Disturbance Model Research Articles

Coupling Disturbance Modeling and Compensation for Aerial Manipulator in Highly Dynamic Motion.

When a manipulator moves in a highly dynamic scenario with a large range of rapid motion, the coupling disturbances between the manipulator and the UAV in the aerial manipulator system (AMS) become very strong, which directly affects the ability of the AMS to perform aerial manipulation and even poses a threat to the safety of the system. The aim of this article is to address the strong coupling disturbance problem in the AMS through precise coupling disturbance modeling and compensation. First, considering the rapid changes in the center of mass (CoM) and the moment of inertia (MoI) of the system under a highly dynamic scenario, this article delves into the generation mechanism of the coupling disturbances and models them based on the variable inertia parameters. The proposed precise coupling disturbance model (CDM) makes good use of the state information of the system, which enables one to achieve accurate estimation of the coupling disturbances without the aid of external force and torque sensors. With the proposed model, the strong coupling disturbances in the AMS are compensated in a feedforward way during the controller design process. An indoor AMS experimental platform is developed for validation purposes. The experiments and simulation are conducted in a highly dynamic scenario, involving rapid movements of the manipulator across a large range. The experimental and simulation results demonstrate the effectiveness and advantages of the proposed method for suppressing the strong coupling disturbances.

Estimation of the helicity of atmospheric disturbances caused by gravity field inhomogeneities

The helicity of atmospheric disturbances caused by inhomogeneities in the gravity field is theoretically estimated. For this purpose, a three-dimensional stationary analytical model of linear disturbances introduced by spatial inhomogeneities of the gravity field into the background geostrophic flow of a stratified rotating medium (atmosphere) was used. From the solution found, it follows that in highly anomalous regions the amplitude of the helicity of emerging disturbances can be noticeable.

Auto-tuning of filtered proportional-integral-derivative controller for industrial processes under routine operating conditions.

In general, auto-tuning implementation of PID controllers relies on dual controllers, exciting/identification experiments or some prior knowledge on the process and hence the considerable cost on auto-tuning implementation occurs. To deal with such a problem, a new auto-tuning scheme of the FPID controller is developed for minimum variance tasks under routine operating conditions in which the closed-loop system is running without any external excitation other than natural disturbances. This paper reveals that the stochastic disturbance model can be uniquely determined from the first several terms of the impulse response coefficients of the closed-loop system when the precondition on the time delay and the order of the disturbance model is satisfied. Based on the closed-loop non-parametric model (in terms of impulse response coefficients) that is estimated online by utilizing the one-shot closed-loop output data, the disturbance model is estimated by solving an optimization problem and hence the plant model is obtained. Subsequently, the new parameter set of the FPID controller is updated online by solving an optimization problem with respect to the H2 norm of the resulting closed-loop transfer function. The benefit of the proposed scheme over the existing auto-tuning methods is the cost saving of the auto-tuning implementation due to the following facts: i) it does not rely on dual controllers or identification/exciting experiments; ii) it does not require prior knowledge of the process. The effectiveness of the proposed scheme is illustrated in terms of output variance index by numerical cases and industrial examples.

Research on Bolt-grouting Reinforcement Technology of Broken Surrounding Rock in Roof of Multiple Disturbance Bottom Drainage Roadway

