This study investigated the filtration and continuous regeneration of a particulate filter system on an engine test bench, consisting of a diesel oxidation catalyst（DOC） and a catalyzed diesel particulate filter（C...This study investigated the filtration and continuous regeneration of a particulate filter system on an engine test bench, consisting of a diesel oxidation catalyst（DOC） and a catalyzed diesel particulate filter（CDPF）. Both the DOC and the CDPF led to a high conversion of NO to NO2 for continuous regeneration. The filtration efficiency on solid particle number（SPN） was close to100%. The post-CDPF particles were mainly in accumulation mode. The downstream SPN was sensitively influenced by the variation of the soot loading. This phenomenon provides a method for determining the balance point temperature by measuring the trend of SPN concentration.展开更多
Purification capacity of a faucet mounted type water filter for home use was evaluated, particularly with regard to microbiological performance under different running conditions. Biofilms were formed inside the filte...Purification capacity of a faucet mounted type water filter for home use was evaluated, particularly with regard to microbiological performance under different running conditions. Biofilms were formed inside the filter, affecting the bacterial quality of the effluent water. Low flow rate, long stagnation period and high filter temperature were found favorable for bacterial growth inside. By commercial analytical profile index （API） kits, ten different bacterial species were identified in drinking water, four of which were probably contributed to the biofilm formation since they were also present in the biofilm. Fluorescence in situ hybridization （FISH） was used to confirm the API identification results, and direct viable count （DVC） method was employed to improve the sensitivity of FISH for the isolated Acinetobacter spp. and Pseudomonas putida as models. Relationship between the filter operating condition and the bacterial community alteration was partly revealed, which could provide the basic knowledge for the filter design and its practical use.展开更多
To simulate steady airflows inside of wall-flow diesel particulate filters （DPF） with different reverse blowing pipes collocation, a mathematical model of the flow in a DPF is established by an equivalent continuum ...To simulate steady airflows inside of wall-flow diesel particulate filters （DPF） with different reverse blowing pipes collocation, a mathematical model of the flow in a DPF is established by an equivalent continuum approach. The experimental results agree well with the theoretical values calculated from the model. Simulation shows that the velocity and the pressure distribution of the filters in the regenerative process are key factors to the filter＇s regeneration. How to decrease the mal-distribution of the flow in the filter and how to achieve the better regenerative performance at the least cost of air consumption in the regenerative process are the ultimate goals of the study. Calculation and experiments show that the goals can be realized through adjusting the angle of two reverse blowing pipes and their relative location suitably.展开更多
The output feedback active disturbance rejection control of a valve-controlled cylinder electro-hydraulic servo system is investigated in this paper.First,a comprehensive nonlinear mathematical model that encompasses ...The output feedback active disturbance rejection control of a valve-controlled cylinder electro-hydraulic servo system is investigated in this paper.First,a comprehensive nonlinear mathematical model that encompasses both matched and mismatched disturbances is formulated.Due to the fact that only position information can be measured,a linear Extended State Observer(ESO)is introduced to estimate unknown states and matched disturbances,while a dedicated disturbance observer is constructed to estimate mismatched disturbances.Different from the traditional observer results,the design of the disturbance observer used in this study is carried out under the constraint of output feedback.Furthermore,an output feedback nonlinear controller is proposed leveraging the aforementioned observers to achieve accurate trajectory tracking.To mitigate the inherent differential explosion problem of the traditional backstepping framework,a finite-time stable command filter is incorporated.Simultaneously,considering transient filtering errors,a set of error compensation signals are designed to counter their negative impact effectively.Theoretical analysis affirms that the proposed control strategy ensures the boundedness of all signals within the closed-loop system.Additionally,under the specific condition of only time-invariant disturbances in the system,the conclusion of asymptotic stability is established.Finally,the algorithm’s efficacy is validated through comparative experiments.展开更多
Fault detection in industrial robot drive systems is a critical aspect of ensuring operational reliability and efficiency.To address the challenge of balancing accuracy and robustness in existing fault detection metho...Fault detection in industrial robot drive systems is a critical aspect of ensuring operational reliability and efficiency.To address the challenge of balancing accuracy and robustness in existing fault detection methods,this paper proposes an enhanced fault detection method based on the unscented Kalman filter(UKF).A comprehensive mathematical model of the brushless DC motor drive system is developed to provide a theoretical foundation for the design of subsequent fault detection methods.The conventional UKF estimation process is detailed,and its limitations in balancing estimation accuracy and robustness are addressed by introducing a dynamic,time-varying boundary layer.To further enhance detection performance,the method incorporates residual analysis using improved z-score and signal-tonoise ratio(SNR)metrics.Numerical simulations under both fault-free and faulty conditions demonstrate that the proposed approach achieves lower root mean square error(RMSE)in fault-free scenarios and provides reliable fault detection.These results highlight the potential of the proposed method to enhance the reliability and robustness of fault detection in industrial robot drive systems.展开更多
Dear Editor,This letter presents an improved repetitive controller(IRC) that uses a complex-coefficient filter to enhance the tracking performance of a system for periodic signals. Compared with the low-pass filter us...Dear Editor,This letter presents an improved repetitive controller(IRC) that uses a complex-coefficient filter to enhance the tracking performance of a system for periodic signals. Compared with the low-pass filter used in the conventional repetitive controller(CRC), the complex-coefficient filter causes less change in the phase and amplitude of a signal at the frequencies of the periodic signal, especially at the fundamental frequency, when the two filters have the same cutofffrequency.展开更多
