Target Controllability of Multi-Layer Networks With High-Dimensional Nodes

This paper studies the target controllability of multilayer complex networked systems,in which the nodes are highdimensional linear time invariant(LTI)dynamical systems,and the network topology is directed and weighted.The influence of inter-layer couplings on the target controllability of multi-layer networks is discussed.It is found that even if there exists a layer which is not target controllable,the entire multi-layer network can still be target controllable due to the inter-layer couplings.For the multi-layer networks with general structure,a necessary and sufficient condition for target controllability is given by establishing the relationship between uncontrollable subspace and output matrix.By the derived condition,it can be found that the system may be target controllable even if it is not state controllable.On this basis,two corollaries are derived,which clarify the relationship between target controllability,state controllability and output controllability.For the multi-layer networks where the inter-layer couplings are directed chains and directed stars,sufficient conditions for target controllability of networked systems are given,respectively.These conditions are easier to verify than the classic criterion.

The Effect of Key Nodes on theMalware Dynamics in the Industrial Control Network

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.

Combinatorial reasoning-based abnormal sensor recognition method for subsea production control system

The subsea production system is a vital equipment for offshore oil and gas production.The control system is one of the most important parts of it.Collecting and processing the signals of subsea sensors is the only way to judge whether the subsea production control system is normal.However,subsea sensors degrade rapidly due to harsh working environments and long service time.This leads to frequent false alarm incidents.A combinatorial reasoning-based abnormal sensor recognition method for subsea production control system is proposed.A combinatorial algorithm is proposed to group sensors.The long short-term memory network(LSTM)is used to establish a single inference model.A counting-based judging method is proposed to identify abnormal sensors.Field data from an offshore platform in the South China Sea is used to demonstrate the effect of the proposed method.The results show that the proposed method can identify the abnormal sensors effectively.

Observer-based dynamic event-triggered control for distributed parameter systems over mobile sensor-plus-actuator networks

We develop a policy of observer-based dynamic event-triggered state feedback control for distributed parameter systems over a mobile sensor-plus-actuator network.It is assumed that the mobile sensing devices that provide spatially averaged state measurements can be used to improve state estimation in the network.For the purpose of decreasing the update frequency of controller and unnecessary sampled data transmission, an efficient dynamic event-triggered control policy is constructed.In an event-triggered system, when an error signal exceeds a specified time-varying threshold, it indicates the occurrence of a typical event.The global asymptotic stability of the event-triggered closed-loop system and the boundedness of the minimum inter-event time can be guaranteed.Based on the linear quadratic optimal regulator, the actuator selects the optimal displacement only when an event occurs.A simulation example is finally used to verify that the effectiveness of such a control strategy can enhance the system performance.

Mechanoluminescent-Triboelectric Bimodal Sensors for Self-Powered Sensing and Intelligent Control

Self-powered flexible devices with skin-like multiple sensing ability have attracted great attentions due to their broad applications in the Internet of Things(IoT).Various methods have been proposed to enhance mechano-optic or electric performance of the flexible devices;however,it remains challenging to realize the display and accurate recognition of motion trajectories for intelligent control.Here,we present a fully self-powered mechanoluminescent-triboelectric bimodal sensor based on micronanostructured mechanoluminescent elastomer,which can patterned-display the force trajectories.The deformable liquid metals used as stretchable electrode make the stress transfer stable through overall device to achieve outstanding mechanoluminescence(with a gray value of 107 under a stimulus force as low as 0.3 N and more than 2000 cycles reproducibility).Moreover,a microstructured surface is constructed which endows the resulted composite with significantly improved triboelectric performances(voltage increases from 8 to 24 V).Based on the excellent bimodal sensing performances and durability of the obtained composite,a highly reliable intelligent control system by machine learning has been developed for controlling trolley,providing an approach for advanced visual interaction devices and smart wearable electronics in the future IoT era.

High Efficient Reconfigurable and Self Testable Architecture for Sensor Node

Sensor networks are regularly sent to monitor certain physical properties that run in length from divisions of a second to many months or indeed several years.Nodes must advance their energy use for expanding network lifetime.The fault detection of the network node is very significant for guaranteeing the correctness of monitoring results.Due to different network resource constraints and malicious attacks,security assurance in wireless sensor networks has been a difficult task.The implementation of these features requires larger space due to distributed module.This research work proposes new sensor node architecture integrated with a self-testing core and cryptoprocessor to provide fault-free operation and secured data transmission.The proposed node architecture was designed using Verilog programming and implemented using the Xilinx ISE tool in the Spartan 3E environment.The proposed system supports the real-time application in the range of 33 nanoseconds.The obtained results have been compared with the existing Microcontroller-based system.The power consumption of the proposed system consumes only 3.9 mW,and it is only 24%percentage of AT mega-based node architecture.

