Synchronization Performance Research Articles

Research on the Coordinated Control of Mining Multi-PMSM Systems Based on an Improved Active Disturbance Rejection Controller

This study focuses on the problems of poor control performance, synchronization performance and stability in multi-motor permanent magnet drive systems in mining belt conveyors when a Proportional Integral Derivative (PID) controller is used to control the multi-motor. In this paper, a system model for three-motor synchronous control of a mine belt conveyor is established. On this basis, an Enhanced first-order Active Disturbance Rejection Controller (Efal_ADRC) is designed based on an optimized nonlinear function. Additionally, a weighted arithmetic mean is used to enhance the compensator of the ring coupling control structure. Finally, the system model is evaluated and simulated using various algorithms. Results show that synchronous control of a multi-Permanent Magnet Synchronous Motor (multi-PMSM) drive system based on the Efal_ADRC ring coupling control structure has better anti-interference ability, control accuracy and synchronization, which is conducive to the stable and efficient safe operation of the belt conveyor.

Long-Interval Prostaglandin F2α Combined with GnRH Improves the Estrus Synchronization and Reproductive Performance of Sheep During the Breeding Season

To improve the efficiency of prostaglandin F2α (PG)-based estrus synchronization in sheep, this study assessed the effect of the gonadotropin-releasing hormone (GnRH) included in the long-interval PG treatment regimen for sheep estrus synchronization during the breeding season. In experiment 1, 30 multiparous Mongolian sheep (3–4.5 years old) were randomly divided into three groups. In the progesterone (P4)–equine chorionic gonadotropin (eCG) group (P4-eCG, n = 10), the ewes were synchronized with intravaginal P4 sponges for 14 days, and received an injection of 330 IU of eCG at sponge withdrawal. In the PG group (n = 10), the ewes received two doses of 0.1 mg PG with a 14 day interval. In the PG-GnRH-PG group (n = 10), the ewes were synchronized by two doses of 0.1 mg PG with a 14 day interval like that in the PG group, but received 50 μg of GnRH 7 days after the first injection of PG. It was found that, at the end of treatment, the number of corpus luteum on the ovaries and the concentration of the serum P4 in the PG-GnRH-PG group were significantly higher than that of the PG and P4-eCG groups. In experiment 2, 59 multiparous Mongolian sheep (3–4.5 years old) were assigned to three groups, like in experiment 1 (n = 20, 20 and 19 for the P4-eCG, PG and PG-GnRH-PG groups, respectively). The estrus of ewes in the PG-GnRH-PG group was more synchronous compared to the PG group. After insemination of the estrus ewes, the pregnancy rate was numerically but not significantly higher in the PG-GnRH-PG group than that in the P4-eCG and the PG groups. In a field test, 285 multiparous Hu sheep (3–4.5 years old) were randomly assigned to a P4-eCG group (n = 142) and PG-GnRH-PG group (n = 143). Timed artificial insemination showed no significant differences in the rates of pregnancy and lambing between the PG-GnRH-PG and P4-eCG groups. We conclude that the addition of GnRH in the long-interval PG protocol may improve the efficiency of PG-based estrus synchronization, and would represent a potential alternative to the conventional P4-eCG based protocol during the breeding season in sheep.

Optimising torque for three-disc afpmsm in electric vehicles using bp_ann and anfis algorithms

Designing an optimal torque distribution controller for the three-disc axial flux permanent magnet synchronous (three-disc AFPMSM) optimises performance while ensuring robustness, stability, and adaptability in a real-world condition. This is crucial for maximising the potential of AFPMSM, particularly in a modern application like an electric vehicle and a renewable energy. Thus, a controller compatible with more complex systems in the future is essential. This paper presents a system that combines torque control algorithms based on a back-propagation neural network (BP-ANN) and an Adaptive Neuro-Fuzzy Inference System (ANFIS). The BP-ANN uses a multi-layer structure where the input layer processes factors such as load torque, rotational speed, and stator current, hidden layers model complex nonlinear interactions, and the output layer predicts optimal torque for AFPMSM operation. Training involves minimising the error between predicted and actual torque through gradient descent and iterative adjustments of weights and biases. The ANFIS-based control enhances performance by integrating neural network learning with fuzzy logic to optimise torque output. By leveraging the strengths of both BP-ANN and ANFIS, the system offers a stable, efficient, and adaptable solution for three-disc AFPMSMs. The Matlab/Simulink simulations confirm its effectiveness, showing balanced torque distribution, reduced energy losses, improved drivetrain efficiency, and adaptability to sudden load or road changes, ensuring stability and enhanced dynamic response