When the proton exchange membrane fuel cell(PEMFC)system is running,there will be a condition that does not require power output for a short time.In order to achieve zero power output under low power consumption,it is...When the proton exchange membrane fuel cell(PEMFC)system is running,there will be a condition that does not require power output for a short time.In order to achieve zero power output under low power consumption,it is necessary to consider the diversity of control targets and the complexity of dynamic models,which brings the challenge of high-precision tracking control of the stack output power and cathode intake flow.For system idle speed control,a modelbased nonlinear control framework is constructed in this paper.Firstly,the nonlinear dynamic model of output power and cathode intake flow is derived.Secondly,a control scheme combining nonlinear extended Kalman filter observer and state feedback controller is designed.Finally,the control scheme is verified on the PEMFC experimental platform and compared with the proportion-integration-differentiation(PID)controller.The experimental results show that the control strategy proposed in this paper can realize the idle speed control of the fuel cell system and achieve the purpose of zero power output.Compared with PID controller,it has faster response speed and better system dynamics.展开更多
Active damping(AD)strategy is an economical and efficient method to solve the resonant problem of the permanent magnet synchronous motor(PMSM)drive system with inductor-capacitor(LC)sine wave filter.In this article,th...Active damping(AD)strategy is an economical and efficient method to solve the resonant problem of the permanent magnet synchronous motor(PMSM)drive system with inductor-capacitor(LC)sine wave filter.In this article,the AD methods used in PMSM drive system are classified as inherent damping(ID),state variable feedback,and digital filter.Based on this,the purpose of this article is to provide an overview and analysis of the AD methods on PMSM drive system in recent years,and to comprehensively review,compare,and summarize the stability,dynamic performance,robustness,and algorithm complexity.Furthermore,a new expansion of AD method based on capacitor current feedback with high-pass filter(HPF-CCF)is studied to ensure the effectiveness when the resonant frequency is around sixth of the sampling frequency.The simulation and experimental results validate the effectiveness of theoretical analysis.展开更多
This study introduces an advanced recommender system for technology enhanced learning(TEL)that synergizes neural collaborative filtering,sentiment analysis,and an adaptive learning rate to address the limitations of t...This study introduces an advanced recommender system for technology enhanced learning(TEL)that synergizes neural collaborative filtering,sentiment analysis,and an adaptive learning rate to address the limitations of traditional TEL systems.Recognizing the critical gap in existing approaches—primarily their neglect of user emotional feedback and static learning paths—our model innovatively incorporates sentiment analysis to capture and respond to nuanced emotional feedback from users.Utilizing bidirectional encoder representations from Transformers for sentiment analysis,our system not only understands but also respects user privacy by processing feedback without revealing sensitive information.The adaptive learning rate,inspired by AdaGrad,allows our model to adjust its learning trajectory based on the sentiment scores associated with user feedback,ensuring a dynamic response to both positive and negative sentiments.This dual approach enhances the system’s adapt-ability to changing user preferences and improves its contentment understanding.Our methodology involves a comprehensive analysis of both the content of learning materials and the behaviors and preferences of learners,facilitating a more personalized learning experience.By dynamically adjusting recommendations based on real-time user data and behavioral analysis,our system leverages the collective insights of similar users and rele-vant content.We validated our approach against three datasets-MovieLens,Amazon,and a proprietary TEL dataset—and saw significant improvements in recommendation precision,F-score,and mean absolute error.The results indicate the potential of integrating sentiment analysis and adaptive learning rates into TEL recommender systems,marking a step forward in developing more responsive and user-centric educational technologies.This study paves the way for future advancements in TEL systems,emphasizing the importance of emotional intelli-gence and adaptability in enhancing the learning experience.展开更多
The structural dynamic response reconstruction technology can extract unmeasured information from limited measured data,significantly impacting vibration control,load identification,parameter identification,fault diag...The structural dynamic response reconstruction technology can extract unmeasured information from limited measured data,significantly impacting vibration control,load identification,parameter identification,fault diagnosis,and related fields.This paper proposes a dynamic response reconstruction method based on the Kalman filter,which simultaneously identifies external excitation and reconstructs dynamic responses at unmeasured positions.The weighted least squares method determines the load weighting matrix for excitation identification,while the minimum variance unbiased estimation determines the Kalman filter gain.The excitation prediction Kalman filter is constructed through time,excitation,and measurement updates.Subsequently,the response at the target point is reconstructed using the state vector,observation matrix,and excitation influence matrix obtained through the excitation prediction Kalman filter algorithm.An algorithm for reconstructing responses in continuous system using the excitation prediction Kalman filtering algorithm in modal space is derived.The proposed structural dynamic response reconstruction method evaluates the response reconstruction and the load identification performance under various load types and errors through simulation examples.Results demonstrate the accurate excitation identification under different load conditions and simultaneous reconstruction of target point responses,verifying the feasibility and reliability of the proposed method.展开更多