An Efficient IIoT-Based Smart Sensor Node for Predictive Maintenance of Induction Motors

Predictive maintenance is a vital aspect of the industrial sector,and the use of Industrial Internet of Things(IIoT)sensor nodes is becoming increasingly popular for detecting motor faults and monitoring motor conditions.An integrated approach for acquiring,processing,and wirelessly transmitting a large amount of data in predictive maintenance applications remains a significant challenge.This study presents an IIoT-based sensor node for industrial motors.The sensor node is designed to acquire vibration data on the radial and axial axes of the motor and utilizes a hybrid approach for efficient data processing via edge and cloud platforms.The initial step of signal processing is performed on the node at the edge,reducing the burden on a centralized cloud for processing data from multiple sensors.The proposed architecture utilizes the lightweight Message Queue Telemetry Transport(MQTT)communication protocol for seamless data transmission from the node to the local and main brokers.The broker’s bridging allows for data backup in case of connection loss.The proposed sensor node is rigorously tested on a motor testbed in a laboratory setup and an industrial setting in a rice industry for validation,ensuring its performance and accuracy in real-world industrial environments.The data analysis and results from both testbed and industrial motors were discussed using vibration analysis for identifying faults.The proposed sensor node is a significant step towards improving the efficiency and reliability of industrial motors through realtime monitoring and early fault detection,ultimately leading to minimized unscheduled downtime and cost savings.

A Reputation-Based AODV Protocol for Blackhole and Malfunction Nodes Detection and Avoidance

Enhancing the security of Wireless Sensor Networks(WSNs)improves the usability of their applications.Therefore,finding solutions to various attacks,such as the blackhole attack,is crucial for the success of WSN applications.This paper proposes an enhanced version of the AODV(Ad Hoc On-Demand Distance Vector)protocol capable of detecting blackholes and malfunctioning benign nodes in WSNs,thereby avoiding them when delivering packets.The proposed version employs a network-based reputation system to select the best and most secure path to a destination.To achieve this goal,the proposed version utilizes the Watchdogs/Pathrater mechanisms in AODV to gather and broadcast reputations to all network nodes to build the network-based reputation system.To minimize the network overhead of the proposed approach,the paper uses reputation aggregator nodes only for forwarding reputation tables.Moreover,to reduce the overhead of updating reputation tables,the paper proposes three mechanisms,which are the prompt broadcast,the regular broadcast,and the light broadcast approaches.The proposed enhanced version has been designed to perform effectively in dynamic environments such as mobile WSNs where nodes,including blackholes,move continuously,which is considered a challenge for other protocols.Using the proposed enhanced protocol,a node evaluates the security of different routes to a destination and can select the most secure routing path.The paper provides an algorithm that explains the proposed protocol in detail and demonstrates a case study that shows the operations of calculating and updating reputation values when nodes move across different zones.Furthermore,the paper discusses the proposed approach’s overhead analysis to prove the proposed enhancement’s correctness and applicability.

基于NodeMCU的智能浇灌系统设计

当前,智能化技术不断发展,为了提升现代农田的智能化管理水平,设计以NodeMCU(节点微控制单元)作为中央控制器的智能浇灌系统,实现农田灌溉智能化。YL-69土壤湿度传感器用于检测土壤含水量,DHT11温湿度传感器用于检测环境温度和湿度,中央控制器负责数据的采集与处理,通过内置的ESP8266芯片连接Wi-Fi将数据无线传输至网页端进行实时监测与控制,并对比系统设置的阈值指标,反馈至微控制器,微控制器通过控制继电器打开水泵对土地浇灌,并且搭建数据库进行数据记录与分析。该系统结构简单,可靠性较高,可实现浇灌的无人化管理,具有重要的现实意义。

A blockchain-empowered authentication scheme for worm detection in wireless sensor network

Wireless Sensor Network(WSN)is a distributed sensor network composed a large number of nodes with low cost,low performance and self-management.The special structure of WSN brings both convenience and vulnerability.For example,a malicious participant can launch attacks by capturing a physical device.Therefore,node authentication that can resist malicious attacks is very important to network security.Recently,blockchain technology has shown the potential to enhance the security of the Internet of Things(IoT).In this paper,we propose a Blockchain-empowered Authentication Scheme(BAS)for WSN.In our scheme,all nodes are managed by utilizing the identity information stored on the blockchain.Besides,the simulation experiment about worm detection is executed on BAS,and the security is evaluated from detection and infection rate.The experiment results indicate that the proposed scheme can effectively inhibit the spread and infection of worms in the network.