The coal seam floor layout bottom drainage roadway is one of the effective means of gas outburst elimination in the working face. However, the roof surrounding rock of the bottom drainage roadway will undergo multiple disturbances such as bottom drainage roadway excavation, drilling excavation, roadway excavation and working face mining, which will easily lead to large deformation of the surrounding rock of the bottom drainage roadway, which will greatly affect the safety and stability of the bottom drainage roadway and the safety of the mine. In this process, the fracture of the borehole wall of the extraction borehole expands, and it is subjected to severe dynamic pressure during roadway excavation and working face mining. At the same time, the redistribution of surrounding rock stress brings secondary damage, which will lead to the increase of roof deformation. Based on the maintenance of the roof surrounding rock of the bottom suction roadway in the 14020 working face of Zhaogu No.2 Coal Mine, aiming at the problems of local large deformation of the roof surrounding rock of the bottom suction roadway and the difficulty in maintaining the roadway caused by the mine pressure appearance, in order to reduce the roof disturbance of the bottom suction roadway and strengthen the roof support, the indoor test, numerical simulation, theoretical analysis and industrial test are used to carry out the research on the deformation law of the roof surrounding rock of the bottom suction roadway and the bolt grouting reinforcement technology. A numerical calculation model of multiple disturbances in the bottom drainage roadway considering the construction of drainage boreholes was established. The causes of deformation and failure of the roof of the bottom drainage roadway were analyzed, and the supporting parameters and techniques were improved. The timing and support scheme of the test roadway support ( reinforcement technology ) were determined. Under the condition of high strength support, the influence law of bottom pumping roadway excavation, drilling excavation, roadway excavation and working face mining on the deformation degree of roof surrounding rock is revealed. The active reinforcement technology of bolt-grouting for surrounding rock of test roadway is put forward and applied in the field. According to the feedback of the on-site mine pressure monitoring results, the roof deformation degree of the test roadway after excavation and mining is small, and the roadway section meets the production demand, which verifies the feasibility of the bolt-grouting reinforcement technology.

Continuation of Fixed Points and Bifurcations from ODE to Flow-Kick Disturbance Models

Continuation of Fixed Points and Bifurcations from ODE to Flow-Kick Disturbance Models

A refined prediction model for the initial disturbances of the projectile in the self-propelled gun

Abstract In the gun launch process, the continuous propellant combustion provides power and energy for the projectile. Due to the gap between the projectile and barrel, the high-speed motion of the former is generally accompanied by contact and collision with the latter. Meanwhile, the gun also recoils under the propellant gas. Notably, the above complex motion of the system causes the initial disturbances of the projectile and muzzle. Previous launch dynamic models usually neglect the influence of the gun recoil on the combustion and flow in the chamber. However, the gun recoil inevitably further increases the chamber’s free space, resulting in the calculation deviations of projectile and muzzle disturbances. The above deviations ultimately determine the firing accuracy and firing stability prediction. To study the in-bore projectile motion and subsequent external ballistic process more accurately, an improved coupled calculation method of launch dynamics is developed. This work combines the interior ballistic two-phase flow dynamics considering the gun recoil, in-bore projectile motion theory, multibody system dynamics, and necessary high-precision numerical schemes. The launch process of the 155 mm self-propelled gun is studied. As the results show, the calculated vibration characteristics, dynamic response, and interior ballistic performance indexes are consistent with measured ones, verifying the feasibility of the above method. In addition, the initial disturbances of the projectile with and without considering the recoil’s influence on the combustion and flow in the chamber is discussed. The work in this paper provides an accurate tool to predict the initial disturbances of the projectile.

Event-Triggered Adaptive Antidisturbance Switching Control for Switched Systems With Dynamic Neural Network Disturbance Modeling.

In this article, a dynamic event-triggered adaptive antidisturbance (ETAAD) switching control strategy is proposed for switched systems subject to multisource disturbances. The disturbances are divided into two categories: the available unmodeled disturbance and the unavailable dynamic neural network modeled disturbance. First, a dynamic ET criterion is set based on the system state. Then, a novel dynamic ETA disturbance estimator is introduced to observe the modeled disturbance. Furthermore, according to the ET rule and adaptive disturbance observer, a switched controller is designed. Next, under the controller and switching criterion with the average dwell time limitation, sufficient conditions are given to force the switched systems to realize multisource disturbance suppression (DS), trajectory tracking, and communication resource (CR) saving simultaneously. Meanwhile, the Zeno phenomenon may be caused by the ET rule being excluded. In addition, the presented ETAAD approach is also applicable to the nonswitched systems case. Finally, a simulation case is given to validate the effectiveness of the dynamic ETAAD switching control method.

