Frequency Of Data Transmission Research Articles

Measurement Method of Stress in High-Voltage Cable Accessories Based on Ultrasonic Longitudinal Wave Attenuation.

High-voltage cables are the main arteries of urban power supply. Cable accessories are connecting components between different sections of cables or between cables and other electrical equipment. The stress in the cold shrink tube of cable accessories is a key parameter to ensure the stable operation of the power system. This paper attempts to explore a method for measuring the stress in the cold shrink tube of high-voltage cable accessories based on ultrasonic longitudinal wave attenuation. Firstly, a pulse ultrasonic longitudinal wave testing system based on FPGA is designed, where the ultrasonic sensor operates in a single-transmit, single-receive mode with a frequency of 3 MHz, a repetition frequency of 50 Hz, and a data acquisition and transmission frequency of 40 MHz. Then, through experiments and theoretical calculations, the transmission and attenuation characteristics of ultrasonic longitudinal waves in multi-layer elastic media are studied, revealing an exponential relationship between ultrasonic wave attenuation and the thickness of the cold shrink tube. Finally, by establishing a theoretical model of the radial stress of the cold shrink tube, using the thickness of the cold shrink tube as an intermediate variable, an effective measurement of the stress of the cold shrink tube was achieved.

Implementation of Data Parsing on Arduino Mega and NodeMCU ESP8266 for Web-Based Monitoring of E-Bike Charging Station

The rising trend of electric bicycles in Indonesia necessitates an efficient monitoring system for electric bicycle charging stations to ensure optimal performance and timely decision-making. This study focuses on developing and testing a web-based monitoring system utilizing Arduino Mega and NodeMCU ESP8266 for real-time data transmission and analysis. The system integrates multiple sensors, including ACS712 current sensors, DC voltage sensors, and PZEM004T sensors, to monitor key parameters such as current, voltage, power, and energy. Data parsing, a crucial process for efficient transmission, is performed on the Arduino Mega before being sent to the NodeMCU ESP8266, which then forwards the data to a web server. The research employs the Research and Development (R&D) method, encompassing stages of information gathering, system planning, implementation, and evaluation. Testing revealed that data parsing failures were due to data loss and format corruption caused by serial communication issues. Various transmission delays (0 ms, 100 ms, 200 ms, and 500 ms) were tested to evaluate their impact on data loss, communication latency, and system responsiveness. The results indicate that a 200 ms delay offers an optimal balance between data transmission frequency and system stability, with minimal data loss and stable latency. The study also explored the effects of data reception delays on the web server, highlighting that lower transmission frequencies result in more stable reception delays and better overall performance. Efficient network resource usage and system responsiveness were achieved with appropriate delay configurations.

Long Range (LoRa) and Alert Network System for Forest Fire Prediction

Forest fires are a regular occurrence throughout the year with an increasing intensity in the summer and fall periods. Forest fires pose a significant threat to ecosystems, property and human lives. Early detection and rapid response are critical to mitigate the devastating effects of these fires. This article presents a Long Range (LoRa) Alert Network System designed for the early prediction and timely notification of forest fires. The system leverages LoRa technology to create a robust and cost-effective wireless communication network in remote forested areas. These fires primarily stem from various natural and environmental phenomena and natural disasters. The timely dissemination of forest fire alerts was hampered, resulting in delays in fire management. In order to address this issue, efforts were made to enhance the capability for prompt forest fire detection. The challenges predominantly revolve around forested regions where data communication infrastructure is deficient. In the event of a forest fire, there exists a network barrier that impedes information transmission. Consequently, forest fire detection systems leveraging Mesh LoRa networks and image processing networks have been devised. An integrated module within the LoRa/GPS HAT has been explored as a potential solution to the fire predicament. The Flame Sensor Module, functioning as a fire detection sensor component, and the LoRa/GPS HAT, serving as a hardware medium for radio frequency data transmission communication, have been employed. The interconnection of these devices within a network facilitates the development of a prototype fire detection system. Combining a Flame Sensor Module with a LoRa/GPS HAT is indeed a viable approach to creating a prototype fire detection and alert system. By combining the Flame Sensor Module with the LoRa/GPS HAT, a scalable and cost-effective fire detection and alert system appropriate for distant and wooded locations with limited traditional communication infrastructure is created. This system can play a crucial role in early fire detection, potentially reducing the severity of forest fires and protecting both natural resources and human lives.