In this work,we mainly study Bell nonlocality and quantum steerability of two-coupled double quantum dots(DQDs)system via local filtering operation.We compare and analyze the influence of the Coulomb potential,tempera...In this work,we mainly study Bell nonlocality and quantum steerability of two-coupled double quantum dots(DQDs)system via local filtering operation.We compare and analyze the influence of the Coulomb potential,temperature,tunneling parameter and local filtering operation on quantum steering and Bell nonlocality in the system.The results show that quantum steering and nonlocality first increase and then decrease but never vanish even for the stronger value of the Coulomb potential.Quantum steering and Bell nonlocality would degrade with the increase of temperature.The filtering process does not increase the degree of steerability,but decreases the range of quantum steerability.In addition,it is noteworthy that a peculiar phenomenon exists:the Einstein-Podolsky-Rosen(EPR)steering asymmetry between Alice and Bob first increase,then decrease to zero and finally increases as the tunneling strength increases.However,this phenomenon does not appear with no operation between Alice and Bob.展开更多
To accelerate the large-scale integration of renewable energy and support the strategic goals of“carbon peaking and carbon neutrality,”High Voltage Direct Current(HVDC)transmission technology has made significant br...To accelerate the large-scale integration of renewable energy and support the strategic goals of“carbon peaking and carbon neutrality,”High Voltage Direct Current(HVDC)transmission technology has made significant breakthroughs.Among the various approaches,a hybrid DC transmission system that combines a line-commutated converter(LCC)and a voltage source converter(VSC)retains the inherent fault self-clearing capability of the LCC topology while mitigating the risk of commutation failure when connected to a weak grid.In this paper,based on the harmonic generation mechanisms of hybrid DC transmission systems,an improved 3-pulse harmonic source model of the LCC and a dynamic phase-sequence harmonic analysis model of the VSC are developed.The integrated harmonic model demonstrates strong adaptability in accurately calculating DC-side harmonics under the influence of power imbalances and background harmonics.Based on this model,the fundamental characteristics of DC-side harmonics in hybrid DC transmission systems are analyzed.To mitigate harmonic effects,this paper proposes an LCLC-trap2 high-order filter structure with parallel RC damping circuits and a co-optimized design of filter parameters.Finally,a±500 kV hybrid DC transmission systemismodeled using theMATLAB/Simulink platform,and the harmonic filtering performances of the conventional LC filter,the Butterworth filter,and the proposed filter are simulated and compared.The results verify that the proposed filter offers superior performance in suppressing low-order harmonics under nonideal operating conditions.展开更多
This article proposes an adaptive extended Kalman filter(EKF)for nonlinear cyber-physical systems(CPSs)under unknown inputs and non-Gaussian noises.It is known that the traditional extended Kalman filter is applicable...This article proposes an adaptive extended Kalman filter(EKF)for nonlinear cyber-physical systems(CPSs)under unknown inputs and non-Gaussian noises.It is known that the traditional extended Kalman filter is applicable to nonlinear systems with Gaussian white noise.The system is reformulated with intermediate variables to expand the application of nonlinear systems under unknown inputs and non-Gaussian noises,which help decompose unknown input estimation into residual tracking and state observation subproblems.By introducing the orthogonal principle of innovation and attenuation factor,the intermediate variables-based filter can improve the estimation performance under non-Gaussian noises and unknown inputs.Simulation results validate the effectiveness of the proposed method.展开更多
This study considers the state estimation problem of the circuit breakers(CBs),solving for randomabrupt changes that occurred in power systems.With the abrupt changes randomly occurring,it is represented in a Markov c...This study considers the state estimation problem of the circuit breakers(CBs),solving for randomabrupt changes that occurred in power systems.With the abrupt changes randomly occurring,it is represented in a Markov chain,and then the CBs can be considered as a Markov jump system(MJS).In these MJSs,the transition probabilities are obtained from historical statistical data of the random abrupt changes when the faults occurred.Considering that the traditional Kalman filter(KF)frameworks based on MJS only depend on the subsystem of MJS,but neglect the stochastic jump between different subsystems.This study utilized the derandomization technique which transforms the stochastic MJS to a deterministic system to introduce the stochastic mode jumping in MJS,in which the state is still in the same norm,and the Lyapunov function is derived to show the stability condition of the systems,which proved that the transformed deterministic system is more conservative than the original MJS mathematically.After that,the Kalman filter algorithm is designed for estimating the state of the CBs depending on the transformed deterministic system.With the help of the Kalman filter,the estimation performance is derived by the recursive state estimation algorithm for the CBs.Furthermore,a single machine infinite-bus(SMIB)power system and a three-bus large scale system are proposed as practical examples to validate the effectiveness of the proposed algorithm.展开更多
The state estimation of the flexible multibody systems is a vital issue since it is the base of effective control and condition monitoring.The research on the state estimation method of flexible multibody system with ...The state estimation of the flexible multibody systems is a vital issue since it is the base of effective control and condition monitoring.The research on the state estimation method of flexible multibody system with large deformation and large rotation remains rare.In this investigation,a state estimator based on multiple nonlinear Kalman filtering algorithms was designed for the flexible multibody systems containing large flexibility components that were discretized by absolute nodal coordinate formulation(ANCF).The state variable vector was constructed based on the independent coordinates which are identified through the constraint Jacobian.Three types of Kalman filters were used to compare their performance in the state estimation for ANCF.Three cases including flexible planar rotating beam,flexible four-bar mechanism,and flexible rotating shaft were employed to verify the proposed state estimator.According to the different performances of the three types of Kalman filter,suggestions were given for the construction of the state estimator for the flexible multibody system.展开更多