Real-time multi-sensor fusion for object detection and localization in self-driving cars: A Carla simulation

Research on integrating camera and LiDAR in self-driving car systems has important scientific significance in the context of developing 4.0 technology and applying artificial intelligence. The research contributes to improving the accuracy in recognizing and locating objects in complex environments. This is an important foundation for further research on optimizing response time and improving the safety of self-driving systems. This study proposes a real-time multi-sensor data fusion method, termed "Multi-Layer Fusion," for object detection and localization in autonomous vehicles. The fusion process leverages pixel-level and feature-level integration, ensuring seamless data synchronization and robust performance under adverse conditions. Experiments conducted on the CARLA simulator. The results show that the method significantly improves environmental perception and object localization, achieving a mean detection accuracy of 95% and a mean distance error of 0.54 meters across diverse conditions, with real-time performance at 30 FPS. These results demonstrate its robustness in both ideal and adverse scenarios

Chaos Synchronization in a Dual-Laser Chaotic Multiplexing System Based on Nanolasers

Nanolaser (NL), as an important optical source device, has a significant impact on photonic integrated circuits and has become a research hotspot in recent years. This study investigates the synchronization performance of a dual-channel laser chaotic multiplexing system based on NLs and employs an active-passive decomposition to enhance signal processing and multiplexing efficiency. By establishing a rate equation model, the synchronization characteristics of the system were analyzed, focusing on the effects of two key parameters—the Purcell factor (F) and the spontaneous emission coupling factor (β)—as well as system parameters, single-parameter mismatches, and multi-parameter mismatches. Numerical simulations show that, with proper parameter configurations, the two master NLs can maintain low correlation, ensuring the "pseudo-orthogonal" of chaotic signals while achieving high-quality chaotic synchronization with their paired slave NLs. The study found that both the Purcell factor (F) and the spontaneous emission coupling factor (β) significantly influence the synchronization performance of the system, and the optimal parameter ranges for achieving high-quality synchronization were identified. Additionally, the effects of feedback strength and frequency detuning were explored, revealing that frequency detuning plays a more critical role in the synchronization between the master NLs. The impact of parameter mismatches on system synchronization performance was also emphasized. The system exhibits robustness against single-parameter mismatches, with minimal impact on master-slave synchronization quality. However, multi-parameter mismatches introduce more complex effects. Compared to traditional semiconductor laser systems, this system can maintain "pseudo-orthogonal" over a wider parameter range, achieving higher security and lower channel interference. This research lays a theoretical foundation for chaos synchronization based on NLs and provides new insights for designing secure, stable, and efficient optical communication systems.

Impact of Synchronous Condenser Thermodynamic Performance on Power Grid Frequency Stability

Impact of Synchronous Condenser Thermodynamic Performance on Power Grid Frequency Stability

