System Parameters Research Articles

CONTROL DESIGN FOR A MULTIDIMENSIONAL SYSTEM OF ORDINARY DIFFERENTIAL EQUATIONS WITH RELAY HYSTERESIS AND PERTURBATION

A multidimensional controllable system with a constant matrix, a significant nonlinearity of the twoposition relay type with hysteresis as a control and a continuous periodic perturbation function is considered. The system matrix has simple, real, non-zero eigenvalues, among which one can be positive. Conditions for the system parameters, including the nonlinearity ones, are established under which there is a single two-point oscillatory periodic solution with a period comparable to the period of the perturbation function in the case of a special type of the feedback vector. The asymptotic stability of the solution has been proven using the phase plane method. The results obtained are illustrated by examples for three-dimensional systems.

SOLUTION OF THE SPECTRUM ALLOCATION PROBLEM FOR A LINEAR CONTROL SYSTEM WITH CLOSED FEEDBACK

The method for constructing a feedback matrix to solve the problem spectrum allocation (spectrum control, pole assignment) for linear dynamic system is given. A new proof of the well-known theorem about the connection between the complete controllability of a dynamic system with existence of the feedback matrix is formed in the process of construction by the cascade decomposition method. The entire set of arbitrary elements that influence the non-uniqueness of the matrix is identified. Examples of constructing a feedback matrix in the case of a real spectrum and in the presence of complex conjugate eigenvalues, as well as for the case of multiple eigenvalues, are given. The stability of the specified spectrum under small perturbations of the system parameters with a fixed feedback matrix is studied.

The Structural Design and Analysis of the Multi Nozzle Relay Air-Jet Inserting System by Profile Reed Guiding for 3D Weaving Machine

Introduction: Based on the literature, this article designs a parameterized simulation model of a multi-layer jet weft insertion system by profiles reed guidance for a 3D loom on the PTC Creo9.0 platform, including the main supersonic nozzle, supersonic auxiliary nozzle (relay nozzle), and multi-slot profiles reed components. Method: Based on the existing basic theory, experimental results, and empirical data of turbulent jet, the parameters of the multi-layer jet weft insertion system, as well as the structural parameters and the relative positions of the main, auxiliary nozzle and profile reed components, such as the center distance of each layer's main nozzle, auxiliary nozzle spacing, auxiliary nozzle installation angle, spray direction angle, and spray angle, have been determined preliminarily. Result: Further, the basic flow field parameters, such as the supply pressure of the main and auxiliary nozzles and the shape of multi-layer profile reeds, have been determined optimally on the Virtual Prototype Collaborative Simulation Platform (PTC Creo9.0/ANSYS Workbench/Fluent 2024R1), and the rationality of the structural design also been verified; on the premise of ensuring that the airflow velocity of each layer's profiles groove meets the requirements of weft insertion, the design and simulation calculation is repeatedly modified, and the optimal structural design parameters of the multi-layer weft insertion system and nozzle is finally determined. Conclusion: To explore the feasibility of multi-layer jet weft insertion, the design of threedimensional multi-layer jet weft insertion looms has laid a theoretical foundation, laying a good foundation for the emergence and industrial manufacturing of three-dimensional multi-layer jet weft insertion looms, and providing an important reference for the innovative design of threedimensional multi-layer water jet weft insertion looms.

