Set stabilization is one of the essential problems in engineering systems, and self-triggered control(STC) can save the storage space for interactive information, and can be successfully applied in networked control s...Set stabilization is one of the essential problems in engineering systems, and self-triggered control(STC) can save the storage space for interactive information, and can be successfully applied in networked control systems with limited communication resources. In this study, the set stabilization problem and STC design of Boolean control networks are investigated via the semi-tensor product technique. On the one hand, the largest control invariant subset is calculated in terms of the strongly connected components of the state transition graph, by which a graph-theoretical condition for set stabilization is derived. On the other hand, a characteristic function is exploited to determine the triggering mechanism and feasible controls. Based on this, the minimum-time and minimum-triggering open-loop, state-feedback and output-feedback STCs for set stabilization are designed,respectively. As classic applications of self-triggered set stabilization, self-triggered synchronization, self-triggered output tracking and self-triggered output regulation are discussed as well. Additionally, several practical examples are given to illustrate the effectiveness of theoretical results.展开更多
As industrialization and informatization becomemore deeply intertwined,industrial control networks have entered an era of intelligence.The connection between industrial control networks and the external internet is be...As industrialization and informatization becomemore deeply intertwined,industrial control networks have entered an era of intelligence.The connection between industrial control networks and the external internet is becoming increasingly close,which leads to frequent security accidents.This paper proposes a model for the industrial control network.It includes a malware containment strategy that integrates intrusion detection,quarantine,and monitoring.Basedonthismodel,the role of keynodes in the spreadofmalware is studied,a comparisonexperiment is conducted to validate the impact of the containment strategy.In addition,the dynamic behavior of the model is analyzed,the basic reproduction number is computed,and the disease-free and endemic equilibrium of the model is also obtained by the basic reproduction number.Moreover,through simulation experiments,the effectiveness of the containment strategy is validated,the influence of the relevant parameters is analyzed,and the containment strategy is optimized.In otherwords,selective immunity to key nodes can effectively suppress the spread ofmalware andmaintain the stability of industrial control systems.The earlier the immunization of key nodes,the better.Once the time exceeds the threshold,immunizing key nodes is almost ineffective.The analysis provides a better way to contain the malware in the industrial control network.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
In the construction and maintenance of particle accelerators,all the accelerator elements should be installed in the same coordinate system,only in this way could the devices in the actual world be consistent with the...In the construction and maintenance of particle accelerators,all the accelerator elements should be installed in the same coordinate system,only in this way could the devices in the actual world be consistent with the design drawings.However,with the occurrence of the movements of the reinforced concrete cover plates at short notice or building deformations in the long term,the control points upon the engineering structure will be displaced,and the fitness between the subnetwork and the global control network may be irresponsible.Therefore,it is necessary to evaluate the deformations of the 3D alignment control network.Different from the extant investigations,in this paper,to characterize the deformations of the control network,all of the congruent models between the points measured in different epochs have been identified,and the congruence model with the most control points is considered as the primary or fundamental model,the remaining models are recognized as the additional ones.Furthermore,the discrepancies between the primary S-transformation parameters and the additional S-transformation parameters can reflect the relative movements of the additional congruence models.Both the iterative GCT method and the iterative combinatorial theory are proposed to detect multiple congruence models in the control network.Considering the actual work of the alignment,it is essential to identify the competitive models in the monitoring network,which can provide us a hint that,even the fitness between the subnetwork and the global control network is good,there are still deformations which may be ignored.The numerical experiments show that the suggested approaches can describe the deformation of the 3D alignment control network roundly.展开更多