Dynamic Characteristic Analysis of Multi-Virtual Synchronous Generator Systems Considering Line Impedance in Multi-Node Microgrid

With the increasing integration of distributed energy resources into modern power systems, virtual synchronous generators (VSGs) have been a promising approach to imitate the inertial response of synchronous generators, thereby enhancing microgrid stability in a dynamic state. When many VSGs are integrated into microgrids, the dynamic characteristics of the system become increasingly complex. Current studies typically assume that different VSGs are connected to a common coupling point, focusing on analyzing the interaction characteristics, which may overlook the widely distributed line impedances in microgrids with distance between different facilities. This may lead to incomplete understanding of the interaction dynamics when VSGs are distributed over long feeder lines. Therefore, this paper proposes and investigates a multi-node, multi-VSG model incorporating line impedances among different nodes, establishing transfer function models for multi-node load disturbances and the frequency responses of individual VSGs. The study explores the dynamic response characteristics of VSGs under varying parameter influences and proposes principles for designing VSG port impedance and inertia parameters to optimize system dynamic frequency characteristics. The findings, validated through simulations in PSCAD v46, provide insights for enhancing the flexibility and reliability of grids incorporating VSGs.

Variable-structure trajectory correction control of small-caliber ammunition based on cascade fuzzy active disturbance rejection

In this study, a low-cost two-dimensional (2D) trajectory correction mechanism is proposed to address the large trajectory deviation of small-caliber extended-range ammunitions. By controlling the projectile’s roll, a single-channel 2D trajectory correction function can be realized. Moreover, based on the ideal trajectory, a five-degree-of-freedom approximate rigid-body trajectory equation is proposed. A high-order system is transformed into two low-order cascading subsystems using fuzzy control and the self-disturbance rejection control theory, which reduces the parameter tuning complexity. The entire control process is divided into three stages which realizes the second-order variable structure control of non-affine nonlinear subsystems. A low-altitude atmospheric disturbance model is established, and as an example, numerical calculations are performed on the control process and projectile impact point dispersion of a 35 mm small-caliber rocket. The results verify the performance of the proposed trajectory correction under atmospheric disturbances. This study provides a control approach for coupled underactuated nonlinear systems and provides guidance for the design of a low-cost 2D trajectory correction controller for small-caliber ammunitions.

Contrasting forest management strategies: Impacts on biodiversity and ecosystem services under changing climate and disturbance regimes

Natural disturbances may compromise the past and ongoing efforts to increase carbon sequestration and halt biodiversity loss in boreal forests. Measures to minimize the effects of forest disturbances i.e., adaptive management, offer solutions to secure future timber yields. However, the consequences of adaptive management on biodiversity, the climate change mitigation potential of forests, and other ecosystem services are not well understood. In addition, the impact of climate change and disturbances on future forest-based mitigation potential is not well known. We compared the effects of forest management options emphasizing climate change mitigation or adaptation on boreal forests in changing climate and disturbance regimes in southern Finland. We used the process-based forest landscape and disturbance model iLand to dynamically model interactions between climate change and disturbances together with forest management and protection options, and examined the consequent effects on forest carbon storage, berry yields, recreation, and structural attributes important for biodiversity. Mitigation managements resulted in up to one-fifth higher carbon stocks, even after accounting for disturbances by wind and bark beetles, but halved annual harvests over the 80-year simulation period. Adaptive managements reduced bark beetle disturbances, but in some cases the disturbed volumes were even higher than under business-as-usual management due to increased wind damage. The effects of proactive risk management depended on the time horizon considered, the adaptive management option chosen and the climate change scenario. In general, the mitigation managements had positive effects on the biodiversity indicators studied, while the effects of adaptive management were mixed. Our results highlight the complex interactions between disturbance risk prevention, biodiversity, carbon sequestration and storage, and other ecosystem services. The results guide forest managers and policymakers to plan mitigation and adaptation strategies optimizing multiple benefits, and strengthening forest resilience in a changing climate.

The effect of time-varying characteristics of shallow-sea waveguides on low-frequency acoustic signal transmission

The time-varying characteristic of shallow sea channel plays one of the most important role in the exploration of ocean. However, there is still lack of estimation model to describe the time-varying characteristics of shallow water low-frequency acoustic channels. This paper proposes a low-frequency channel model based on wave equation and ray theory to estimate the time-varying characteristics of shallow sea. Firstly, for the actual characteristics of shallow sea, suitable boundary conditions are designed to solve the wave equation. Secondly, the constraint conditions of shallow sea wave equation are optimized by combining ray theory. Then, based on the physical characteristics of shallow sea, time-delay variation and phase variation are solved by shallow wave equation. Combining bellhop propagation model with ocean disturbance model, the simulation is designed to verify the time-varying characteristic model of low-frequency shallow sea in this paper. Finally, with different propagation distance measurement experiment of sea, estimation value of time-delay variation and phase variation are confirmed, which is significant to shallow sea channel.