Особенности системы гемостаза при истинной полицитемии у детей

Patients with polycythemia vera (PV) are at an increased risk for thrombosis. Abnormalities in coagulation parameters and global hemostasis tests can help with hypercoagulation recognition in PV. The purpose of this research was to analyze the features of changes in laboratory parameters of the hemostasis system in pediatric patients with PV. Materials and methods used: a single-center retrospective cohort study of clinical records of 32 (11 (35%) girls/21 (65%) boys aged 11.5 [0.8; 17.5] y/o) pediatric (all under the age of 18 y/o) PV patients who were admitted at the National Scientific and Practical Center for Pediatric Hematology, Oncology and Immunology named after Dmitry Rogachev (Moscow, Russia) in Jan. 2012-June 2024 was conducted. Laboratory parameters were determined prior to the beginning of the antiplatelet and cytoreductive therapy. Results: in 20 (62.5%) and 4 (12.5%) patients, mutations in the JAK2V617F and JAK2 ex 12 genes were detected, respectively, the remaining 8 (25%) children were JAK2-negative. In total, there were 8 (72%) JAK2-positive girls and 15 (71%) boys; gender did not statistically significantly affect the presence of a driver mutation (p=0.939). Both the median and the mean values of the main parameters of the blood coagulation system were within the reference values. The thromboelastography parameters did not deviate from the reference values for the parameters. According to the results of the thrombodynamics study, the average value of the initial clot growth rate among all patients was increased and amounted to 58.3±5.07 μm/min, the steady-state velocity also increased among all patients to 29.5±4.3 μm/min, the median and the mean values of the remaining parameters were within the reference intervals. Conclusion: the parameters of standard coagulogram and thromboelastography tests in pediatric PV patients had no deviations. The average values of thrombodynamics (initial and steady-state clot growth rate) were increased, which potentially indicates the hypercoagulation.

Cardiorespiratory system of massage therapists when performing a dosed massage procedure

The article tells about the presentation of a number of studies on the effect of massage procedures on the physiological, biochemical and psychological status of a person, while work on evaluating the functional indicators of massage therapists during the procedure is rare. The study aims to determine the functional state of the cardiorespiratory system (CRS) of massage specialists in the dynamics of performing a 30-minute back massage session. The object of the study was 10 male massage therapists (age 36.0 (29.0;42.0); BMI 24.7(23.3;31.3). The study consisted in performing a classical back massage procedure for 30 minutes according to a generally accepted technique using six massage techniques. To determine the functional state during the work of specialists, an ergospirometric system and measurement of blood pressure (BP) by the Korotkiy method were used. During the massage procedure, specialists noted an increase in metabolic parameters, oxygen consumption (OC), respiratory coefficient (RC) and energy consumption, as well as blood pressure by the 30th minute of the procedure. When performing a 30-minute back massage, massage specialists significantly mobilize the links of the cardiorespiratory system. At the end of the procedure, there is an increase in blood pressure. However, the maximum increase in the parameters of the cardiorespiratory system occurs when performing a shock vibration reception. Limitations. Due to the small sample of the group, it is not possible to statistically reliably assess the significance of changes in some indicators. Ethics. The protocol of the experiment corresponded to the Helsinki Declaration. The study was developed and conducted in accordance with the methodological guidelines of the Local Scientific Research Committee on Bioethics of the Institute of Physiology of the Komi Scientific Center of the Ural Branch of the Russian Academy of Sciences.

Mechanical Analysis and Function Matrix Projective Synchronization of El-Nino Chaotic System

Abstract This study explores the mechanical aspects of the El Niño system by transforming it into a Kolmogorov type system, characterized by four types of torques known as internal, inertial, dissipation, and external. Five scenarios by varying these torques to identify the factors that lead to chaos and their physical significance are also investigated. The interactions between kinetic, potential, and Hamiltonian energies are analyzed and depicted as how these energies interact with system parameters. The study also emphasizes the benefits of conservative chaos over dissipative chaos. Particularly, it has more applications like secure communications and pseudo-random number generation. The role of force interactions and exchanges, including Casimir energy in the generation of chaos is also identified. The transition from regular to irregular orbits, and then to more chaotic states is investigated through Casimir function. It concludes that all four types of torques are necessary to induce chaos in the El Niño chaotic system. Additionally, function matrix projective synchronization between identical El-Nino chaotic systems has achieved.