In the course of the cryoplant modernization, a control network will be set up in order to facilitate the control, the supervision, the centralized data acquisition and the alarm handling of the cryogenic system for H...In the course of the cryoplant modernization, a control network will be set up in order to facilitate the control, the supervision, the centralized data acquisition and the alarm handling of the cryogenic system for HT-7U tokamak. The paper introduces the preliminary design of control network based on the Controller Link Network for HT-7U tokamak cryogenic system. The multi-layer structure mentioned in the paper is the mainstream of automatic control. The control philosophy, the structure of the network and the components for control are also presented.展开更多
BACKGROUND The use of antidepressant therapy alone has a limited efficacy in patients with childhood trauma-associated major depressive disorder(MDD).However,the effectiveness of antidepressant treatment combined with...BACKGROUND The use of antidepressant therapy alone has a limited efficacy in patients with childhood trauma-associated major depressive disorder(MDD).However,the effectiveness of antidepressant treatment combined with psychodrama in these patients is unclear.AIM To evaluate the effectiveness of antidepressant treatment combined with psychodrama.METHODS Patients with childhood trauma-associated MDD treated with antidepressants were randomly assigned to either the psychodrama intervention(observation group)or the general health education intervention(control group)and received combination treatment for 6 mo.The observation group received general health education given by the investigator together with the“semi-structured group intervention model”of Yi Shu psychodrama.A total of 46 patients were recruited,including 29 cases in the observation group and 17 cases in the control group.Symptoms of depression and anxiety as well as coping style and resting-state functional magnetic resonance imaging were assessed before and after the intervention.RESULTS Symptoms of depression and anxiety,measured by the Hamilton Depression Scale,Beck Depression Inventory,and Beck Anxiety Inventory,were reduced after the intervention in both groups of patients.The coping style of the observation group improved significantly in contrast to the control group,which did not.In addition,an interaction between treatment and time in the right superior parietal gyrus node was found.Furthermore,functional connectivity between the right superior parietal gyrus and left inferior frontal gyrus in the observation group increased after the intervention,while in the control group the connectivity decreased.CONCLUSION This study supports the use of combined treatment with antidepressants and psychodrama to improve the coping style of patients with childhood trauma-associated MDD.Functional connectivity between the superior parietal gyrus and inferior frontal gyrus was increased after this combined treatment.We speculate that psychodrama enhances the internal connectivity of the cognitive control network and corrects the negative attention bias of patients with childhood trauma-associated MDD.Elucidating the neurobiological features of patients with childhood trauma-associated MDD is important for the development of methods that can assist in early diagnosis and intervention.展开更多
In this paper,we propose a intrusion detection algorithm based on auto-encoder and three-way decisions(AE-3WD)for industrial control networks,aiming at the security problem of industrial control network.The ideology o...In this paper,we propose a intrusion detection algorithm based on auto-encoder and three-way decisions(AE-3WD)for industrial control networks,aiming at the security problem of industrial control network.The ideology of deep learning is similar to the idea of intrusion detection.Deep learning is a kind of intelligent algorithm and has the ability of automatically learning.It uses self-learning to enhance the experience and dynamic classification capabilities.We use deep learning to improve the intrusion detection rate and reduce the false alarm rate through learning,a denoising AutoEncoder and three-way decisions intrusion detection method AE-3WD is proposed to improve intrusion detection accuracy.In the processing,deep learning AutoEncoder is used to extract the features of high-dimensional data by combining the coefficient penalty and reconstruction loss function of the encode layer during the training mode.A multi-feature space can be constructed by multiple feature extractions from AutoEncoder,and then a decision for intrusion behavior or normal behavior is made by three-way decisions.NSL-KDD data sets are used to the experiments.The experiment results prove that our proposed method can extract meaningful features and effectively improve the performance of intrusion detection.展开更多
We present the best bounds on the distance between 3-direction quartic box spline surface patch and its control net by means of analysis and computing for the basis functions of 3-direction quartic box spline surface....We present the best bounds on the distance between 3-direction quartic box spline surface patch and its control net by means of analysis and computing for the basis functions of 3-direction quartic box spline surface.Both the local bounds and the global bounds are given by the maximum norm of the first differences or second differences or mixed differences of the control points of the surface patch.展开更多