An Open-Source Julia Package for RMS Time-Domain Simulations of Power Systems

This paper presents RMSPowerSims.jl, an open-source Julia package for the time-domain simulation of power systems. The package is designed to be used in conjunction with PowerModels.jl, a widely used Julia package for power system optimization. RMSPowerSims.jl provides a framework for the simulation of power systems in the time domain, allowing for the study of transient stability, frequency stability, and other dynamic phenomena. The package is designed to be intuitive and flexible, allowing users to easily define custom models for network components and disturbances, while also providing a range of pre-constructed models for common power system components. RMSPowerSims.jl simplifies the process of performing RMS simulations on power system models developed using the PowerModels.jl ecosystem, and provides an easy-to-use modeling that reduces the barrier to entry for new users wishing to perform RMS simulations. The accuracy of the package is verified against DIgSILENT PowerFactory for short-circuit and load-increase disturbances, using the New England 39-bus system. The active power generation delivered by several generators in the network, and the voltage magnitudes of selected busbars are analyzed and noted to be in close agreement with those obtained using PowerFactory. The computational performance of the package is compared to that of PowerFactory and is found to be comparable for load-step simulations; however, PowerFactory is found to be considerably faster for short-circuit simulations. As computational performance is not a priority at this stage of development, this is expected, and speed optimization is planned for future work. RMSPowerSims.jl is available under an open-source license and can be downloaded from GitHub.

The Study of the State of Monoaminergic Systems in the Brain Structures of the Offsprings of Female BALB/C Mice at Different Stages of Formation of Autism Spectrum Disorders

The study of the status of norepinephrine-, dopamine- and serotonergic neurotransmitter systems of BALB/C mice brain structures on 15 and 64 days of postnatal development (PD) in the model of autistic disturbances induced by injection of of sodium valproate (SV, 400 mg/kg, s/c) to pregnant females was carried out using the HPLC/ED method. The level of both catechol- and indolamines in the brain structures of control group mice at the age of 15 days was significantly lower than in adult animals at the age of 64 days. Prenatal administration of SV caused a decrease in all parameters of monoaminergic neurotransmission in the striatum of offspring at the age of 15 days, but had no effect in other brain structures studied. Subsequently, the level of dopamine increased and by the 64th day of PD did not differ from the parameters of the control group. The parameters of the serotonergic system changed in a similar pattern, with the content of serotonin and the serotonin metabolite 5-OIAA in the striatum increasing gradually and reaching maximum values by the 64th day of PR. Our data allows to assume that the administration of SV to pregnant females affects the activity of the dopamine and serotonergic systems of the brain of the offspring, causing a decrease in their activity in the striatum by the 15th day of pregnancy, followed by restoration to control values by the 64th day, which we previously observed in male pups. Thus, the patterns of dynamic changes in the neurochemical profile do not differ between males and females.

Adaptive RBF iterative learning tracking control of multi-degree-of-freedom manipulators

Abstract Targeting on the issue of poor dynamic performance of multi-degree-of-freedom manipulator system under disturbance environment and model parameter uncertainty, this paper designs an adaptive iterative learning tracking control method utilizing a radial basis function (RBF) neural network observer, aiming at realizing stable control and disturbance suppression of closed-loop system. The controller consists of the proportional-differential term based on the backstepping method, the sign function robust term of adaptive sliding mode, and the disturbance observation term of the RBF neural network. The sign function robust term compensates for the repetitive disturbance of the system, and the RBF observer compensates for the non-repetitive disturbance of the system. Under the premise of ensuring the normal functioning of the control system, the sliding mode parameter is updated in the iterative domain, and the RBF network weight parameter is updated in the time domain to enhance the system’s robustness. Simultaneously, the stability of the closed-loop system within the iterative domain and the convergence of the tracking error are demonstrated using the Lyapunov composite energy theory. Finally, the proposed control method’s efficacy and robustness are validated through simulation and experiment.