Explore the operational performance of phase change radiation terminal heating system in different heating zones of China

IntroductionHeating is one of the main factors leading to high energy consumption and serious carbon emissions in buildings. The clean heating system formed by the coupling of phase change building maintenance structure and solar heating system can improve the thermal storage density of the building maintenance structure, while reducing energy consumption in winter while maintaining a comfortable room temperature through stable energy security.MethodsTherefore, a phase change radiation terminal heating (PCRTH) system with the phase change radiation module as the terminal and the solar energy and air energy as the clean heat source is established in this study. Nanjing, Tianjin and Shenyang in China were selected as the study zones which correspond to the hot summer and cold winter zone, the cold zone and the severe cold zone respectively. The operational effect of the PCRTH system in different climate zones was studied, and the parameters of the PCRTH system were optimized by the GenOpt program combined with Hooke-Jeeves optimization algorithm.ResultsThe analysis results show that the cascade phase change radiation terminals in the three zones reduced room temperature fluctuation, energy consumption and carbon dioxide emissions, but the heating cost was higher. After the Hooke-Jeeves optimization algorithm was used to optimize the PCRTH system parameters in three zones, the PCRTH system heating cost was reduced, and the PCRTH system energy consumption and PCRTH system carbon dioxide emissions were further reduced.DiscussionTherefore, the building heating system composed of PCM maintenance structure and renewable energy has great application advantages in maintaining a comfortable room temperature and improving heating system energy conservation and environmental protection.

System identification-based tuning of PID algorithm parameters by using PSO and genetic algorithms

The PID control algorithm is the most used industrial control method. This is due to its simplicity, ease of use, and because it yields stable results. PID parameters vary for each controller; therefore, finding the optimal parameters is crucial for obtaining good results. However, tuning PID parameters for complex systems is not a trivial task and is also somewhat difficult as conventional techniques rely on time and effort manual tuning or rely on simplified statistical estimation techniques of the system’s model yielding sub- optimal results. In this project, we propose to use machine learning for PID parameter tuning on proprietary historical time series operating process control data. The data is processed with the help of computational and machine-learning techniques to better identify the process model and predict the optimal PID parameters. The research methodology consists of three main steps. First, process-model identification is done by using a Radial Basis Function (RBF) neural network. Secondly, Particle Swarm Optimization (PSO) hybrid with Genetic Algorithms (GA) is used for finding the optimal PID parameters. The PID values predicted by PSO, will be fed to GA optimization process as an initial starting point. The final step consists of integrating the identified process model with the PID optimization algorithm in a computer-based simulation environment (Simulink). The experimental simulations are done for various study cases. Results showed that the predicted PID parameters error rate and standard deviation for PID control and process are decreased, which enhances the process controlling and stability.

Adaptive Approach for Power Oscillation Damping using STATCOM

In this paper we had described the designing of a Power Oscillation Damping (POD) controller for a Static Synchronous Compensator (STATCOM) equipped with Energy Storage System (ESS). Various adaptive techniques like fuzzy logic controller, PID controller, algorithm, etc. can be employed to achieve this allowing a fast and adaptive approximation of the low-frequency electromechanical oscillations from locally measured signals during power system disturbances. We developed an approach using variable DC voltage control and constant modulation index method; which are effective in increasing the damping of the system at the concerned frequencies and in case of system parameter uncertainties. A control policy that optimizes active and reactive power inoculation at various connection points of the STATCOM is derived using the simplified model in MATLAB Simulink using impower system toolbox. Signal analysis of the dynamic performance of the proposed control strategy is carried out. To verify the effectiveness of the proposed control method, we carried out simulations and found that the approach provides oscillation damping irrespective of the connection point of the device and also in the presence of system parameter uncertainties.

Macroeconomic Policy, Wage Gap and Asset Prices: A Dynamic Dependent Economy Model

The role of financial sector in general and macroeconomic policy in particular is a crucial issue in the study of macroeconomic behaviour of developing countries. This article addresses this issue in terms of a dynamic dependent economy model consisting of traded and non-traded sectors. We use perfect foresight and focus on wage gap between skilled and unskilled labour along with unemployment and movement of asset prices. Based on the structure of the model we examine multitude of transmission mechanisms with implications of monetary policy and decrease in oil subsidy. The several cross effects induced by change in system of parameters have their profound bearing on exchange rate, Tobin’s q, wage gap, level of employment and the sectoral composition output. JEL Codes: E31, E63, F32, F41