The problem of stabilizing multiple independent linear systems sharing one common network cable is presented and solved. Both the quantization and time sequencing are studied in the field of control over networks by p...The problem of stabilizing multiple independent linear systems sharing one common network cable is presented and solved. Both the quantization and time sequencing are studied in the field of control over networks by providing the formulated stabilizing sufficient condition which illustrates the relationship between the system instability, quantization and time sequencing,and the data rate is also presented in terms of the quantization and time sequencing. A numerical example is given to illustrate the result.展开更多
Aiming at the weaknesses of LON bus, combining the coexistence of fieldbus and DCS (Distribu ted Control Systems) in control networks, the authors introduce a hierarchical hybrid control network design based on LON an...Aiming at the weaknesses of LON bus, combining the coexistence of fieldbus and DCS (Distribu ted Control Systems) in control networks, the authors introduce a hierarchical hybrid control network design based on LON and master slave RS 422/485 protocol. This design adopts LON as the trunk, master slave RS 422/485 control networks are connected to LON as special subnets by dedicated gateways. It is an implementation method for isomerous control network integration. Data management is ranked according to real time requirements for different network data. The core components, such as control network nodes, router and gateway, are detailed in the paper. The design utilizes both communication advantage of LonWorks technology and the more powerful control ability of universal MCUs or PLCs, thus it greatly increases system response speed and performance cost ratio.展开更多
Objective of the study: This study aimed at characterizing output features of the higher-order motor control centers (hoMCCs), including secondary (premotor cortex [Pre] and supplementary motor area [SMA]) and associa...Objective of the study: This study aimed at characterizing output features of the higher-order motor control centers (hoMCCs), including secondary (premotor cortex [Pre] and supplementary motor area [SMA]) and association (prefrontal cortex [PFC]) motor regions to the primary motor cortex (M1) during graded force tasks. It is well known that one of the major roles of the primary motor cortex (M1) is controlling motor output such as muscle force. However, it is unclear how the hoMCCs interact with M1 in regulating voluntary muscle contractions. Methods: fMRI data was acquired during graded force tasks and fMRI-based effective connectivity (EC) and muscle force analyses were performed to study the relationship between hoMCCs-M1 effective connectivity and voluntarily exerted handgrip force. Results: The results show that there is a consistent information flow from the hoMCCs to M1 under all force conditions, suggesting a hierarchical control mechanism in the brain in regulating voluntary muscle force. Only the premotor cortex exhibited a significant role in mediating the level of force production through its EC with M1 but that role diminished when the exerted force was high, suggesting perhaps a ceiling and/or fatigue effect on the EC. A flip in the direction of EC from the primary sensory cortex (S1) to the hoMCCs (PFC, SMA, and Pre) at lower force levels while at higher forces EC was observed from the hoMCCs to S1. Conclusion: The hoMCCs regulate M1 output to produce desired voluntary muscle force. Only the Pre-to-M1 connectivity strength directly correlates with the force level especially from low to moderate levels. The hoMCCs are involved in modulating higher force production likely by strengthening M1 output and downgrad<span style="font-size:12px;line-height:102%;font-family:Verdana;">ing</span><span style="font-size:12px;line-height:102%;font-family:Verdana;"> inhibition from S1 to M1.</span>展开更多
There are a lot of equipments in HIRFL such as faraday cups, view screens power supplies, RF (radio frequency)equipment, vacuum equipment, and so on. A growing number of equipment support network interface in theseyea...There are a lot of equipments in HIRFL such as faraday cups, view screens power supplies, RF (radio frequency)equipment, vacuum equipment, and so on. A growing number of equipment support network interface in theseyears. Thus the control network system of HIRFL has become more and more big and complicated. So it is veryimportant to ensure that each device is online. We built a network monitoring platform. There are three functions.The first is monitoring the online or offline state of each switch. Second, the devices in the control network belongto different subsystem and are managed by subsystem managers. We cannot guarantee that each device is notdropped, but we can have a warning system which can warn device manager once the device dropped. Third, ifsome ports are abnormal, the information can be immediately reported to the administrator. Therefore, the controlnetwork monitoring platform has three subsystems, switch monitoring system, equipment offline warning systemand switch log analysis system, as shown in Fig. 1.展开更多