Robust Driving Control Design for Precise Positional Motions of Permanent Magnet Synchronous Motor Driven Rotary Machines with Position-Dependent Periodic Disturbances

Position-dependent periodic disturbances often limit the accuracy and smoothness of the positional motion of permanent magnet synchronous motor (PMSM)-driven rotary machines. Because the period of these disturbances varies with the motion velocity of the rotary machine, spatial domain control methods such as spatial iterative learning control (SILC) and spatial repetitive control (SRC) have been proposed and applied to improve rotary machine motion control designs. However, problems with learning period convergence and rotary machine dynamics significantly affect transient motion, further constraining the overall motion performance. To address these challenges, this study developed a robust driving control (RDC) that integrates a robust control design with position-dependent periodic disturbance feedforward compensation, rotary machine dynamics compensation, and proportional–proportional integral feedback control. A position-dependent periodic disturbance model was developed using multiple position–sinusoidal signals and identified using a spatial fast Fourier transform. RDC compensates for disturbances and dynamics and considers the effects of model parameter uncertainty and modeling error on the stability of the control system. Several motion control experiments were conducted on a PMSM test bench to compare the RDC, SILC, and SRC. The experimental results demonstrated that although both SILC and SRC can effectively suppress position-dependent periodic disturbances, SILC provides slower position error convergence owing to the learning process, and SILC and SRC result in significant position errors because of the influence of the PMSM-driven rotary machine dynamics. RDC not only suppresses position-dependent periodic disturbances, but also significantly reduces position errors with a reduction rate of 90%. Therefore, the RDC developed in this study effectively suppressed position-dependent periodic disturbances and significantly improved both the transient-state and steady-state position-tracking performances of the PMSM-driven rotary machine.

Unexpected macrophage-mediated myocardial cGas-STING activation in a novel mouse model of stress-related sleep disturbance

Abstract Background Delayed bedtime following stress disorder is prevalent in waves of pandemics and modern life. Considered to be a specific and important contributor to cardiovascular health, stress-related sleep disturbance has an unmet need in steady preclinical models. We previously found exciting corticotropin-releasing hormone (CRH) neurons in the paraventricular nucleus of the hypothalamus (PVH) area of mice could induce 3-hour-long wakefulness. Purpose This study aimed to induce reproducible phenotypes of stress-related sleep disturbance in mice and explore the potential impact on cardiac function. Methods The chemogenetic method of designer receptors exclusively activated by designer drugs (DREADD) system was adopted to mimic stress-related sleep disturbance. We transfected PVH CRH neurons with rAAV-hSyn-DIO-hM3Dq-mCherry and rAAV-Crh-CRE. Prolonged CRH neuron activation was induced by daily intraperitoneal injection of clozapine N-oxide (CNO, 3mg/kg) at 9 am. Bulk RNA-sequencing and bioinformatics analysis were conducted for mechanistic exploration. Results 2-week repeated chemogenetic activation of PVH CRH neurons induced a 5-fold corticosterone release, consistent with increased daily 3-hour wakefulness and corresponding decreases in both rapid eye movement (REM) as well as non-REM sleep. Over 30% of chronic CRH activation mice displayed difficulties in maintaining balance and experienced premature mortality. Mice subjected to prolonged CRH activation showed impaired left ventricular ejection fraction (67.9% versus 48.2%, p=0.0011), and a dilated appearance demonstrated by histological staining. Intriguingly, the number of circulating monocytes increased. Then, we performed bulk RNA-sequencing of heart and bone marrow from CRH-activated and control mice. Differential gene expression and gene set enrichment analysis (GSEA) indicated marked activation of interferon-beta-related pathways in both tissues. Cytosolic DNA-sensing pathway and related key effector genes (cGAS, Cxcl10, CCL5) were found up-regulated in the heart, while mitochondrial oxidative phosphorylation was suppressed. We adopted the CIBERSORT tool to estimate immune infiltration in heart tissues and characterized M1 macrophage as the main pro-inflammatory cell. Further, we screened a set of secreted factors and mediators, which might play active roles in inflamed hearts. Conclusion Taken together, we report a failing heart in a mouse model of stress-related sleep disturbance. The neuro-immune axis involvement and molecular mechanisms merit in-depth explorations.