TELEREHABILITATION. CURRENT OPPORTUNITIES AND PROBLEMS OF REMOTE PATIENT MONITORING

In the last five years, against the background of the appearance of COVID-19 in the world, the direction of remote telerehabilitation is intensively developing, which requires the improvement and implementation of new approaches to the patients conditions` synchronous monitoring with the involvement of the latest technical developments. The purpose of the study. To explore the latest publications on the possibilities of remote monitoring of patients during rehabilitation examinations and synchronous telerehabilitation procedures. Research material and methods. Publications of foreign scientists in the fields of clinical, physical and rehabilitation medicine, biometrics, digital technologies on the implementation of synchronous monitoring technologies for the condition of patients with various pathologies The results. Research of modern publications has shown that conducting synchronous sessions of remote examination of patients allows with a high degree of probability to conduct a general examination of the patient, conduct anthropometric and some functional studies. Among the latest –studies of changes in heart rate, blood pressure, respiratory rate, oxygen saturation, ECG and EEG data. Their results can be transmitted for direct evaluation by a doctor. There are certain problems during synchronous performance of tests with physical load to failure due to the impossibility of observing safety conditions. Technical solutions have been found for the transmission of bimetric signals during the telerehabilitation procedure. Thus, the combination of virtual reality or augmented reality with devices such as robots, sensors and wearables can be used for remote monitoring, assessment and diagnosis. These advanced methods pave the way for the transition from traditional to personalized rehabilitation by identifying the needs of each patient and tailoring the rehabilitation process to their individual characteristics. Conclusions. The development of modern technologies and digital medicine has led to the emergence of the remote provision of services in the rehabilitation system, which on the one hand significantly increases the possibilities of access to the rehabilitation system, and on the other hand significantly increases the requirements for their implementation. First of all, this concerns the safety of telerehabilitation procedures. Adherence to basic safety requirements should be given due attention, which can be achieved, first of all, with the use of remote synchronous monitoring of the patient's condition, when the PhRM doctor can objectify changes in the patient's body under the direct influence of telerehabilitation tools.

Design and implementation of a synchronous Hardware Performance Monitor for a RISC-V space-oriented processor

Design and implementation of a synchronous Hardware Performance Monitor for a RISC-V space-oriented processor

Pinning Synchronization for Stochastic Complex Networks With Randomly Occurring Nonlinearities: Tackling Bit Rate Constraints and Allocations.

In this article, the ultimately bounded synchronization problem is investigated for a class of discrete-time stochastic complex networks under the pinning control strategy. Communication between system nodes and the remote controller is facilitated via wireless networks subject to bit rate constraints. The system model is distinguished by the inclusion of randomly occurring nonlinearities. A coding-decoding transmission mechanism under constrained bit rates is introduced to characterize the digital transmission process. To achieve synchronization of the network nodes with the unforced target node, a pinning controller is specifically devised based on the information from partially selected nodes. Through the application of the stochastic analysis method, a sufficient condition is derived for ensuring the mean-square boundedness of the synchronization error system. In addition, an optimization algorithm is introduced to address bit rate allocation and the design of desired controller gains. Within the presented theoretical framework, the correlation between the mean-square synchronization performance and bit rate allocation is further elucidated. To conclude, a simulation example is provided to substantiate the efficacy of the recommended pinning control approach.

Comparative analysis of two novel chaotic systems, and validation of hybrid function projective and complete synchronization using active-adaptive control

Abstract This study investigates the nonlinear characteristics of two novel 3D-chaotic models using phase portraits, bifurcation diagrams, Lyapunov exponents, time series analysis, and Poincaré maps. Here, we have examined hybrid-function projective and complete synchronization schemes via adaptive and active control methods. Moreover, the performance of hybrid-function projective synchronization, utilizing sine, cosine, and exponential terms, is compared to complete synchronization through two control strategies. Our designed controllers ensure asymptotic global chaotic synchronization based on Lyapunov stability principles. We have also compared our results with other competitive schemes and validated the theoretical findings through simulations on the MATLAB platform.

Visual and Radar Data Fusion: Complementary or Alternative Sensors in Intelligent Driving Systems

This article explores the role and advantages and disadvantages of visual and radar data fusion in intelligent driving systems. With the rapid development of intelligent driving technology, the comprehensive perception of the environment by car perception systems has become crucial, usually requiring the combination of low, medium, and high-precision sensors. Visual sensors perform excellently in acquiring high-resolution images and recognizing detailed information, while radar sensors have higher stability and penetration in harsh weather conditions. Due to the limitations of a single sensor in complex driving environments, data fusion has become a key strategy for improving the performance of perception systems. By comparing different perception schemes and application scenarios, this article analyzes the actual effects and potential advantages of visual and radar data fusion, revealing its important role in intelligent driving technology. Fusion technology can compensate for the shortcomings of various sensors, and improve the accuracy and reliability of environmental perception, but still faces challenges in data synchronization, algorithm selection, and real-time performance. This article aims to provide valuable insights for the development of future intelligent driving technology.