Boolean control network consists of a set of Boolean variables whose state is determined by other variables in the network. Boolean network is used for modeling complex system. In this paper, we have presented a model...Boolean control network consists of a set of Boolean variables whose state is determined by other variables in the network. Boolean network is used for modeling complex system. In this paper, we have presented a model of a context-aware system used in smart home based on Boolean control networks. This modeling describes the relationship between the context elements (person, time, location, and activity) and services (Morning Call, Sleeping, Guarding, Entertainment, and normal), which is effective to logical inference. We apply semi tensor matrix product to describe the dynamic of the system. This matrix form of expression is a convenient and reasonable way to design logic control system.展开更多
The Internet of Things(IoT)access controlmechanism may encounter security issues such as single point of failure and data tampering.To address these issues,a blockchain-based IoT reputation value attribute access cont...The Internet of Things(IoT)access controlmechanism may encounter security issues such as single point of failure and data tampering.To address these issues,a blockchain-based IoT reputation value attribute access control scheme is proposed.Firstly,writing the reputation value as an attribute into the access control policy,and then deploying the access control policy in the smart contract of the blockchain system can enable the system to provide more fine-grained access control;Secondly,storing a large amount of resources fromthe Internet of Things in Inter Planetary File System(IPFS)to improve system throughput;Finally,map resource access operations to qualification tokens to improve the performance of the access control system.Complete simulation experiments based on the Hyperledger Fabric platform.Fromthe simulation experimental results,it can be seen that the access control system can achieve more fine-grained and dynamic access control while maintaining high throughput and low time delay,providing sufficient reliability and security for access control of IoT devices.展开更多
This paper studies the problem of time-varying formation control with finite-time prescribed performance for nonstrict feedback second-order multi-agent systems with unmeasured states and unknown nonlinearities.To eli...This paper studies the problem of time-varying formation control with finite-time prescribed performance for nonstrict feedback second-order multi-agent systems with unmeasured states and unknown nonlinearities.To eliminate nonlinearities,neural networks are applied to approximate the inherent dynamics of the system.In addition,due to the limitations of the actual working conditions,each follower agent can only obtain the locally measurable partial state information of the leader agent.To address this problem,a neural network state observer based on the leader state information is designed.Then,a finite-time prescribed performance adaptive output feedback control strategy is proposed by restricting the sliding mode surface to a prescribed region,which ensures that the closed-loop system has practical finite-time stability and that formation errors of the multi-agent systems converge to the prescribed performance bound in finite time.Finally,a numerical simulation is provided to demonstrate the practicality and effectiveness of the developed algorithm.展开更多
基金supported by the National Natural Science Foundation of China (62273201,62173209,72134004,62303170)the Research Fund for the Taishan Scholar Project of Shandong Province of China (TSTP20221103)。
文摘Set stabilization is one of the essential problems in engineering systems, and self-triggered control(STC) can save the storage space for interactive information, and can be successfully applied in networked control systems with limited communication resources. In this study, the set stabilization problem and STC design of Boolean control networks are investigated via the semi-tensor product technique. On the one hand, the largest control invariant subset is calculated in terms of the strongly connected components of the state transition graph, by which a graph-theoretical condition for set stabilization is derived. On the other hand, a characteristic function is exploited to determine the triggering mechanism and feasible controls. Based on this, the minimum-time and minimum-triggering open-loop, state-feedback and output-feedback STCs for set stabilization are designed,respectively. As classic applications of self-triggered set stabilization, self-triggered synchronization, self-triggered output tracking and self-triggered output regulation are discussed as well. Additionally, several practical examples are given to illustrate the effectiveness of theoretical results.
基金Scientific Research Project of Liaoning Province Education Department,Code:LJKQZ20222457&LJKMZ20220781Liaoning Province Nature Fund Project,Code:No.2022-MS-291.