Dear Editor,This letter deals with the distributed recursive set-membership filtering(DRSMF)issue for state-saturated systems under encryption-decryption mechanism.To guarantee the data security,the encryption-decrypt...Dear Editor,This letter deals with the distributed recursive set-membership filtering(DRSMF)issue for state-saturated systems under encryption-decryption mechanism.To guarantee the data security,the encryption-decryption mechanism is considered in the signal transmission process.Specifically,a novel DRSMF scheme is developed such that,for both state saturation and encryption-decryption mechanism,the filtering error(FE)is limited to the ellipsoid domain.Then,the filtering error constraint matrix(FECM)is computed and a desirable filter gain is derived by minimizing the FECM.Besides,the bound-edness evaluation of the FECM is provided.展开更多
Dear Editor,Through distributed machine learning,multi-UAV systems can achieve global optimization goals without a centralized server,such as optimal target tracking,by leveraging local calculation and communication w...Dear Editor,Through distributed machine learning,multi-UAV systems can achieve global optimization goals without a centralized server,such as optimal target tracking,by leveraging local calculation and communication with neighbors.In this work,we implement the stochastic gradient descent algorithm(SGD)distributedly to optimize tracking errors based on local state and aggregation of the neighbors'estimation.However,Byzantine agents can mislead neighbors,causing deviations from optimal tracking.We prove that the swarm achieves resilient convergence if aggregated results lie within the normal neighbors'convex hull,which can be guaranteed by the introduced centerpoint-based aggregation rule.In the given simulated scenarios,distributed learning using average,geometric median(GM),and coordinate-wise median(CM)based aggregation rules fail to track the target.Compared to solely using the centerpoint aggregation method,our approach,which combines a pre-filter with the centroid aggregation rule,significantly enhances resilience against Byzantine attacks,achieving faster convergence and smaller tracking errors.展开更多
This study systematically investigated the influence of deposition rate on the structure,broadband opti⁃cal properties(1.0-13.0μm),and stress characteristics of Germanium(Ge)films.Additionally,a method for enhancing ...This study systematically investigated the influence of deposition rate on the structure,broadband opti⁃cal properties(1.0-13.0μm),and stress characteristics of Germanium(Ge)films.Additionally,a method for enhancing the performance of infrared filters based on rate-modulated deposition of Ge films was proposed.The optical absorption of Ge films in the short-wave infrared(SWIR)and long-wave infrared(LWIR)bands can be effectively reduced by modulating the deposition rate.As the deposition rate increases,the Ge films maintain an amorphous structure.The optical constants of the films in the 1.0-2.5μm and 2.5-13.0μm bands were precisely determined using the Cody-Lorentz model and the classical Lorentz oscillator model,respectively.Notably,high⁃er deposition rates result in a gradual increase in the refractive index.The extinction coefficient increases with the deposition rate in the SWIR region,attributed to the widening of the Urbach tail,while it decreases in the LWIR region due to the reduced absorption caused by the Ge-O stretching mode.Additionally,the films exhibit a tensile stress that decreases with increasing deposition rate.Finally,the effectiveness of the proposed fabrication method for an infrared filter with Ge films deposited at an optimized rate was demonstrated through practical examples.This work provides theoretical and technical support for the application of Ge films in high-performance infrared filters.展开更多
The Savitzky-Golay(SG)filter,which employs polynomial least-squares approximations to smooth data and estimate derivatives,is widely used for processing noisy data.However,noise suppression by the SG filter is recogni...The Savitzky-Golay(SG)filter,which employs polynomial least-squares approximations to smooth data and estimate derivatives,is widely used for processing noisy data.However,noise suppression by the SG filter is recognized to be limited at data boundaries and high frequencies,which can significantly reduce the signal-to-noise ratio(SNR).To solve this problem,a novel method synergistically integrating Principal Component Analysis(PCA)with SG filtering is proposed in this paper.This approach avoids the is-sue of excessive smoothing associated with larger window sizes.The proposed PCA-SG filtering algorithm was applied to a CO gas sensing system based on Cavity Ring-Down Spectroscopy(CRDS).The perform-ance of the PCA-SG filtering algorithm is demonstrated through comparison with Moving Average Filtering(MAF),Wavelet Transformation(WT),Kalman Filtering(KF),and the SG filter.The results demonstrate that the proposed algorithm exhibits superior noise reduction capabilities compared to the other algorithms evaluated.The SNR of the ring-down signal was improved from 11.8612 dB to 29.0913 dB,and the stand-ard deviation of the extracted ring-down time constant was reduced from 0.037μs to 0.018μs.These results confirm that the proposed PCA-SG filtering algorithm effectively improves the smoothness of the ring-down curve data,demonstrating its feasibility.展开更多
1 Introduction Recently,the increasing demand for advanced telecommunication systems has spurred extensive research into bandpass filters(BPFs),with particular emphasis on miniaturization,reduction of insertion loss(I...1 Introduction Recently,the increasing demand for advanced telecommunication systems has spurred extensive research into bandpass filters(BPFs),with particular emphasis on miniaturization,reduction of insertion loss(IL),and enhancement of upper stopband rejection(Huang et al.,2021;Snyder et al.,2021;Lin et al.,2023;Zeng et al.,2023).展开更多
基金supported by the National High Technology Research and Development Program of China(863)(No.2013AA065304)
文摘This study investigated the filtration and continuous regeneration of a particulate filter system on an engine test bench, consisting of a diesel oxidation catalyst（DOC） and a catalyzed diesel particulate filter（CDPF）. Both the DOC and the CDPF led to a high conversion of NO to NO2 for continuous regeneration. The filtration efficiency on solid particle number（SPN） was close to100%. The post-CDPF particles were mainly in accumulation mode. The downstream SPN was sensitively influenced by the variation of the soot loading. This phenomenon provides a method for determining the balance point temperature by measuring the trend of SPN concentration.
