This paper addresses the control design for automatic train operation of high-speed trains with protection constraints.A new resilient nonlinear gain-based feedback control approach is proposed,which is capable of gua...This paper addresses the control design for automatic train operation of high-speed trains with protection constraints.A new resilient nonlinear gain-based feedback control approach is proposed,which is capable of guaranteeing,under some proper non-restrictive initial conditions,the protection constraints control raised by the distance-to-go(moving authority)curve and automatic train protection in practice.A new hyperbolic tangent function-based model is presented to mimic the whole operation process of high-speed trains.The proposed feedback control methods are easily implementable and computationally inexpensive because the presence of only two feedback gains guarantee satisfactory tracking performance and closed-loop stability,no adaptations of unknown parameters,function approximation of unknown nonlinearities,and attenuation of external disturbances in the proposed control strategies.Finally,rigorous proofs and comparative simulation results are given to demonstrate the effectiveness of the proposed approaches.展开更多
Neutron Flux Monitor, a key diagnostic system in International Thermonuclear Experimental Reactor, may provide for reading a series of important parameters in fusion reaction process. We designed an important part of ...Neutron Flux Monitor, a key diagnostic system in International Thermonuclear Experimental Reactor, may provide for reading a series of important parameters in fusion reaction process. We designed an important part of its main electronic system - Automatic Gain Adjustment Campbell Integrator (AGACI), expanding the detecting neutron counting rate of 104-108 cps (counts per second). The total gain of AGACI in five files is divided into 1, 10, 100, 1000, and 10 000 times, and can be automatically adjusted. The linear correlation coefficient (R) is more than 0.9999 in AGACI working range.展开更多
This paper presented an automatic gain control （AGC） circuit suitable for FM/cw ladar. The proposed architecture was based on two-stage variable gain amplifier （VGA） chain with a novel DC offset canceller circuit,...This paper presented an automatic gain control （AGC） circuit suitable for FM/cw ladar. The proposed architecture was based on two-stage variable gain amplifier （VGA） chain with a novel DC offset canceller circuit, which contained an improved Gilbert cell and a Gm-C feedback loop. To keep the VGA with a linearity in dB characteristic, an improved exponential gain control circuit was introduced. The AGC was implemented in 0.18 gm standard CMOS process. Simulation and measurement results verified that its gain ranged from -20 dB to 30 dB, and band- width ranged from 100 kHz to 10 MHz. Its power consumption was 19.8 mW under a voltage supply of 3.3 V.展开更多
A novel wide-range CMOS variable gain amplifier （VGA） topology is presented. The proposed VGA is composed of a variable transconductor and a novel variable output resistor and can offer a high gain variation range o...A novel wide-range CMOS variable gain amplifier （VGA） topology is presented. The proposed VGA is composed of a variable transconductor and a novel variable output resistor and can offer a high gain variation range of 80dB while using a single variable-gain stage. Temperature-compensation and decibel-linear gain characteristic are achieved by using a control circuit that provides a gain error lower than ±1.5dB over the full temperature and gain ranges. Realized in 0.25μm CMOS technology, a prototype of the proposed VGA provides a total gain range of 64.5dB with 55.6dB-linear range,a P-1dB varying from - 17.5 to 11.5dBm,and a 3dB-bandwith varying from 65 to 860MHz while dissipating 16.5mW from a 2.5V supply voltage.展开更多
Co-seismic landslide detection is essential for post-disaster rescue and risk assessment after an earthquake event.However,a variety of ground objects,including roads and bare land,have spectral characteristics simila...Co-seismic landslide detection is essential for post-disaster rescue and risk assessment after an earthquake event.However,a variety of ground objects,including roads and bare land,have spectral characteristics similar to those of co-seismic landslides,making it difficult to gather information and assess their impact rapidly and accurately.Therefore,an automatic detection method based on a deep learning model,named ENVINet5,with multiple features(ENVINet5_MF)was proposed to solve this problem and improve the detection accuracy of co-seismic landslides.The ENVINet5_MF method is advantageous for co-seismic landslide detection because it features a landslide gain index(LGI)that effectively eliminates the spectral interference of bare land and roads.We conducted two experiments using multi-temporal PlanetScope images acquired in Hokkaido,Japan,and Mainling,China.The accuracy evaluation and rationality analysis show that ENVINet5_MF performed better than comparative methods and that the co-seismic landslide areas detected by ENVINet5_MF were the most consistent with ground reference data.The findings of this study suggest that ENVINet5_MF can provide an efficient and accurate method for coseismic landslide detection to ensure a rapid response to co-seismic landslide disasters.展开更多