A palm-like 3D tactile sensor based on liquid-metal triboelectric nanogenerator for underwater robot gripper

The highly sensitive and power efficient tactile sensors can provide grippers with vertical and shear forces from interactions with objects. In an ocean environment with low visual distance and high noise, sea otters can rely on their palms to accurately identify and grasp target objects without damage. Inspired by the structure of the sea otter’s palm, this paper proposes a distributed liquid metal-based three-dimensional biomimetic underwater triboelectric palm-like tactile sensor (UPTS) for feedback-controlled grippers. The device is mainly composed of a flexible shell, a flexible cover, a flexible support, a triboelectric sensing unit and a fixed shell. The force acting on the flexible cover causes the flexible cover and sensing unit to deform, so that the sensing unit undergoes a contact-separation process, thereby generating an electrical signal. UPTS has the capability to identify the magnitude and direction of force, with a direction recognition error angle within 5 degrees. Additionally, it can distinguish the hardness and shape of objects, achieving an accuracy rate of 100% and 99.75% respectively for the tested objects. The results indicate that UPTS can provide force feedback for underwater grippers, thereby assisting the grippers in better completing salvage task.

An Optimal Node Localization in WSN Based on Siege Whale Optimization Algorithm

Localization or positioning scheme in Wireless sensor networks (WSNs) is one of the most challenging andfundamental operations in various monitoring or tracking applications because the network deploys a large areaand allocates the acquired location information to unknown devices. The metaheuristic approach is one of themost advantageous ways to deal with this challenging issue and overcome the disadvantages of the traditionalmethods that often suffer from computational time problems and small network deployment scale. This studyproposes an enhanced whale optimization algorithm that is an advanced metaheuristic algorithm based on thesiege mechanism (SWOA) for node localization inWSN. The objective function is modeled while communicatingon localized nodes, considering variables like delay, path loss, energy, and received signal strength. The localizationapproach also assigns the discovered location data to unidentified devices with the modeled objective functionby applying the SWOA algorithm. The experimental analysis is carried out to demonstrate the efficiency of thedesigned localization scheme in terms of various metrics, e.g., localization errors rate, converges rate, and executedtime. Compared experimental-result shows that theSWOA offers the applicability of the developed model forWSNto perform the localization scheme with excellent quality. Significantly, the error and convergence values achievedby the SWOA are less location error, faster in convergence and executed time than the others compared to at least areduced 1.5% to 4.7% error rate, and quicker by at least 4%and 2% in convergence and executed time, respectivelyfor the experimental scenarios.

Mechanism analysis of regulating Turing instability and Hopf bifurcation of malware propagation in mobile wireless sensor networks

A dynamical model is constructed to depict the spatial-temporal evolution of malware in mobile wireless sensor networks(MWSNs). Based on such a model, we design a hybrid control scheme combining parameter perturbation and state feedback to effectively manipulate the spatiotemporal dynamics of malware propagation. The hybrid control can not only suppress the Turing instability caused by diffusion factor but can also adjust the occurrence of Hopf bifurcation induced by time delay. Numerical simulation results show that the hybrid control strategy can efficiently manipulate the transmission dynamics to achieve our expected desired properties, thus reducing the harm of malware propagation to MWSNs.

Review on uncertainty analysis and information fusion diagnosis of aircraft control system

In the aircraft control system,sensor networks are used to sample the attitude and environmental data.As a result of the external and internal factors(e.g.,environmental and task complexity,inaccurate sensing and complex structure),the aircraft control system contains several uncertainties,such as imprecision,incompleteness,redundancy and randomness.The information fusion technology is usually used to solve the uncertainty issue,thus improving the sampled data reliability,which can further effectively increase the performance of the fault diagnosis decision-making in the aircraft control system.In this work,we first analyze the uncertainties in the aircraft control system,and also compare different uncertainty quantitative methods.Since the information fusion can eliminate the effects of the uncertainties,it is widely used in the fault diagnosis.Thus,this paper summarizes the recent work in this aera.Furthermore,we analyze the application of information fusion methods in the fault diagnosis of the aircraft control system.Finally,this work identifies existing problems in the use of information fusion for diagnosis and outlines future trends.

Hybrid Multi-Infeed Interaction Factor Calculation Method Considering Voltage Regulation Control Characteristics of Voltage Source Converter

Voltage source converter based high voltage direct current(VSC-HVDC)can participate in voltage regulation by flexible control to help maintain the voltage stability of the power grid.In order to quantitatively evaluate its influence on the voltage interaction between VSC-HVDC and line commutated converter based high voltage direct current(LCC-HVDC),this paper proposes a hybrid multi-infeed interaction factor(HMIIF)calculation method considering the voltage regulation control characteristics of VSC-HVDC.Firstly,for a hybrid multi-infeed high voltage direct current system,an additional equivalent operating admittance matrix is constructed to characterize HVDC equipment characteristics under small disturbance.Secondly,based on the characteristic curve between the reactive power and the voltage of a certain VSC-HVDC project,the additional equivalent operating admittance of VSC-HVDC is derived.The additional equivalent operating admittance matrix calculation method is proposed.Thirdly,the equivalent bus impedance matrix is obtained by modifying the alternating current(AC)system admittance matrix with the additional equivalent operating admittance matrix.On this basis,the HMIIF calculation method based on the equivalent bus impedance ratio is proposed.Finally,the effectiveness of the proposed method is verified in a hybrid dual-infeed high voltage direct current system constructed in Power Systems Computer Aided Design(PSCAD),and the influence of voltage regulation control on HMIIF is analyzed.