Adaptive Weighted Particle Swarm Optimization for Controlling Multiple Switched Reluctance Motors with Enhanced Deviatoric Coupling Control

Switched reluctance motors (SRMs) are widely used in industrial applications due to their advantages. Multi-motor synchronous control systems are crucial in modern industry, as their control strategies significantly impact synchronization performance. Traditional deviation coupling control structures face limitations during the startup phase, leading to excessive tracking errors and exacerbated by uneven load distribution, resulting in desynchronized motor acceleration and increased speed synchronization errors. This study proposes a modified deviation coupling control method based on an adaptive weighted particle swarm optimization (PSO) algorithm to enhance multi-motor synchronization performance. Traditional deviation coupling control applies equal reference torque inputs to each motor’s current loop, failing to address uneven load distribution and causing inconsistent accelerations. To resolve this, a gain equation based on speed deviation is introduced, incorporating self-tracking error and gain coefficients for dynamic synchronization error compensation. The gain coefficients are optimized using the adaptive weighted PSO algorithm to improve system adaptability. A simulation model of a synchronization control system for three SRMs was developed in the Matlab/Simulink R2023b environment. This model compares the synchronization performance of traditional deviation coupling, Fuzzy-PID improved structure, and adaptive PSO improved structure during motor startup, sudden speed increases, and load disturbances. The validated deviation coupling control structure achieved the initial set speed in approximately 0.236 s, demonstrating faster convergence and a 6.35% reduction in settling time. In both the motor startup and sudden speed increase phases, the two optimized methods outperformed the traditional structure in dynamic performance and synchronization accuracy, with the adaptive PSO structure improving synchronization accuracy by 54% and 37.17% over the Fuzzy-PID structure, respectively. Therefore, the PSO-optimized control system demonstrates faster convergence, improved stability, and enhanced synchronization performance.

Behavior of leadless atrioventricular synchronous pacing during exercise

BackgroundThe leadless Micra AV pacemaker is designed to provide atrioventricular (AV) synchronous tracking by detecting atrial contraction. Detection of the mechanical atrial signals can become challenging at a fast sinus rate. ObjectiveThe purpose of the study was to evaluate the AV synchronous performance at exercise in outpatients implanted with a Micra AV pacemaker. MethodsPatients were enrolled at least 1 month after Micra AV implantation and underwent a cycle test protocol. Serial device interrogations (each minute) and continuous electrocardiograms were collected to measure AV synchrony and determine maximum achieved sinus and ventricular rates for each patient. In addition, the A1, A2, A3, and A4 accelerometer signal amplitudes were measured at the start and peak of exercise. ResultsThirty-five patients (mean age 75.6 ± 13.4 years; 80% male) were enrolled in the study; 22 (64%) were predominantly ventricular paced (>90%) during exercise. Average AV synchrony was 90.4% in the entire cohort and 84.7% in patients with high-degree AV block. The mean amplitude of the accelerometer signals increased significantly from the start to the peak of exercise: A1, 4.1–6.3 m/s2; A2, 2.4–3.8 m/s2; and A4, 4.5–7.6 m/s2 (P < .01 for all). The time from the VP-A2 decreased 25 ms for each 100 ms of the R-R interval decrease. ConclusionMaintaining AV synchrony during maximal exercise in elderly patients is achievable by adequate detection of atrial contraction at high sinus rates by the leadless Micra AV pacemaker. All components of the accelerometer signal increased, likely because of increased contractility related to exercise.

Stabilization and Synchronization of Neural Networks via Impulsive Adaptive Control.