In order to enhance the accuracy of Air Traffic Control(ATC)cybersecurity attack detection,in this paper,a new clustering detection method is designed for air traffic control network security attacks.The feature set f...In order to enhance the accuracy of Air Traffic Control(ATC)cybersecurity attack detection,in this paper,a new clustering detection method is designed for air traffic control network security attacks.The feature set for ATC cybersecurity attacks is constructed by setting the feature states,adding recursive features,and determining the feature criticality.The expected information gain and entropy of the feature data are computed to determine the information gain of the feature data and reduce the interference of similar feature data.An autoencoder is introduced into the AI(artificial intelligence)algorithm to encode and decode the characteristics of ATC network security attack behavior to reduce the dimensionality of the ATC network security attack behavior data.Based on the above processing,an unsupervised learning algorithm for clustering detection of ATC network security attacks is designed.First,determine the distance between the clustering clusters of ATC network security attack behavior characteristics,calculate the clustering threshold,and construct the initial clustering center.Then,the new average value of all feature objects in each cluster is recalculated as the new cluster center.Second,it traverses all objects in a cluster of ATC network security attack behavior feature data.Finally,the cluster detection of ATC network security attack behavior is completed by the computation of objective functions.The experiment took three groups of experimental attack behavior data sets as the test object,and took the detection rate,false detection rate and recall rate as the test indicators,and selected three similar methods for comparative test.The experimental results show that the detection rate of this method is about 98%,the false positive rate is below 1%,and the recall rate is above 97%.Research shows that this method can improve the detection performance of security attacks in air traffic control network.展开更多
基金supported jointly by the National Natural Science Foundation of China(61703033,61790573)Beijing Natural Science Foundation(4192046)+1 种基金Fundamental Research Funds for Central Universities(2018JBZ002)State Key Laboratory of Rail Traffic Control and Safety(RCS2018ZT013),Beijing Jiaotong University
文摘This paper addresses the control design for automatic train operation of high-speed trains with protection constraints.A new resilient nonlinear gain-based feedback control approach is proposed,which is capable of guaranteeing,under some proper non-restrictive initial conditions,the protection constraints control raised by the distance-to-go(moving authority)curve and automatic train protection in practice.A new hyperbolic tangent function-based model is presented to mimic the whole operation process of high-speed trains.The proposed feedback control methods are easily implementable and computationally inexpensive because the presence of only two feedback gains guarantee satisfactory tracking performance and closed-loop stability,no adaptations of unknown parameters,function approximation of unknown nonlinearities,and attenuation of external disturbances in the proposed control strategies.Finally,rigorous proofs and comparative simulation results are given to demonstrate the effectiveness of the proposed approaches.
基金Supported by the ITER Plan National Major Project (2008GB109000)
文摘Neutron Flux Monitor, a key diagnostic system in International Thermonuclear Experimental Reactor, may provide for reading a series of important parameters in fusion reaction process. We designed an important part of its main electronic system - Automatic Gain Adjustment Campbell Integrator (AGACI), expanding the detecting neutron counting rate of 104-108 cps (counts per second). The total gain of AGACI in five files is divided into 1, 10, 100, 1000, and 10 000 times, and can be automatically adjusted. The linear correlation coefficient (R) is more than 0.9999 in AGACI working range.