Generalized efficient robust predictive control for networked interval type-2 T–S fuzzy system with adaptive event-triggered scheme

This article studies the generalized efficient robust predictive control (GERPC) for the nonlinear systems denoted by interval type-2 (IT2) Takagi–Sugeno (T–S) fuzzy model over networks with consideration of packet dropout, bounded disturbance and adaptive event-triggered scheme (AETS). First, the packet dropout is described by a Bernoulli process, and an AETS with thresholds that can be self-regulated according to different situations is employed to decide whether to release data into the communication network, so as to reduce the data transmission frequency and the network burden; Second, taking into consideration of packet dropout and AETS, a unified IT2 T–S fuzzy control model based on GERPC is established, and the stability of closed-loop system with bounded disturbance is guaranteed by quadratic boundedness (QB) technique; Third, generalized efficient robust predictive controller is designed to obtain a larger initial feasible region, smaller online computation and acceptable control performance. The unconstrained control law is designed offline, and a new variable will be optimized online to achieve good control performance, which is introduced to adjust the control quantity. Then, the convex LMI reformulation method is utilized to handle non-convex terms in optimization problem, and the effectiveness of the GERPC algorithm is proved by the matrix partition technique. At last, the effectiveness of the designed controller based on the GERPC strategy is verified by a given simulation experiment.

An Adaptive Event-Triggered Consensus Approach for MASs With Network-Induced Delays

This study investigates the consensus control problem of linear multi-agent systems (MASs) with network-induced delays (NIDs). A state feedback controller based on an event-triggered transmission scheme is proposed, where the novel adaptive event-triggering mechanism (ETM) is used to lower the frequency of data transmission. In contrast to previous works, sufficient conditions related to the consensus for the resulting closed-loop control systems are derived using a discontinuous looped Lyapunov functional (DLLF) and the corresponding reciprocally convex protocol. It is demonstrated that the consensus errors of resulting closed-loop control systems are asymptotically stable and the Zeno behavior is excluded. Finally, a numerical example of an unmanned aerial vehicle (UAV) model is presented to demonstrate the effectiveness of our proposed theoretical results.

Dual-Domain Triggered Iterative Learning Control for Networked Switched Systems Against Denial-of-Service Attacks

In this article, dual-domain triggered iterative learning control (ILC) is studied for networked switched systems against denial-of-service (DoS) attacks. Unlike existing research on ILC focusing only on updating between iterations, a novel dual-domain (time and iteration domains) triggered ILC is proposed. The updates between iterations and updates of network feedback information for each iteration on the time scale are performed, reducing the iteration steps and network data transmission frequency within each iteration. In each iteration, the system output is transmitted via a network, which is assumed to be vulnerable to DoS attacks. An attack detection mechanism and buffer-based compensation mechanism are proposed. Then, the boundedness of the iterative tracking error of the networked switched systems is ensured through a switching stability analysis based on the Lyapunov theory. Finally, the advantages of the proposed methods are substantiated by a simulation example consisting of three parts.

Battery-Powered RSU Running Time Monitoring and Prediction Using ML Model Based on Received Signal Strength and Data Transmission Frequency in V2I Applications

The application of the Internet of Things (IoT), vehicles to infrastructure (V2I) communication and intelligent roadside units (RSU) are promising paradigms to improve road traffic safety. However, for the RSUs to communicate with the vehicles and transmit the data to the remote location, RSUs require enough power and good network quality. Recent advances in technology have improved lithium-ion battery capabilities. However, other complementary methodologies including battery management systems (BMS) have to be developed to provide an early warning sign of the battery's state of health. In this paper, we have evaluated the impact of the received signal strength indication (RSSI) and the current consumption at different transmission frequencies on a static battery-based RSU that depends on the global system for mobile communications (GSM)/general packet radio services (GPRS). Machine learning (ML) models, for instance, Random Forest (RF) and Support Vector Machine (SVM), were employed and tested on the collected data and later compared using the coefficient of determination (R2). The models were used to predict the battery current consumption based on the RSSI of the location where the RSUs were imposed and the frequency at which the RSU transmits the data to the remote database. The RF was preferable to SVM for predicting current consumption with an R2 of 98% and 94%, respectively. It is essential to accurately forecast the battery health of RSUs to assess their dependability and running time. The primary duty of the BMS is to estimate the status of the battery and its dynamic operating limits. However, achieving an accurate and robust battery state of charge remains a significant challenge. Referring to that can help road managers make alternative decisions, such as replacing the battery before the RSU power source gets drained. The proposed method can be deployed in other remote WSN and IoT-based applications.