This article addresses the stabilization and synchronization problems of coupled neural networks (NNs) via an impulsive adaptive control (IAC) strategy. Unlike the traditional fixed-gain-based impulsive methods, a novel discrete-time-based adaptive updating law for the impulsive gain is designed to maintain the stabilization and synchronization performance of the coupled NNs, where the adaptive generator only intermittently updates its data at the impulsive instants. Several stabilization and synchronization criteria for the coupled NNs are established based on the impulsive adaptive feedback protocols. Additionally, the corresponding convergence analysis are also provided. Finally, the effectiveness of the obtained theoretical results is illustrated using two comparison simulation examples.

Bionic driving method of multi-actuator hydraulic synchronization system based on wild goose cluster flight principle

Heavy equipment is often driven synchronously by multi-actuator hydraulic system. However, when the load deviation of the actuators is large, such systems exhibit serious energy loss and inferior synchronization performance. Inspired by the cluster flight of wild goose, a bionic hydraulic actuator and a bionic driving method are proposed. Different from traditional two-chamber hydraulic actuator, the redundant freedom of the bionic hydraulic actuator is used to simulate the airflow vortex formed by wild goose. By doing so, the bionic actuators can provide or accept auxiliary driving force from other actuators according to different topology. In addition, the optimal load balance performance of multi-actuators can be realized by adjusting the auxiliary driving pressure between actuators. In this study, topology switching rules and auxiliary pressure control strategies are discussed. Numerical simulation results demonstrate that the proposed method can reduce the maximum load deviation by over 85% and the synchronization error by over 80% in typical cases.

Resonance and beat perception of ballroom dancers: An EEG study.

The ability to synchronize the perceptual and motor systems is important for full motor coordination and the core determinant of motor skill performance. Dance-related training has been found to effectively improve sensorimotor synchronization, however, the underlying characteristics behind these improvements still warrant further exploration. This study was conducted to investigate the behavioral and neuroactivity characteristics of ballroom dancers relative to those of non-dancers. Thirty-two dancers (19.8 ± 1.8 years old) and 31 non-dancers (22.6 ± 3.1 years old) were recruited to perform a finger-tapping task in synchrony with audiovisual beat stimuli at two intervals: 400 and 800 ms, while simultaneously recording EEG data. Behavioral and neural activity data were recorded during the task. The dancers employed a predictive strategy when synchronizing with the beat. EEG recordings revealed stronger brain resonance with external rhythmic stimuli, indicating heightened neural resonance compared to non-dancers (p < 0.05). The task was more challenging with an 800-ms beat interval, as observed through both behavioral metrics and corresponding neural signatures in the EEG data, leading to poorer synchronization performance and necessitating a greater allocation of attentional resources (ps < 0.05). When performing the finger-tapping task involving audiovisual beats, the beat interval was the primary factor influencing movement synchronization, neural activity and attentional resource allocation. Although no significant behavioral differences were observed between dancers and non-dancers, dancers have enhanced neural resonance in response to rhythmic stimuli. Further research using more ecologically valid tasks and stimuli may better capture the full extent of dancers' synchronization abilities.

Chaotic laser time series prediction based on an improved logistic mapping algorithm echo state network

Chaos synchronization plays vital functions in the fields of optical chaos secure communication. The synchronization performance can be significantly degraded by parameter mismatches between the chaotic transmitter and receiver. In this paper, the Deep-Logistical Mapping Echo State Network (D-LMESN) is proposed to enhance the performance of chaos synchronization. The network is upgraded by using an improved logical mapping algorithm and a deep reserve pool structure with phase space reconstruction. Results show that D-LMESN exhibits better performance in the prediction of chaotic time series, thanks to the adaptive parameter adjustment, which increases the ability to capture the dynamic characteristics of complex systems. Compared with ESN, the mean square error of this model is reduced by 55% and 72%, respectively, in chaotic laser simulation and actual data experiments. This provides a new possibility, to our knowledge, for the development of chaotic secure communication.

