by the initial value and differential derivation of the system.Modulation function method parameter identification models have been established for single-degree-of-freedom and multi-degree-of-freedom magnetic levitation bearing rotor systems.The influence of different parameters of Hartley modulation function on the accuracy of system parameter identification has been investigated,thus providing a basis for the design of Hartley modulation function parameters.Simulation and experimental results demonstrate that the modulation function method can effectively identify system parameters despite the presence of system noise.
基金supported by the National Natural Science Foundation of China(62263014)the Yunnan Provincial Basic Research Project(202301AT070443,202401AT070344).
文摘Accurate identification of unknown internal parameters in photovoltaic(PV)cells is crucial and significantly affects the subsequent system-performance analysis and control.However,noise,insufficient data acquisition,and loss of recorded data can deteriorate the extraction accuracy of unknown parameters.Hence,this study proposes an intelligent parameter-identification strategy that integrates artificial ecosystem optimization(AEO)and a Bayesian neural network(BNN)for PV cell parameter extraction.A BNN is used for data preprocessing,including data denoising and prediction.Furthermore,the AEO algorithm is utilized to identify unknown parameters in the single-diode model(SDM),double-diode model(DDM),and three-diode model(TDM).Nine other metaheuristic algorithms(MhAs)are adopted for an unbiased and comprehensive validation.Simulation results show that BNN-based data preprocessing com-bined with effective MhAs significantly improve the parameter-extraction accuracy and stability compared with methods without data preprocessing.For instance,under denoised data,the accuracies of the SDM,DDM,and TDM increase by 99.69%,99.70%,and 99.69%,respectively,whereas their accuracy improvements increase by 66.71%,59.65%,and 70.36%,respectively.
文摘BACKGROUND The Asia-Pacific Colorectal Screening(APCS)score was designed with the purpose of distinguishing individuals at high risk(HR)for colorectal advanced neoplasia(AN).Traditional Chinese medicine(TCM)constitution was also linked with colorectal cancer(CRC).AIM To integrate the APCS score with TCM constitution identification as a new algorithm to screen for CRC.METHODS A cross-sectional multicenter study was carried out in three hospitals,enrolling 1430 patients who were asymptomatic and undergoing screening colonoscopy from 2022 to 2023.Patients were considered to have average risk,moderate risk,or HR with their APCS score.Odd ratios assessed the relationship between TCM constitution and disease progression.A TCM constitution risk score was created.The sensitivity and specificity of the new algorithm were calculated to evaluate diagnostic performance in detecting advanced adenoma(AA),CRC,and AN.RESULTS Of the 1430 patients,370(25.9%)were categorized as average risk,755(52.8%)as moderate risk,and 305(21.3%)as HR.Using the combined APCS score and the TCM constitution(damp-heat,qi-deficiency,yang-deficiency,phlegm-dampness,and inherited special constitution as positive)algorithm,72.2%of patients with AA and 73.7%of patients with AN were detected.Compared with the APCS score alone,the new algorithm significantly improved the sensitivity for screening AA[72.2%,95%confidence interval(CI):64.4%-80.0%vs 49.2%,95%CI:40.5%-57.9%]and AN(73.7%,95%CI:66.4%-81.1%vs 51.1%,95%CI:42.7%-59.5%).CONCLUSION The combination of APCS and TCM constitution identification questionnaires was valuable in identifying Chinese individuals who were asymptomatic for colorectal screening prioritization.
基金supported by the National Natural Science Foundation of China under Grant U21A20449The Zhongguancun Project under Grant 23120035.
文摘Synthetic aperture radar(SAR)radio frequency identification(RFID)localization is widely used for automated guided vehicles(AGVs)in the industrial internet of things(IIoT).However,the AGV’s speeds are limited by the phase difference(PD)of two neighboring readers.In this paper,an inertial navigation system(INS)based SAR RFID localization method(ISRL)where AGV moves nonlinearly.To relax the speed limitation,a new phase-unwrapping method based on the similarity of PDs(PU-SPD)is proposed to deal with the PD ambiguity when the AGV speed exceeds 60km/h.In localization,the gauss-newton algorithm(GN)is employed and an initial value estimation scheme based on variable substitution(IVE-VS)is proposed to improve its positioning accuracy and the convergence rate.Thus,ISRL is a combination of IVE-VS and GN.Moreover,the Cramer-Rao lower bound(CRLB)and the speed limitation is derived.Simulation results show that the ISRL can converge after two iterations,and the positioning accuracy can achieve 7.50cm at a phase noise levelσ=0.18,which is 35%better than the Hyperbolic unbiased estimation localization(HyUnb).