基金Supported by the National Science and Technology Major Project of the Ministry of Science and Technology of China(No.2012ZX03004008)
文摘This paper presented an automatic gain control （AGC） circuit suitable for FM/cw ladar. The proposed architecture was based on two-stage variable gain amplifier （VGA） chain with a novel DC offset canceller circuit, which contained an improved Gilbert cell and a Gm-C feedback loop. To keep the VGA with a linearity in dB characteristic, an improved exponential gain control circuit was introduced. The AGC was implemented in 0.18 gm standard CMOS process. Simulation and measurement results verified that its gain ranged from -20 dB to 30 dB, and band- width ranged from 100 kHz to 10 MHz. Its power consumption was 19.8 mW under a voltage supply of 3.3 V.
文摘A novel wide-range CMOS variable gain amplifier （VGA） topology is presented. The proposed VGA is composed of a variable transconductor and a novel variable output resistor and can offer a high gain variation range of 80dB while using a single variable-gain stage. Temperature-compensation and decibel-linear gain characteristic are achieved by using a control circuit that provides a gain error lower than ±1.5dB over the full temperature and gain ranges. Realized in 0.25μm CMOS technology, a prototype of the proposed VGA provides a total gain range of 64.5dB with 55.6dB-linear range,a P-1dB varying from - 17.5 to 11.5dBm,and a 3dB-bandwith varying from 65 to 860MHz while dissipating 16.5mW from a 2.5V supply voltage.
基金supported by the National Natural Science Foundation of China(Grant No.42271078)the Key Research and Development Program of Shaanxi(Grant No.2024SF-YBXM669)the Second Tibetan Plateau Scientific Expedition and Research Program(STEP)(Grant No.2019QZKK0902)。
文摘Co-seismic landslide detection is essential for post-disaster rescue and risk assessment after an earthquake event.However,a variety of ground objects,including roads and bare land,have spectral characteristics similar to those of co-seismic landslides,making it difficult to gather information and assess their impact rapidly and accurately.Therefore,an automatic detection method based on a deep learning model,named ENVINet5,with multiple features(ENVINet5_MF)was proposed to solve this problem and improve the detection accuracy of co-seismic landslides.The ENVINet5_MF method is advantageous for co-seismic landslide detection because it features a landslide gain index(LGI)that effectively eliminates the spectral interference of bare land and roads.We conducted two experiments using multi-temporal PlanetScope images acquired in Hokkaido,Japan,and Mainling,China.The accuracy evaluation and rationality analysis show that ENVINet5_MF performed better than comparative methods and that the co-seismic landslide areas detected by ENVINet5_MF were the most consistent with ground reference data.The findings of this study suggest that ENVINet5_MF can provide an efficient and accurate method for coseismic landslide detection to ensure a rapid response to co-seismic landslide disasters.
基金National Natural Science Foundation of China(U2133208,U20A20161)National Natural Science Foundation of China(No.62273244)Sichuan Science and Technology Program(No.2022YFG0180).
文摘In order to enhance the accuracy of Air Traffic Control(ATC)cybersecurity attack detection,in this paper,a new clustering detection method is designed for air traffic control network security attacks.The feature set for ATC cybersecurity attacks is constructed by setting the feature states,adding recursive features,and determining the feature criticality.The expected information gain and entropy of the feature data are computed to determine the information gain of the feature data and reduce the interference of similar feature data.An autoencoder is introduced into the AI(artificial intelligence)algorithm to encode and decode the characteristics of ATC network security attack behavior to reduce the dimensionality of the ATC network security attack behavior data.Based on the above processing,an unsupervised learning algorithm for clustering detection of ATC network security attacks is designed.First,determine the distance between the clustering clusters of ATC network security attack behavior characteristics,calculate the clustering threshold,and construct the initial clustering center.Then,the new average value of all feature objects in each cluster is recalculated as the new cluster center.Second,it traverses all objects in a cluster of ATC network security attack behavior feature data.Finally,the cluster detection of ATC network security attack behavior is completed by the computation of objective functions.The experiment took three groups of experimental attack behavior data sets as the test object,and took the detection rate,false detection rate and recall rate as the test indicators,and selected three similar methods for comparative test.The experimental results show that the detection rate of this method is about 98%,the false positive rate is below 1%,and the recall rate is above 97%.Research shows that this method can improve the detection performance of security attacks in air traffic control network.