基金supported by the Proctor and Gamble Company and in part by Boshidian Fund of Ministry of Education of China(No.200800030046)
文摘Purification capacity of a faucet mounted type water filter for home use was evaluated, particularly with regard to microbiological performance under different running conditions. Biofilms were formed inside the filter, affecting the bacterial quality of the effluent water. Low flow rate, long stagnation period and high filter temperature were found favorable for bacterial growth inside. By commercial analytical profile index （API） kits, ten different bacterial species were identified in drinking water, four of which were probably contributed to the biofilm formation since they were also present in the biofilm. Fluorescence in situ hybridization （FISH） was used to confirm the API identification results, and direct viable count （DVC） method was employed to improve the sensitivity of FISH for the isolated Acinetobacter spp. and Pseudomonas putida as models. Relationship between the filter operating condition and the bacterial community alteration was partly revealed, which could provide the basic knowledge for the filter design and its practical use.
基金This project is supported by National Hi-tech Research and DevelopmentProgram of China (863 Program, No.2003AA643010B).
文摘To simulate steady airflows inside of wall-flow diesel particulate filters （DPF） with different reverse blowing pipes collocation, a mathematical model of the flow in a DPF is established by an equivalent continuum approach. The experimental results agree well with the theoretical values calculated from the model. Simulation shows that the velocity and the pressure distribution of the filters in the regenerative process are key factors to the filter＇s regeneration. How to decrease the mal-distribution of the flow in the filter and how to achieve the better regenerative performance at the least cost of air consumption in the regenerative process are the ultimate goals of the study. Calculation and experiments show that the goals can be realized through adjusting the angle of two reverse blowing pipes and their relative location suitably.
基金supported by the National Key R&D Program of China(No.2021YFB2011300)the Special Funds Project for the Transformation of Scientific and Technological Achievements of Jiangsu Province,China(No.BA2023039)+1 种基金the National Natural Science Foundation of China(No.52075262)the Fundamental Research Funds for the Central Universities,China(No.30922010706).
文摘The output feedback active disturbance rejection control of a valve-controlled cylinder electro-hydraulic servo system is investigated in this paper.First,a comprehensive nonlinear mathematical model that encompasses both matched and mismatched disturbances is formulated.Due to the fact that only position information can be measured,a linear Extended State Observer(ESO)is introduced to estimate unknown states and matched disturbances,while a dedicated disturbance observer is constructed to estimate mismatched disturbances.Different from the traditional observer results,the design of the disturbance observer used in this study is carried out under the constraint of output feedback.Furthermore,an output feedback nonlinear controller is proposed leveraging the aforementioned observers to achieve accurate trajectory tracking.To mitigate the inherent differential explosion problem of the traditional backstepping framework,a finite-time stable command filter is incorporated.Simultaneously,considering transient filtering errors,a set of error compensation signals are designed to counter their negative impact effectively.Theoretical analysis affirms that the proposed control strategy ensures the boundedness of all signals within the closed-loop system.Additionally,under the specific condition of only time-invariant disturbances in the system,the conclusion of asymptotic stability is established.Finally,the algorithm’s efficacy is validated through comparative experiments.
基金Supported by the Natural Science Foundation of the Higher Education Institutions of Jiangsu Province(22KJB520012)the Research Project on Higher Education Reform in Jiangsu Province(2023JSJG781)the College Student Innovation and Entrepreneurship Training Program Project(202313571008Z)。
文摘Fault detection in industrial robot drive systems is a critical aspect of ensuring operational reliability and efficiency.To address the challenge of balancing accuracy and robustness in existing fault detection methods,this paper proposes an enhanced fault detection method based on the unscented Kalman filter(UKF).A comprehensive mathematical model of the brushless DC motor drive system is developed to provide a theoretical foundation for the design of subsequent fault detection methods.The conventional UKF estimation process is detailed,and its limitations in balancing estimation accuracy and robustness are addressed by introducing a dynamic,time-varying boundary layer.To further enhance detection performance,the method incorporates residual analysis using improved z-score and signal-tonoise ratio(SNR)metrics.Numerical simulations under both fault-free and faulty conditions demonstrate that the proposed approach achieves lower root mean square error(RMSE)in fault-free scenarios and provides reliable fault detection.These results highlight the potential of the proposed method to enhance the reliability and robustness of fault detection in industrial robot drive systems.
基金supported in part by the National Natural Science Foundation of China(61873348,6230 3266,62273200)JSPS(Japan Society for the Promotion of Science) KAKENHI(22H03998,23K25252)
文摘Dear Editor,This letter presents an improved repetitive controller(IRC) that uses a complex-coefficient filter to enhance the tracking performance of a system for periodic signals. Compared with the low-pass filter used in the conventional repetitive controller(CRC), the complex-coefficient filter causes less change in the phase and amplitude of a signal at the frequencies of the periodic signal, especially at the fundamental frequency, when the two filters have the same cutofffrequency.