文摘As industrialization and informatization becomemore deeply intertwined,industrial control networks have entered an era of intelligence.The connection between industrial control networks and the external internet is becoming increasingly close,which leads to frequent security accidents.This paper proposes a model for the industrial control network.It includes a malware containment strategy that integrates intrusion detection,quarantine,and monitoring.Basedonthismodel,the role of keynodes in the spreadofmalware is studied,a comparisonexperiment is conducted to validate the impact of the containment strategy.In addition,the dynamic behavior of the model is analyzed,the basic reproduction number is computed,and the disease-free and endemic equilibrium of the model is also obtained by the basic reproduction number.Moreover,through simulation experiments,the effectiveness of the containment strategy is validated,the influence of the relevant parameters is analyzed,and the containment strategy is optimized.In otherwords,selective immunity to key nodes can effectively suppress the spread ofmalware andmaintain the stability of industrial control systems.The earlier the immunization of key nodes,the better.Once the time exceeds the threshold,immunizing key nodes is almost ineffective.The analysis provides a better way to contain the malware in the industrial control network.
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.
文摘In the construction and maintenance of particle accelerators,all the accelerator elements should be installed in the same coordinate system,only in this way could the devices in the actual world be consistent with the design drawings.However,with the occurrence of the movements of the reinforced concrete cover plates at short notice or building deformations in the long term,the control points upon the engineering structure will be displaced,and the fitness between the subnetwork and the global control network may be irresponsible.Therefore,it is necessary to evaluate the deformations of the 3D alignment control network.Different from the extant investigations,in this paper,to characterize the deformations of the control network,all of the congruent models between the points measured in different epochs have been identified,and the congruence model with the most control points is considered as the primary or fundamental model,the remaining models are recognized as the additional ones.Furthermore,the discrepancies between the primary S-transformation parameters and the additional S-transformation parameters can reflect the relative movements of the additional congruence models.Both the iterative GCT method and the iterative combinatorial theory are proposed to detect multiple congruence models in the control network.Considering the actual work of the alignment,it is essential to identify the competitive models in the monitoring network,which can provide us a hint that,even the fitness between the subnetwork and the global control network is good,there are still deformations which may be ignored.The numerical experiments show that the suggested approaches can describe the deformation of the 3D alignment control network roundly.
基金National 863-803 Project of China(No.2002AA834020)
文摘In the course of the cryoplant modernization, a control network will be set up in order to facilitate the control, the supervision, the centralized data acquisition and the alarm handling of the cryogenic system for HT-7U tokamak. The paper introduces the preliminary design of control network based on the Controller Link Network for HT-7U tokamak cryogenic system. The multi-layer structure mentioned in the paper is the mainstream of automatic control. The control philosophy, the structure of the network and the components for control are also presented.
文摘BACKGROUND The use of antidepressant therapy alone has a limited efficacy in patients with childhood trauma-associated major depressive disorder(MDD).However,the effectiveness of antidepressant treatment combined with psychodrama in these patients is unclear.AIM To evaluate the effectiveness of antidepressant treatment combined with psychodrama.METHODS Patients with childhood trauma-associated MDD treated with antidepressants were randomly assigned to either the psychodrama intervention(observation group)or the general health education intervention(control group)and received combination treatment for 6 mo.The observation group received general health education given by the investigator together with the“semi-structured group intervention model”of Yi Shu psychodrama.A total of 46 patients were recruited,including 29 cases in the observation group and 17 cases in the control group.Symptoms of depression and anxiety as well as coping style and resting-state functional magnetic resonance imaging were assessed before and after the intervention.RESULTS Symptoms of depression and anxiety,measured by the Hamilton Depression Scale,Beck Depression Inventory,and Beck Anxiety Inventory,were reduced after the intervention in both groups of patients.The coping style of the observation group improved significantly in contrast to the control group,which did not.In addition,an interaction between treatment and time in the right superior parietal gyrus node was found.Furthermore,functional connectivity between the right superior parietal gyrus and left inferior frontal gyrus in the observation group increased after the intervention,while in the control group the connectivity decreased.CONCLUSION This study supports the use of combined treatment with antidepressants and psychodrama to improve the coping style of patients with childhood trauma-associated MDD.Functional connectivity between the superior parietal gyrus and inferior frontal gyrus was increased after this combined treatment.We speculate that psychodrama enhances the internal connectivity of the cognitive control network and corrects the negative attention bias of patients with childhood trauma-associated MDD.Elucidating the neurobiological features of patients with childhood trauma-associated MDD is important for the development of methods that can assist in early diagnosis and intervention.