The GAPS programme at TNG. LXVI. A homogeneous search for Na I and its possible variability in ten gas giant exoplanets

The neutral sodium resonance doublet ( Na I D) has been detected in the upper atmosphere of several close-in gas giants, through high-resolution transmission spectroscopy. We aim to investigate whether its variability is linked to the planets' properties, the data quality, or the accuracy of the system parameters used. Using the public code SLOPpy we extracted the transmission spectrum in the Na I D region of ten gas giants for which a large number of HARPS-N observations are available. We modelled the absorption signals found, performing an MCMC analysis, and converted the measured absorption depth to the corresponding atmospheric height over which most sodium absorption occurs. While two targets (GJ 436 b and KELT-7 b) show no Na I D feature, we found variability in the transmission spectrum of the other targets. Three of them (HD 209458 b, WASP-80 b, and WASP-127 b) present absorption on only some nights, while in the other five targets (HD 189733 b, KELT-9 b, KELT-20 b, WASP-69 b, and WASP-76 b), a significant absorption signal is present on most of the nights analysed. Except for WASP-69 b, the measured absorption depths lead to a ratio of the two Na I D depths that is compatible with or slightly larger than one. As was expected from literature, the relative atmospheric height follows an empirical exponential trend as a function of a scaled product of the planet's equilibrium temperature and surface gravity. We confirm the sodium detection on HD 189733 b, KELT-9 b, KELT-20 b, WASP-69 b, and WASP-76 b. The signal detected in WASP-127 b requires further observations for definitive confirmation. We exclude a planetary origin for the signals found on HD 209458 b and WASP-80 b. The sodium absorption variability does not appear to be related to planetary properties, but rather to data quality, sub-optimal data treatment, or stellar activity.

Exploring epidemics using non-monotonic incidence function: Effects of sociological factors and hospital bed availability

This study investigates the dynamics of an epidemic employing an (Susceptible-Infected-Hospitalized-Recovered-Susceptible (SIHRS) epidemiological model highlighting the crucial importance of hospital bed availability and a non-monotone incidence function, which incorporates the influences of stringent governmental measures, social behavior dynamics and public responses in both autonomous and non-autonomous scenarios. The analysis investigates the conditions for existence of infection-free and endemic steady states based on the basic reproduction number as it surpasses unity. Sensitivity analysis has been conducted to evaluate the impact of different system parameters on disease transmission. This work also investigates alterations in stability of the system caused by transcritical, Hopf and saddle-node bifurcations. Additionally, two-parameter bifurcation identifies the regions where the stability of both the equilibrium points has been examined. Numerical simulations are shown to illustrate all the theoretically obtained results. Also, the model examines the dynamical behavior of the epidemic when the quantity of available hospital beds varies periodically. This aspect of the study highlights the significant impact of hospital bed availability. Such factors are crucial in preventing disease spread during an epidemic. The results provide valuable insights into how dynamic patterns of disease transmission are influenced by healthcare infrastructure and public health interventions. This comprehensive exploration underscores the importance of integrated approaches combining medical resources and societal measures in managing and mitigating the effects of epidemics.

Shape Optimization of an Industrial Aeroengine Combustor to reduce Thermoacoustic Instability

Abstract We parameterize the geometry of an industrial aeroengine combustor using Free Form Deformation (FFD). We then define the thermoacoustic system parameters and impose the acoustic boundary conditions to calculate the thermoacoustic eigenmode of the model using an open source parallelized Helmholtz solver. We then use adjoint methods to calculate the shape derivatives of the unstable eigenvalue with respect to the shape parameters. First we calculate the sensitivities with respect to surface movements. Second, we calculate the sensitivities with respect to the FFD control points. We modify the FFD control point positions in order to reduce the thermoacoustic growth rate until the mode considered is stable. These findings show how, when combined with other constraints, this method could be used to reduce combustion instability in industrial annular combustors through geometric modifications.