基金Supported by the Major Science and Technology Projects in Jilin Province and Changchun City(20220301010GX).
文摘When the proton exchange membrane fuel cell(PEMFC)system is running,there will be a condition that does not require power output for a short time.In order to achieve zero power output under low power consumption,it is necessary to consider the diversity of control targets and the complexity of dynamic models,which brings the challenge of high-precision tracking control of the stack output power and cathode intake flow.For system idle speed control,a modelbased nonlinear control framework is constructed in this paper.Firstly,the nonlinear dynamic model of output power and cathode intake flow is derived.Secondly,a control scheme combining nonlinear extended Kalman filter observer and state feedback controller is designed.Finally,the control scheme is verified on the PEMFC experimental platform and compared with the proportion-integration-differentiation(PID)controller.The experimental results show that the control strategy proposed in this paper can realize the idle speed control of the fuel cell system and achieve the purpose of zero power output.Compared with PID controller,it has faster response speed and better system dynamics.
基金supported in part by the National Natural Science Foundational of China under Grants 62373363 and 52007190
文摘Active damping(AD)strategy is an economical and efficient method to solve the resonant problem of the permanent magnet synchronous motor(PMSM)drive system with inductor-capacitor(LC)sine wave filter.In this article,the AD methods used in PMSM drive system are classified as inherent damping(ID),state variable feedback,and digital filter.Based on this,the purpose of this article is to provide an overview and analysis of the AD methods on PMSM drive system in recent years,and to comprehensively review,compare,and summarize the stability,dynamic performance,robustness,and algorithm complexity.Furthermore,a new expansion of AD method based on capacitor current feedback with high-pass filter(HPF-CCF)is studied to ensure the effectiveness when the resonant frequency is around sixth of the sampling frequency.The simulation and experimental results validate the effectiveness of theoretical analysis.
文摘This study introduces an advanced recommender system for technology enhanced learning(TEL)that synergizes neural collaborative filtering,sentiment analysis,and an adaptive learning rate to address the limitations of traditional TEL systems.Recognizing the critical gap in existing approaches—primarily their neglect of user emotional feedback and static learning paths—our model innovatively incorporates sentiment analysis to capture and respond to nuanced emotional feedback from users.Utilizing bidirectional encoder representations from Transformers for sentiment analysis,our system not only understands but also respects user privacy by processing feedback without revealing sensitive information.The adaptive learning rate,inspired by AdaGrad,allows our model to adjust its learning trajectory based on the sentiment scores associated with user feedback,ensuring a dynamic response to both positive and negative sentiments.This dual approach enhances the system’s adapt-ability to changing user preferences and improves its contentment understanding.Our methodology involves a comprehensive analysis of both the content of learning materials and the behaviors and preferences of learners,facilitating a more personalized learning experience.By dynamically adjusting recommendations based on real-time user data and behavioral analysis,our system leverages the collective insights of similar users and rele-vant content.We validated our approach against three datasets-MovieLens,Amazon,and a proprietary TEL dataset—and saw significant improvements in recommendation precision,F-score,and mean absolute error.The results indicate the potential of integrating sentiment analysis and adaptive learning rates into TEL recommender systems,marking a step forward in developing more responsive and user-centric educational technologies.This study paves the way for future advancements in TEL systems,emphasizing the importance of emotional intelli-gence and adaptability in enhancing the learning experience.
基金supported by the National Natural Science Foundation of China(Nos.12372066,U23B6009,52171261)the Aeronautical Science Fund(No.20240013052002)the Qing Lan Project。
文摘The structural dynamic response reconstruction technology can extract unmeasured information from limited measured data,significantly impacting vibration control,load identification,parameter identification,fault diagnosis,and related fields.This paper proposes a dynamic response reconstruction method based on the Kalman filter,which simultaneously identifies external excitation and reconstructs dynamic responses at unmeasured positions.The weighted least squares method determines the load weighting matrix for excitation identification,while the minimum variance unbiased estimation determines the Kalman filter gain.The excitation prediction Kalman filter is constructed through time,excitation,and measurement updates.Subsequently,the response at the target point is reconstructed using the state vector,observation matrix,and excitation influence matrix obtained through the excitation prediction Kalman filter algorithm.An algorithm for reconstructing responses in continuous system using the excitation prediction Kalman filtering algorithm in modal space is derived.The proposed structural dynamic response reconstruction method evaluates the response reconstruction and the load identification performance under various load types and errors through simulation examples.Results demonstrate the accurate excitation identification under different load conditions and simultaneous reconstruction of target point responses,verifying the feasibility and reliability of the proposed method.
基金supported by the University-Industry Collaborative Education Program(Project No.220506627183928).