基金supported by National Nature Science Foundation of China (Grant No.61471182)Postgraduate Research&Practice Innovation Program of Jiangsu Province (Grant No.KYCX20_2993)Jiangsu postgraduate research innovation project (SJCX18_0784)。
文摘In this paper,we propose a intrusion detection algorithm based on auto-encoder and three-way decisions(AE-3WD)for industrial control networks,aiming at the security problem of industrial control network.The ideology of deep learning is similar to the idea of intrusion detection.Deep learning is a kind of intelligent algorithm and has the ability of automatically learning.It uses self-learning to enhance the experience and dynamic classification capabilities.We use deep learning to improve the intrusion detection rate and reduce the false alarm rate through learning,a denoising AutoEncoder and three-way decisions intrusion detection method AE-3WD is proposed to improve intrusion detection accuracy.In the processing,deep learning AutoEncoder is used to extract the features of high-dimensional data by combining the coefficient penalty and reconstruction loss function of the encode layer during the training mode.A multi-feature space can be constructed by multiple feature extractions from AutoEncoder,and then a decision for intrusion behavior or normal behavior is made by three-way decisions.NSL-KDD data sets are used to the experiments.The experiment results prove that our proposed method can extract meaningful features and effectively improve the performance of intrusion detection.
基金Supported by the National Natural Science Foundation of China (61170324 and 61100105)
文摘We present the best bounds on the distance between 3-direction quartic box spline surface patch and its control net by means of analysis and computing for the basis functions of 3-direction quartic box spline surface.Both the local bounds and the global bounds are given by the maximum norm of the first differences or second differences or mixed differences of the control points of the surface patch.
基金This work was financially supported by China Scholarship Council (21937016)
文摘The problem of stabilizing multiple independent linear systems sharing one common network cable is presented and solved. Both the quantization and time sequencing are studied in the field of control over networks by providing the formulated stabilizing sufficient condition which illustrates the relationship between the system instability, quantization and time sequencing,and the data rate is also presented in terms of the quantization and time sequencing. A numerical example is given to illustrate the result.
文摘Aiming at the weaknesses of LON bus, combining the coexistence of fieldbus and DCS (Distribu ted Control Systems) in control networks, the authors introduce a hierarchical hybrid control network design based on LON and master slave RS 422/485 protocol. This design adopts LON as the trunk, master slave RS 422/485 control networks are connected to LON as special subnets by dedicated gateways. It is an implementation method for isomerous control network integration. Data management is ranked according to real time requirements for different network data. The core components, such as control network nodes, router and gateway, are detailed in the paper. The design utilizes both communication advantage of LonWorks technology and the more powerful control ability of universal MCUs or PLCs, thus it greatly increases system response speed and performance cost ratio.