Advanced beamforming and reflection control in intelligent reflecting surfaces with integrated channel estimation

AbstractIntelligent Reflecting Surfaces (IRS) enhance wireless communication by optimising signal reflection from the base station (BS) towards users. The passive nature of IRS components makes tuning phase shifters difficult and direct channel measurement problematic. This study presents a machine learning framework that directly maximises the beamformers at the BS and the reflective coefficients at the IRS, bypassing conventional methods that estimate channels before optimising system parameters. This is achieved by mapping incoming pilot signals and data, including user positions, with a deep neural network (DNN), guiding an optimal setup. User interactions are captured using a permutation‐invariant graph neural network (GNN) architecture. Simulation results show that implicit channel estimation method requires fewer pilots than standard approaches, effectively learns to optimise sum rate or minimum‐rate targets, and generalises well. Specifically, the sum rate for GDNNet (GNN + DNN) improves by over linear minimum mean square error (LMMSE) and by over perfect CSI concerning the number of users, and by over LMMSE and by over perfect CSI concerning pilot length. Offering a feasible solution with reduced computing complexity for real‐world applications, the proposed GNN + DNN method outperforms conventional model‐based techniques such as LMMSE and approaches the performance of perfect CSI, demonstrating its high effectiveness in various scenarios.

System to Assist the Driver During a Single Lane Change Maneuver, in the Conditions of Danger Arising from a Change in the Condition of the Road Surface

The article describes the application of a vehicle simulation model to assess the driving hazards that arise due to changes in the tyre–road adhesion during a lane change. An experimentally verified vehicle dynamics model was used. The typical single lane change maneuver, performed on dry concrete, wet concrete, and ice-covered roads, was simulated for three vehicle speeds. The disturbance was introduced as a changed tyre–road adhesion on the target lane. Typical sinusoidal (one-period) input was applied to the steering wheel. Adhesion change may lead to an accident when considering the driver’s reaction time. An original control algorithm has been built. It is the driver assistance system with a double PID controller of the steering wheel angle. The system parameters were determined based on the principles recommended in the automatic control engineering monographs. The controller fulfils its tasks for motion at very high speeds on a homogeneous road surface and for the case where the tyre–road adhesion is changed during a maneuver. Thanks to this, the threat can be avoided.

Nonlinear Dynamics of Whirling Rotor with Asymmetrically Supported Snubber Ring

Rotor–stator whirling is a critical malfunction frequently encountered in rotating machinery, often resulting in severe damages. This study investigates the nonlinear dynamics of a whirling rotor interacting with a snubber ring through numerical simulations that account for the stiffness asymmetries of the snubber ring. A two-degrees-of-freedom (DOF) model is employed to analyse the contact interactions that occurred between the rotor and the snubber ring, assuming a linear elastic contact model. The analysis also incorporates the static offset between the centers of the rotor and the snubber ring. The dynamic behaviour of the whirling system is characterised by pronounced nonlinearity due to transitions between contact and non-contact states. The model is first validated against our prior theoretical and experimental studies. The nonlinear responses of the rotor are analysed to evaluate the effects of stator asymmetry through various techniques, including time-domain waveforms, frequency spectra, rotor orbits, and bifurcation diagrams. Furthermore, the influence of varying system parameters, such as rotational speed and the damping ratio, both with and without stator asymmetry, are systematically analysed. The results demonstrate that the rubbing response is highly sensitive to small variations in system parameters, with stator asymmetry significantly affecting system behaviour, even at low asymmetry levels. Direct stiffness asymmetry is shown to have a more pronounced effect than cross-coupling stiffness. The system exhibits a range of dynamics, including periodic, quasi-periodic, and chaotic responses, with regions of periodic orbits coexisting with chaotic ones. Complex phenomena such as period doubling, period halving, and jump bifurcations are identified, alongside quasi-periodic and period doubling routes to chaos. These findings contribute to a deeper understanding of the nonlinear phenomena associated with rotor–stator whirling and provide valuable insights into the unique characteristics of rubbing faults, which could facilitate fault diagnosis.