A Novel Design of Fuzzy PID Controllers for Dual-Sensor Cardiac Pacemaker Systems

This work proposes to design a fuzzy proportional-integral derivative (FPID) controller for dual-sensor cardiac pacemaker systems, which can automatically control the heart rate to accurately track a desired preset profile. The combination of fuzzy logic and conventional PID control approaches is adopted for the controller design based on dual-sensors. This controller offers good adaptation of the heart rate to the physiological needs of the patient under different states (rest and walk). Through comparing with the conventional fuzzy control algorithm, FPID provides a more suitable control strategy to determine a pacing rate in order to achieve a closer match between actual heart rate and a desired profile. To assist the heartbeat recovery, the stimuli with adjustable pacing rate is generated by the pacemaker according to the FPID controller, such actual heart rate may track the preset heart rate faithfully. Simulation results confirm that this proposed control design is effective for heartbeat recovery and maintenance. This study will be helpful not only for the analysis and treatment of bradycardias but also for improving the performance of medical devices.

基于Node-red的云端智能生产线控制系统设计与实现

针对传统生产线在刚性生产过程中面临的成本过高、远程实施难、兼容性低等关键问题,基于目前中小企业的技术基础相对薄弱,无法将云计算平台、数据存储和处理等设备及技术运用到实际生产中的现状,本文利用西门子S7-1200 PLC作为核心控制器,基于Node-red平台设计了成本低、兼容性高的云端智能生产线监控系统,便于实现对于生产线的监视和控制,提高生产效率与产品质量。现场运行表明,该系统运行稳定,满足智能生产线的设计要求,同时具备部署成本低、兼容性高的突出优势。

Attractor-Based Simultaneous Design of the Minimum Set of Control Nodes and Controllers in Boolean Networks

Design of control strategies for gene regulatory networks is a challenging and important topic in systems biology. In this paper, the problem of finding both a minimum set of control nodes (control inputs) and a controller is studied. A control node corresponds to a gene that expression can be controlled. Here, a Boolean network is used as a model of gene regulatory networks, and control specifications on attractors, which represent cell types or states of cells, are imposed. It is important to design a gene regulatory network that has desired attractors and has no undesired attractors. Using a matrix-based representation of BNs, this problem can be rewritten as an integer linear programming problem. Finally, the proposed method is demonstrated by a numerical example on a WNT5A network, which is related to melanoma.

Enhancing Patients Outcomes and Infection Control through Smart Indoor Air Quality Monitoring Systems

Air pollution poses a critical threat to public health and environmental sustainability globally, and Nigeria is no exception. Despite significant economic growth and urban development, Nigeria faces substantial air quality challenges, particularly in urban centers. While outdoor air pollution has received considerable attention, the issue of indoor air quality remains underexplored yet equally critical. This study aims to develop a reliable, cost-effective, and user-friendly solution for continuous monitoring and reporting of indoor air quality, accessible from anywhere via a web interface. Addressing the urgent need for effective indoor air quality monitoring in urban hospitals, the research focuses on designing and implementing a smart indoor air quality monitoring system using Arduino technology. Employing an Arduino Uno, ESP8266 Wi-Fi module, and MQ135 gas sensor, the system collects real-time air quality data, transmits it to the ThingSpeak cloud platform, and visualizes it through a user-friendly web interface. This project offers a cost-effective, portable, and reliable solution for monitoring indoor air quality, aiming to mitigate health risks and promote a healthier living environment.

Fuzzy Controller for Dual Sensors Cardiac Pacemaker System in Patients with Bradycardias at Rest

Cardiovascular disease is defined as a heart rate that is less than 60 bpm. Implantable cardiac devices such as pacemakers are widely used nowadays. In this paper, design and implementation of the heart model can be controlled to be the heart of a patient suffering from a decrease in heart rate (Bradycardia). A system is designed to sense and calculate the heart rate per minute and it is considered as an input to the controller. The design and implementation of Mamdani fuzzy controller to generate electric pulses that mimic the natural pacing system of the heart maintains an adequate heart rate by delivering controlled, rhythmic electrical stimuli to the chambers of the patient heart. The proposed controller is tested by using Matlab/Simulink program.