文摘In this work,we mainly study Bell nonlocality and quantum steerability of two-coupled double quantum dots(DQDs)system via local filtering operation.We compare and analyze the influence of the Coulomb potential,temperature,tunneling parameter and local filtering operation on quantum steering and Bell nonlocality in the system.The results show that quantum steering and nonlocality first increase and then decrease but never vanish even for the stronger value of the Coulomb potential.Quantum steering and Bell nonlocality would degrade with the increase of temperature.The filtering process does not increase the degree of steerability,but decreases the range of quantum steerability.In addition,it is noteworthy that a peculiar phenomenon exists:the Einstein-Podolsky-Rosen(EPR)steering asymmetry between Alice and Bob first increase,then decrease to zero and finally increases as the tunneling strength increases.However,this phenomenon does not appear with no operation between Alice and Bob.
基金funded by the Natural Science Foundation of Chongqing(CSTB2023NSCQMSX0279)the Science and Technology Research Program of Chongqing Municipal Education Commission(KJQN202201119).
文摘To accelerate the large-scale integration of renewable energy and support the strategic goals of“carbon peaking and carbon neutrality,”High Voltage Direct Current(HVDC)transmission technology has made significant breakthroughs.Among the various approaches,a hybrid DC transmission system that combines a line-commutated converter(LCC)and a voltage source converter(VSC)retains the inherent fault self-clearing capability of the LCC topology while mitigating the risk of commutation failure when connected to a weak grid.In this paper,based on the harmonic generation mechanisms of hybrid DC transmission systems,an improved 3-pulse harmonic source model of the LCC and a dynamic phase-sequence harmonic analysis model of the VSC are developed.The integrated harmonic model demonstrates strong adaptability in accurately calculating DC-side harmonics under the influence of power imbalances and background harmonics.Based on this model,the fundamental characteristics of DC-side harmonics in hybrid DC transmission systems are analyzed.To mitigate harmonic effects,this paper proposes an LCLC-trap2 high-order filter structure with parallel RC damping circuits and a co-optimized design of filter parameters.Finally,a±500 kV hybrid DC transmission systemismodeled using theMATLAB/Simulink platform,and the harmonic filtering performances of the conventional LC filter,the Butterworth filter,and the proposed filter are simulated and compared.The results verify that the proposed filter offers superior performance in suppressing low-order harmonics under nonideal operating conditions.
基金Supported by the Foreign Experts Project of the Belt and Road Innovative Talent Exchange(No.DL2023016005L).
文摘This article proposes an adaptive extended Kalman filter(EKF)for nonlinear cyber-physical systems(CPSs)under unknown inputs and non-Gaussian noises.It is known that the traditional extended Kalman filter is applicable to nonlinear systems with Gaussian white noise.The system is reformulated with intermediate variables to expand the application of nonlinear systems under unknown inputs and non-Gaussian noises,which help decompose unknown input estimation into residual tracking and state observation subproblems.By introducing the orthogonal principle of innovation and attenuation factor,the intermediate variables-based filter can improve the estimation performance under non-Gaussian noises and unknown inputs.Simulation results validate the effectiveness of the proposed method.
文摘This study considers the state estimation problem of the circuit breakers(CBs),solving for randomabrupt changes that occurred in power systems.With the abrupt changes randomly occurring,it is represented in a Markov chain,and then the CBs can be considered as a Markov jump system(MJS).In these MJSs,the transition probabilities are obtained from historical statistical data of the random abrupt changes when the faults occurred.Considering that the traditional Kalman filter(KF)frameworks based on MJS only depend on the subsystem of MJS,but neglect the stochastic jump between different subsystems.This study utilized the derandomization technique which transforms the stochastic MJS to a deterministic system to introduce the stochastic mode jumping in MJS,in which the state is still in the same norm,and the Lyapunov function is derived to show the stability condition of the systems,which proved that the transformed deterministic system is more conservative than the original MJS mathematically.After that,the Kalman filter algorithm is designed for estimating the state of the CBs depending on the transformed deterministic system.With the help of the Kalman filter,the estimation performance is derived by the recursive state estimation algorithm for the CBs.Furthermore,a single machine infinite-bus(SMIB)power system and a three-bus large scale system are proposed as practical examples to validate the effectiveness of the proposed algorithm.
基金supported by the National Natural Science Foundation of China(Grant Nos.12272123 and 12302047)the Natural Science Foundation of Jiangsu Province(Grant No.BK20231185)the Postgraduate Research&Practice Innovation Program of Jiangsu Province(Grant No.SJCX24_0192).
文摘The state estimation of the flexible multibody systems is a vital issue since it is the base of effective control and condition monitoring.The research on the state estimation method of flexible multibody system with large deformation and large rotation remains rare.In this investigation,a state estimator based on multiple nonlinear Kalman filtering algorithms was designed for the flexible multibody systems containing large flexibility components that were discretized by absolute nodal coordinate formulation(ANCF).The state variable vector was constructed based on the independent coordinates which are identified through the constraint Jacobian.Three types of Kalman filters were used to compare their performance in the state estimation for ANCF.Three cases including flexible planar rotating beam,flexible four-bar mechanism,and flexible rotating shaft were employed to verify the proposed state estimator.According to the different performances of the three types of Kalman filter,suggestions were given for the construction of the state estimator for the flexible multibody system.
基金supported by the National Natural Science Foundation of China(12471416,12171124,12301567)the Heilongjiang Provincial Natural Science Foundation of China(PL2024F015)+2 种基金the Postdoctoral Science Foundation of Heilongjiang Province of China(LBH-Z22199)the Fundamental Research Foun-dation for Universities of Heilongjiang Province of China(2022-KYYWF-0141)the Alexander von Humboldt Foundation of Germany.