文摘Objective of the study: This study aimed at characterizing output features of the higher-order motor control centers (hoMCCs), including secondary (premotor cortex [Pre] and supplementary motor area [SMA]) and association (prefrontal cortex [PFC]) motor regions to the primary motor cortex (M1) during graded force tasks. It is well known that one of the major roles of the primary motor cortex (M1) is controlling motor output such as muscle force. However, it is unclear how the hoMCCs interact with M1 in regulating voluntary muscle contractions. Methods: fMRI data was acquired during graded force tasks and fMRI-based effective connectivity (EC) and muscle force analyses were performed to study the relationship between hoMCCs-M1 effective connectivity and voluntarily exerted handgrip force. Results: The results show that there is a consistent information flow from the hoMCCs to M1 under all force conditions, suggesting a hierarchical control mechanism in the brain in regulating voluntary muscle force. Only the premotor cortex exhibited a significant role in mediating the level of force production through its EC with M1 but that role diminished when the exerted force was high, suggesting perhaps a ceiling and/or fatigue effect on the EC. A flip in the direction of EC from the primary sensory cortex (S1) to the hoMCCs (PFC, SMA, and Pre) at lower force levels while at higher forces EC was observed from the hoMCCs to S1. Conclusion: The hoMCCs regulate M1 output to produce desired voluntary muscle force. Only the Pre-to-M1 connectivity strength directly correlates with the force level especially from low to moderate levels. The hoMCCs are involved in modulating higher force production likely by strengthening M1 output and downgrad<span style="font-size:12px;line-height:102%;font-family:Verdana;">ing</span><span style="font-size:12px;line-height:102%;font-family:Verdana;"> inhibition from S1 to M1.</span>
文摘There are a lot of equipments in HIRFL such as faraday cups, view screens power supplies, RF (radio frequency)equipment, vacuum equipment, and so on. A growing number of equipment support network interface in theseyears. Thus the control network system of HIRFL has become more and more big and complicated. So it is veryimportant to ensure that each device is online. We built a network monitoring platform. There are three functions.The first is monitoring the online or offline state of each switch. Second, the devices in the control network belongto different subsystem and are managed by subsystem managers. We cannot guarantee that each device is notdropped, but we can have a warning system which can warn device manager once the device dropped. Third, ifsome ports are abnormal, the information can be immediately reported to the administrator. Therefore, the controlnetwork monitoring platform has three subsystems, switch monitoring system, equipment offline warning systemand switch log analysis system, as shown in Fig. 1.
文摘Boolean control network consists of a set of Boolean variables whose state is determined by other variables in the network. Boolean network is used for modeling complex system. In this paper, we have presented a model of a context-aware system used in smart home based on Boolean control networks. This modeling describes the relationship between the context elements (person, time, location, and activity) and services (Morning Call, Sleeping, Guarding, Entertainment, and normal), which is effective to logical inference. We apply semi tensor matrix product to describe the dynamic of the system. This matrix form of expression is a convenient and reasonable way to design logic control system.
文摘The Internet of Things(IoT)access controlmechanism may encounter security issues such as single point of failure and data tampering.To address these issues,a blockchain-based IoT reputation value attribute access control scheme is proposed.Firstly,writing the reputation value as an attribute into the access control policy,and then deploying the access control policy in the smart contract of the blockchain system can enable the system to provide more fine-grained access control;Secondly,storing a large amount of resources fromthe Internet of Things in Inter Planetary File System(IPFS)to improve system throughput;Finally,map resource access operations to qualification tokens to improve the performance of the access control system.Complete simulation experiments based on the Hyperledger Fabric platform.Fromthe simulation experimental results,it can be seen that the access control system can achieve more fine-grained and dynamic access control while maintaining high throughput and low time delay,providing sufficient reliability and security for access control of IoT devices.
基金the National Natural Science Foundation of China(62203356)Fundamental Research Funds for the Central Universities of China(31020210502002)。
文摘This paper studies the problem of time-varying formation control with finite-time prescribed performance for nonstrict feedback second-order multi-agent systems with unmeasured states and unknown nonlinearities.To eliminate nonlinearities,neural networks are applied to approximate the inherent dynamics of the system.In addition,due to the limitations of the actual working conditions,each follower agent can only obtain the locally measurable partial state information of the leader agent.To address this problem,a neural network state observer based on the leader state information is designed.Then,a finite-time prescribed performance adaptive output feedback control strategy is proposed by restricting the sliding mode surface to a prescribed region,which ensures that the closed-loop system has practical finite-time stability and that formation errors of the multi-agent systems converge to the prescribed performance bound in finite time.Finally,a numerical simulation is provided to demonstrate the practicality and effectiveness of the developed algorithm.