Distributed Event-Triggered Formation Control of Planar Vehicles Without Velocity Sensors

In this paper, an event-triggered distributed formation control method is proposed for multiple planar vehicles which are modeled as uncertain Euler-Lagrangian systems (ELSs). Firstly, a position and orientation (PAO)-based event-triggered mechanism is designed to decrease the frequency of data transmission through the wireless network. According to the PAO information at the event-triggered time, an event-triggered high-gain extended state observer (EHGESO) is developed to remove the demand of velocity information in conventional backstepping technique and eliminate the requirement of continuous PAO information in traditional HGESO design. Under the developed EHGESO and the PAO-based event-triggered mechanism, planar vehicles can cooperatively move along the parameterized path, and can transmit information with their neighbor vehicles only if the designed event-triggered mechanism is violated. The stability is proved by employing input-to-state stability (ISS) and semi-global uniformly ultimately bounded (SGUUB) stability theory. Eventually, a simulation of three-degree-of-freedom surface vehicle models is offered to illustrate the effectiveness of the developed control method.

H∞Bipartite Synchronization of Double-Layer Markov Switched Cooperation-Competition Neural Networks: A Distributed Dynamic Event-Triggered Mechanism.

In this article, the H∞ bipartite synchronization issue is studied for a class of discrete-time coupled switched neural networks with antagonistic interactions via a distributed dynamic event-triggered control scheme. Essentially different from most current literature, the topology switching of the investigated signed graph is governed by a double-layer switching signal, which integrates a flexible deterministic switching regularity, the persistent dwell-time switching, into a Markov chain to represent the variation of transition probability. Considering the coexistence of cooperative and antagonistic interactions among nodes, the bipartite synchronization of which the dynamics of nodes converge to values with the same modulus but the opposite signs is explored. A distributed control strategy based on the dynamic event-triggered mechanism is utilized to achieve this goal. Under this circumstance, the information update of the controller presents an aperiodic manner, and the frequency of data transmission can be reduced extensively. Thereafter, by constructing a novel Lyapunov function depending on both the switching signal and the internal dynamic nonnegative variable of the triggering mechanism, the exponential stability of bipartite synchronization error systems in the mean-square sense is analyzed. Finally, two simulation examples are provided to illustrate the effectiveness of the derived results.

Event-based Predefined-time Deployment Control for Space Triangular Tethered Satellite System with Input Quantization

The problem of space triangular tethered satellite system deployment in the presence of external disturbances, input quantization, and limited communication from the controller to the actuator is investigated in this paper. A disturbancebased predefined time sliding mode controller is employed to ensure the system converges to the neighborhood of zero without depending on initial conditions. An input quantizer and an eventtriggered mechanism are integrated into the proposed controller to reduce the frequency and bandwidth of data transmission from controller to actuator. An adaptive law is considered to counteract the control input chattering produced by quantization errors and event-triggered input errors. The whole proposed control scheme guarantees that the closed-loop system is semi-globally stable and converges to a stable region at the predefined time. Finally, the effectiveness of the proposed scheme is confirmed by simulation tests.

Resilient Unscented Kalman Filtering Fusion With Dynamic Event-Triggered Scheme: Applications to Multiple Unmanned Aerial Vehicles

In this article, the resilient unscented Kalman filtering fusion issue is investigated for a class of nonlinear systems under the dynamic event-triggered mechanism where each sensor node transmits the measurement information to its corresponding local filter in an intermittent way. Compared with its static counterpart, the dynamic event-triggered scheme is capable of scheduling the frequency of data transmission in a more efficient way, thereby better reducing communication burden and energy consumption. In addition, for each local filter, the variation of the filter gain is characterized by a multiplicative noise term. To cope with the intractable problem of computing the cross covariance between local filters, the sequential covariance intersection fusion strategy is introduced into the proposed distributed fusion framework. Finally, the proposed algorithm is applied to a maneuvering target tracking scenario with multiple unmanned aerial vehicles, and both numerical simulations and hardware experiments are provided to elucidate the effectiveness and practicality of the proposed filtering scheme.

Security-Based Passivity Analysis of Markov Jump Systems via Asynchronous Triggering Control.