文摘Dear Editor,This letter deals with the distributed recursive set-membership filtering(DRSMF)issue for state-saturated systems under encryption-decryption mechanism.To guarantee the data security,the encryption-decryption mechanism is considered in the signal transmission process.Specifically,a novel DRSMF scheme is developed such that,for both state saturation and encryption-decryption mechanism,the filtering error(FE)is limited to the ellipsoid domain.Then,the filtering error constraint matrix(FECM)is computed and a desirable filter gain is derived by minimizing the FECM.Besides,the bound-edness evaluation of the FECM is provided.
基金supported By Guangdong Major Project of Basic and Applied Basic Research(2023B0303000009)Guangdong Basic and Applied Basic Research Foundation(2024A1515030153,2025A1515011587)+1 种基金Project of Department of Education of Guangdong Province(2023ZDZX4046)Shen-zhen Natural Science Fund(Stable Support Plan Program 20231122121608001),Ningbo Municipal Science and Technology Bureau(ZX2024000604).
文摘Dear Editor,Through distributed machine learning,multi-UAV systems can achieve global optimization goals without a centralized server,such as optimal target tracking,by leveraging local calculation and communication with neighbors.In this work,we implement the stochastic gradient descent algorithm(SGD)distributedly to optimize tracking errors based on local state and aggregation of the neighbors'estimation.However,Byzantine agents can mislead neighbors,causing deviations from optimal tracking.We prove that the swarm achieves resilient convergence if aggregated results lie within the normal neighbors'convex hull,which can be guaranteed by the introduced centerpoint-based aggregation rule.In the given simulated scenarios,distributed learning using average,geometric median(GM),and coordinate-wise median(CM)based aggregation rules fail to track the target.Compared to solely using the centerpoint aggregation method,our approach,which combines a pre-filter with the centroid aggregation rule,significantly enhances resilience against Byzantine attacks,achieving faster convergence and smaller tracking errors.
基金Supported by the National Natural Science Foundation of China(62275053,62275256)the National key Research and Development Program of China(2021YFB3701500)+1 种基金the Youth Innovation Promotion Association of the Chinese Academy of Sciences(2023248)the Eastern Talent Plan Youth Project 2022,the Shanghai Key Laboratory of Optical Coatings and Spectral Modulation(23dz2260500).
文摘This study systematically investigated the influence of deposition rate on the structure,broadband opti⁃cal properties(1.0-13.0μm),and stress characteristics of Germanium(Ge)films.Additionally,a method for enhancing the performance of infrared filters based on rate-modulated deposition of Ge films was proposed.The optical absorption of Ge films in the short-wave infrared(SWIR)and long-wave infrared(LWIR)bands can be effectively reduced by modulating the deposition rate.As the deposition rate increases,the Ge films maintain an amorphous structure.The optical constants of the films in the 1.0-2.5μm and 2.5-13.0μm bands were precisely determined using the Cody-Lorentz model and the classical Lorentz oscillator model,respectively.Notably,high⁃er deposition rates result in a gradual increase in the refractive index.The extinction coefficient increases with the deposition rate in the SWIR region,attributed to the widening of the Urbach tail,while it decreases in the LWIR region due to the reduced absorption caused by the Ge-O stretching mode.Additionally,the films exhibit a tensile stress that decreases with increasing deposition rate.Finally,the effectiveness of the proposed fabrication method for an infrared filter with Ge films deposited at an optimized rate was demonstrated through practical examples.This work provides theoretical and technical support for the application of Ge films in high-performance infrared filters.
文摘The Savitzky-Golay(SG)filter,which employs polynomial least-squares approximations to smooth data and estimate derivatives,is widely used for processing noisy data.However,noise suppression by the SG filter is recognized to be limited at data boundaries and high frequencies,which can significantly reduce the signal-to-noise ratio(SNR).To solve this problem,a novel method synergistically integrating Principal Component Analysis(PCA)with SG filtering is proposed in this paper.This approach avoids the is-sue of excessive smoothing associated with larger window sizes.The proposed PCA-SG filtering algorithm was applied to a CO gas sensing system based on Cavity Ring-Down Spectroscopy(CRDS).The perform-ance of the PCA-SG filtering algorithm is demonstrated through comparison with Moving Average Filtering(MAF),Wavelet Transformation(WT),Kalman Filtering(KF),and the SG filter.The results demonstrate that the proposed algorithm exhibits superior noise reduction capabilities compared to the other algorithms evaluated.The SNR of the ring-down signal was improved from 11.8612 dB to 29.0913 dB,and the stand-ard deviation of the extracted ring-down time constant was reduced from 0.037μs to 0.018μs.These results confirm that the proposed PCA-SG filtering algorithm effectively improves the smoothness of the ring-down curve data,demonstrating its feasibility.
基金supported by the National Natural Science Foundation of China(No.62371263)the Postgraduate Research&Practice Innovation Program of Jiangsu Province(No.SJCK25_1995).
文摘1 Introduction Recently,the increasing demand for advanced telecommunication systems has spurred extensive research into bandpass filters(BPFs),with particular emphasis on miniaturization,reduction of insertion loss(IL),and enhancement of upper stopband rejection(Huang et al.,2021;Snyder et al.,2021;Lin et al.,2023;Zeng et al.,2023).