Research on the performance of high-strength explosive ink and application of direct writing technology in micro-explosive network

With the widespread application of 3D direct writing technology in the field of energetic materials, it has become a current research topic to design an explosive ink with excellent micro-size detonation performance and high-strength mechanical properties and combining it with explosion network technology to improve detonation synchronization has become a research hotspot. This article uses FEVE-F2311 and PF as the composite bonding system, submicron CL-20 as the main explosive, and adds an appropriate amount of TDI as the curing agent to prepare an explosive ink with excellent micro-size detonation performance and high-strength mechanical properties. Research shows that the explosive ink has a detonation velocity of 7322 m·s−1 at a charge density of 1.621 g·cm−3, a critical propagation size of 0.3×0.3 mm, a critical propagation thickness of 1×0.040 mm, and a maximum detonation Corners can reach 160°. The error of detonation synchronization in the "one in and six out" micro-explosion network is within 150 ns, showing excellent detonation synchronization. The nano-indentation test shows that the average elastic modulus of CL-20-based explosive ink is 6.991 GPa and the average hardness is 0.200 GPa, showing excellent mechanical properties; the compressive stress-strain curve shows that its average compressive stress is 7.62 MPa, showing excellent Compressive strength. It not only greatly improves the mechanical properties of explosive ink, but also provides a method to improve the synchronization performance of micro-explosive networks.

Zadoff–Chu Sequence Pilot for Time and Frequency Synchronization in UWA OFDM System

In underwater communications for 6G, Doppler effects cause the coherent time to become similar to or shorter than the orthogonal frequency division multiplexing (OFDM) symbol length. Conventional time and frequency synchronization methods require additional training symbols for synchronization, which reduces the traffic data rate. This paper proposes the Zadoff–Chu sequence (ZCS) pilot-based OFDM for time and frequency synchronization. The proposed method transmits ZCS as a pilot for OFDM symbols and simultaneously transmits traffic data to increase the traffic data rate while estimating the CFO at each coherence time. For time–frequency synchronization, the correlation of the ZCS pilot is used to perform coarse and fine time and frequency synchronization in two stages. Since the traffic data cause interference with the correlation of ZCS pilots, we theoretically analyzed the relationship between the amount of traffic data and interference and verified it through computer simulations. The synchronization and BER performance of the proposed ZCS pilot-based OFDM were evaluated by conduction computer simulations and a practical ocean experiment. Compared to the methods of Ren, Yang, and Avrashi, the proposed method demonstrated a 6.3% to 14.3% increase in traffic data rate with similar BER performance and a 2 dB to 3.8 dB SNR gain for a 14.3% to 23.8% decrease in traffic data rate.

Structural design of cellulose-hyperbranched double-network for enhanced intramolecular diffusion kinetics of heavy metal ion capture processes

Extracting cellulose from agricultural residues and converting it into environmentally friendly adsorbents to solve the heavy metal contamination problem of groundwater and farmland is an effective strategy to achieve high-value utilization of agricultural residues. Herein, we propose a streamlined crosslinking strategy to fabricate a cellulose-based amphoteric hyperbranched adsorbent (MAHPA) in a controlled manner. The strategy involves synthesizing the amphoteric hyperbranched functional reagent first and then crosslinking it with microcrystalline cellulose (MCC). This approach simplifies the complexity of the multi-component cross-linking system, resulting in a conversion rate of reaction reagents exceeding 99 %. MAHPA, with a three-dimensional hyperbranched structure (degree of branching: 0.77), exhibits a high swelling rate (247.62 %) and high densities of carboxyl (7.05 mmol·g−1) and amino (8.27 mmol·g−1) groups. Moreover, the cellulose-hyperbranched double-network structure of MAHPA greatly enhances the intramolecular diffusion kinetics of heavy metal ions on MAHPA, enabling it to complete the removal of low concentrations of Cr(VI), As(V), Pb(II), and Cd(II) within 20 min. Interestingly, MAHPA demonstrates excellent synchronous capture performance for Cr(VI), As(V), Pb(II), and Cd(II) in groundwater at a velocity of 1.60 × 10−2 m·s−1. Meanwhile, applying MAHPA can realize the safe utilization of Cd-As contaminated soil. This work offers a general strategy for the structural design of cellulose-based hyperbranched adsorbent holding great promise as heavy metal contaminated groundwater and soil remediation field.