This article considers the security-based passivity problem for a class of discrete-time Markov jump systems in the presence of deception attacks, where the deception attacks aim to change the transmitted signal. Considering the impact of deception attacks on network disruption, it causes the existence of time-varying delays in signal transmission inevitably, which makes the controlled system and the controller work asynchronously. The asynchronous control method is employed to overcome the nonsynchronous phenomenon between the system mode and controller mode. On the other hand, to reduce the frequency of data transmission, a resilient asynchronous event-triggered control scheme taking deception attacks into account is designed to save communication resources, and the proposed controller can cover some existing ones as special examples. Moreover, different triggering conditions corresponding to different jumping modes are developed to decide whether state signals should be transferred. A new stability criterion is derived to ensure the passivity of the resultant system although there exist deception attacks. Finally, a simulation example is given to verify the theoretical analysis.

ECONOMIC EFFICIENCY OF VOLTAGE AND TEMPERATURE DRIFT COMPENSATION CIRCUIT FOR DIGITAL DELAY LINE

Nowadays when semiconductor devices sizes reached to the few nanometers, high-speed SERDES systems became less power-consuming, and systems operating frequen-cies reached dozens of gigahertz. Despite these advantages, devices became more vulne-rable against temperature-voltage drifts. Also, because of dozens of gigahertz frequency data transmission, it became more complicated to meet timing constraints in Serdes sys-tems. Therefore, it is important to have stable de-skew mechanisms, otherwise data loss and other timing issues can be observed. One of the commonly used circuits to over-come this problem is digital delay lines (DDL). Often integrated circuits (IC) being used in non-standard environments, so it is necessity to have voltage-temperature (VT) compensation circuit (VTDCC), otherwise DDL will lose its effectiveness. The development of the proposed of VTDCC has become an economically important condition, because VTDCC allows digital delay line (DDL) to work correctly in non-standard conditions, which increases the demand for DDL. Digital delay line with included compensation circuit has shown around 51% DDL delay range improvement during non-standard conditions VT drift compensation circuit requires an additional 37% area in DDL.

Dynamic Event-Triggered Output Feedback Control for Networked Systems Subject to Multiple Cyber Attacks.

This article is concerned with the problem of the H∞ output feedback control for a class of event-triggered networked systems subject to multiple cyber attacks. Two dynamic event-triggered generators are equipped at sensor and observer sides, respectively, to lower the frequency of unnecessary data transmission. The sensor-to-observer (STO) channel and observer-to-controller (OTC) channel are subject to deception attacks and Denial-of-Service (DoS) attacks, respectively. The aim of the addressed problem is to design an output feedback controller, with the consideration of the effects of dynamic event-triggered schemes (DETSs) and multiple cyber attacks. Sufficient condition is derived, which can guarantee that the resulted closed-loop system is asymptotically mean-square stable (AMSS) with a prescribed H∞ performance. Moreover, we provide the desired output feedback controller design method. Finally, the effectiveness of the proposed method is demonstrated by an example.

Event-triggered fuzzy finite-time reliable control for dynamic positioning of nonlinear unmanned marine vehicles

This paper studies the fuzzy finite-time reliable dynamic positioning (DP) control for nonlinear unmanned marine vehicles. Firstly, the motion dynamics of nonlinear unmanned marine vehicles is modeled by the Takagi-Sugeno (T-S) fuzzy system. Secondly, a fuzzy state observer is designed to estimate the immeasurable position and velocity of unmanned marine vehicles. In order to decrease the frequency of data transmission of actuators and sensors, a dynamic event-triggered mechanism is presented based on unmanned marine vehicles information and the estimation error. Then, a fuzzy event-triggered reliable output feedback control method is presented by finite-time theory to tackle the actuator faults problem occurring in unmanned marine vehicles. The sufficient finite-time stable conditions in the form of LMIs are established via constructing finite-time Lyapunov-Krasovskii functional. Ultimately, the computer simulation results and comparisons with the existing control methods verify the advantages of the presented control method.