Adaptive Dynamic Thresholding Method for Fault Detection in Diesel Engine Lubrication Systems

Fault detection in marine diesel engine lubrication systems is crucial for ensuring the long-term stable operation of diesel engines and the safety of maritime navigation. Traditional fixed-parameter alarm threshold methods lack flexibility and are prone to missing faults. Data-driven approaches like machine learning require high-quality data for fault samples. This study leverages the relative advantages of data mining methods and threshold techniques, proposing an adaptive threshold construction method based on dynamic parameter relationship inference. Employing an algorithm for inferring dynamic relationships among multiple parameters of the lubrication system builds an adaptive threshold detection model. Extensive diesel engine tests and actual fault data demonstrate that the proposed method can address the issues of missed faults encountered by static threshold methods and the low detection accuracy of machine learning approaches without the need for fault samples. This significantly enhances fault detection accuracy in marine diesel engine lubrication systems, offering considerable industrial practical value.

The Effect of Adding Generation Bus to the Short Circuit Current Level in Electrical Power System

The need for electrical energy is changing and increasing, requiring system flexibility always to be changed and developed. On the other hand, changes in the configuration of the electric power system due to the addition of components or sub-systems also change system parameters such as impedance or level of fault current (short circuit current). This paper presents a study of changes in the fault current caused by adding a new generating bus to an electric power system. This paper aims to determine the change in short-circuit current due to the addition of generators on new buses connected to existing buses to identify the most suitable location for adding these generators based on short-circuit current levels. Three-phase short circuit faults are simulated and analyzed on the IEEE 14 bus standard system using ETAP software with a base MVA 615 MVA. The addition of generators was carried out at five locations with varying generating capacities. The research results show that the short circuit current will change significantly when adding a generator bus to bus 13, with an average percentage change of 5,656%. The smallest change occurs when adding a generator to bus 2, with an average percentage change of 2,417%. The research results conclude that connecting a generator to a new bus linked to an existing generator bus (PV bus) is more effective than connecting it to a new bus associated with a load bus (PQ bus).

Predicting multi-parametric dynamics of an externally forced oscillator using reservoir computing and minimal data

AbstractMechanical systems exhibit complex dynamical behavior from harmonic oscillations to chaotic motion. The dynamics undergo qualitative changes due to changes to internal system parameters like stiffness and changes to external forcing. Mapping out complete bifurcation diagrams numerically or experimentally is resource-consuming, or even infeasible. This study uses a data-driven approach to investigate how bifurcations can be learned from a few system response measurements. Particularly, the concept of reservoir computing (RC) is employed. As proof of concept, a minimal training dataset under the resource constraint problem of a Duffing oscillator with harmonic external forcing is provided as training data. Our results indicate that the RC not only learns to represent the system dynamics for the external forcing seen during training, but it also provides qualitatively accurate and robust system response predictions for completely unknown multi-parameter regimes outside the training data. Particularly, while being trained solely on regular period-2 cycle dynamics, the proposed framework correctly predicts higher-order periodic and even chaotic dynamics for out-of-distribution forcing signals.

Outage Probability Analysis and Altitude Optimization of a UAV-Enabled Triple-Hop Mixed RF-FSO-Based Wireless Communication System

In this paper, we present the evaluation of network parameters for the unmanned aerial vehicle (UAV)-enabled triple-hop mixed RF/FSO-based wireless communication system, where one relay is a fixed relay and the second relay is a UAV which acts as decode-and-forward relay for communication from the base station (B) to the multiple mobile users (Mi), i∈{1,2⋯N}. The first hop from B to fixed relay (R1) is the radio frequency (RF) link modeled using α−κ−μ fading distribution, the second hop from the relay R1 to the UAV relay (R2) is a free space optics (FSO) link modeled using Gamma-Gamma fading, and the third hop from R2 to the Mi is, again, an RF link modeled using the Rayleigh fading model. The direct communication between the B and the Mi is not feasible due to the very large distance. We derive the closed form analytical expression for the outage probability of the proposed system and find the effect of the base system parameters on the performance of the system. We also analyze the outage probability of the system at high SNR values to get further insights of the system performance. In addition, altitude optimization of UAV is carried out to know the optimal elevation angle in correspondence with UAV’s optimal altitude in order to maximize performance of the system.