The Effect of Some Meteorological Parameters on Wireless Data Transmission

It is essential to bring together the data measured in agricultural lands, greenhouses and animal shelters transmit to follow the data online. Wireless and wired systems have advantages and disadvantages. In wired systems, there is a cost of cabling, but data can be transmitted more securely. In wireless systems, system installation is cheap, but there are losses in data transmission. Wireless data transmission carried out in the outdoor environment takes place under surrounding climatic conditions. In this study, the effect of atmospheric meteorological factors on data loss in wireless data transmission system was tried to be determined. For this purpose, the losses that occur during the transfer of the data measured in the greenhouse in Bursa Uludağ University Faculty of Agriculture Research Farm to the office 150 m away are discussed. Temperature, humidity, precipitation, wind speed and atmospheric pressure were used as meteorological parameters, and 4 different frequencies from the civil use frequency range (2420, 2440, 2460 and 2480 Mhz) were used as data transmission frequency. The SPSS package was used for the correlation analysis with the data set. According to the results of the correlation analysis, relative humidity has a statistically significant effect on the data transmission losses at all data transmission frequencies (p

Adaptive Event-Triggered [formula omitted] Control of Semi-Markov Jump Distributed Parameter Systems

This paper focuses on the problem of adaptive event-triggered L2−L∞ control for distributed parameter systems with semi-Markov jump parameters. An event-triggered transmission scheme, whose threshold function can be adaptively adjusted, is established to decrease the frequency of data transmission. Simultaneously, the utilization of limited network bandwidth resources is also improved due to plenty of “unnecessary” packets being discarded before accessing networks. Furthermore, the jumping of stochastic parameters in networks can be described by a semi-Markov jump model, in which the sojourn-time is considered subject to the Weibull distribution instead of the exponential distribution. Based on the aforesaid discussions, a mode-dependent controller is designed under an adaptive event-triggered scheme. Whereafter, some criteria are constructed based on the Lyapunov stability theory to guarantee stochastic stability and a prescribed L2−L∞ performance of the system. Ultimately, two simulation examples are provided to verify the feasibility of the proposed design approach.

Robust Formation Control for Nonlinear Heterogeneous Multiagent Systems Based on Adaptive Event-Triggered Strategy

In this article, a distributed adaptive event-triggered formation control strategy is proposed for unified nonlinear heterogeneous multiagent systems under uncertainties and disturbances to achieve time-varying formations. To reduce the frequency of data transmission, a distributed dual adaptive observer with an event-triggered strategy is developed to estimate the states of a reference exosystem. Without incurring prior global information about a communication graph, a novel robust formation controller, with dynamic distributed compensators for uncertainties and disturbances, is designed based on an observer result and a nonlinear internal control principle. Finally, both simulation and experiment are conducted for tracking and patrolling formation to verify the effectiveness of the proposed formation control strategy and its robustness. Note to Practitioners—This article addresses the collaborative formation problem of multiagent systems that has potential applications in transportation and disaster relief. The design of robust and energy-saving coordination strategies is challenging in heterogeneous multivehicle systems. The proposed distributed method is suitable for large-scale uncertain heterogeneous systems, and the use of the dual adaptive event-triggered strategy reduces the data transmission rate.

Event-triggered Observer-based Robust H∞ Fault-tolerant Control for Markov Jumping NCSs

For network control systems (NCSs) with parameter uncertainties, packet loss and time-delays, the design for the observer and robust H∞ fault-tolerant controller is discussed with the event-triggered mechanism. The random Markov jumping system is used to describe the NCSs with faults. In order to reduce the frequency of data transmission and save network channel resources, the discrete event-triggered mechanism is utilized, which allows the NCS to transmit the signal when the trigger condition is met only. Under this mechanism the system states are estimated by the observer provided, while a robust fault-tolerant controller is designed for actuator failures, so that the NCSs can remain stable in the event of failures. Finally, the proposed method is verified by simulation, the respective results showing its validity and feasibility.

Output-Based Event-Triggered Cooperative Robust Regulation for Constrained Heterogeneous Multiagent Systems.

The output-based event-triggered cooperative output regulation problem is addressed for constrained linear heterogeneous multiagent system in this article. In light of the robust control theory, H∞ leader-following consensus with respect to exogenous signals, including both disturbance to be rejected and reference state of leader to be tracked, is guaranteed. Meanwhile, the system performance alleviates degradation through a model recovery anti-windup technique while encountering input saturation. Furthermore, the follower's self-state observer, the leader-state observer, and the anti-windup auxiliary system are integrated into a comprehensive system, and a unified event-triggering mechanism of full states is addressed. A fixed lower bound of sampled interval is adopted such that the frequency of data transmission gets reduced and no Zeno-behavior happens. Both the input and output of the follower's controller and anti-windup compensator hold constant, respectively, during the event-triggered intervals such that the resulting output-based event-triggered controller can be directly implemented in a digital platform. Finally, a simulation example is provided to illustrate the effectiveness.