Model-based workflow for sustainable production of high-quality spirits in packed column stills

This study addresses water scarcity in Chilean distilleries by developing a model-based engineering workflow. Prolonged droughts, likely driven by global warming, have intensified this problem. The primary challenge is maintaining high-quality spirits while reducing cooling water and energy use during batch distillation in packed columns. This process was modeled using mass and energy balances, resulting in a system of partial differential algebraic equations (PDAE). Our workflow includes mechanistic modeling, disturbance modeling, multiobjective optimization, model predictive control, and Monte Carlo simulations. Our findings show that cooling water consumption can be reduced by up to 35 % and energy consumption by up to 14.4 % while maintaining product quality. The proposed system is robust against operational disturbances and model mismatch, ensuring consistent distillate quality. This research demonstrates the integration of model-based optimization and control strategies in batch distillation processes, which can be replicated in other fruit wine distillation processes for improved sustainability.

An Examination and Analysis of Theoretical Models of Learning Disturbance and Coping Strategies of Vietnamese Chinese Language Centers

An Examination and Analysis of Theoretical Models of Learning Disturbance and Coping Strategies of Vietnamese Chinese Language Centers

Construction and verification of the prediction model for risk of sleep disturbance in elderly patients with hypertension: a cross-sectional survey based on NHANES database from 2005 to 2018

ObjectiveTo construct and verify a risk prediction model for sleep disturbance in elderly patients with hypertension, aiming to offer guidance for sleep management in this demographic.MethodsA cohort of 6,708 elderly hypertensive patients from the NHANES database, spanning 2005 to 2018, met the inclusion criteria and were selected for this study. Participants were randomly assigned to a development group (n = 4,696) and a verification group (n = 2,012) in a 7:3 ratio. The occurrence of sleep disturbance was assessed across the subjects. Independent risk factors for sleep disturbance were analyzed using weighted multivariate logistic regression within the development group. A predictive model for sleep disturbance risk in elderly hypertensive patients was developed and verified using Stata 17.0. The model's predictive accuracy and stability were evaluated using the verification group's data.ResultsOf the 6,708 subjects, 2,014 (30.02%) were identified with sleep disturbance, and the weighted prevalence of sleep disturbance among elderly hypertensive patients was 33.283%. Weighted multivariate logistic regression analysis in the development group revealed that six factors were independently associated with sleep disturbance: higher total depression scores, higher education level, asthma, overweight, arthritis, and work restriction (OR > 1 and P < 0.05). The area under the receiver operating characteristic (ROC) curve (AUC) for the nomogram prediction model was 0.709 in the development group and 0.707 in the verification group, indicating good discrimination ability. Brier scores for the nomogram model were 0.185 in the development group and 0.189 in the verification group, both below 0.25, suggesting good calibration. Decision Curve Analysis (DCA) determined that the nomogram's clinical net benefit was maximized when the threshold probability for sleep disturbance in elderly hypertensive patients was 0.13–0.67 in the development group and 0.14–0.61 in the verification group, highlighting the model's clinical utility.LimitationsThis study is not without its limitations, including issues with data collection, the absence of external validation, and the non-extrapolation of results.ConclusionThe prevalence of sleep disturbance among elderly hypertensive patients stands at 33.283%. The nomogram model, based on identified risk factors for sleep disturbance in this population, has demonstrated good predictive efficiency and clinical relevance. It serves as a valuable tool to assist healthcare providers in identifying elderly hypertensive patients at high risk for sleep disturbance.

“Wait” to promote high sighting rates of wildlife in tourism: evidence from a wildlife disturbance experiment

ABSTRACT Ecotourism is often seen as beneficial for both people and nature, but unregulated wildlife tourism can harm wildlife. To improve management practices, we studied rabbit tourism involving Amami rabbits (Pentalagus furnessi) at a Natural World Heritage Site in Japan. The study aimed to determine the sighting rates of wildlife under different car schedules and density scenarios. Using wildlife disturbance experiments and model simulations, we estimated the recovery rate of rabbits after being disturbed by tourists. Our findings revealed that a 20-minute time lag between cars resulted in a 90% recovery rate for the rabbits. Additionally, a regular car schedule increased rabbit sighting rates by approximately 1.85 times compared to random schedules and 2.4 times compared to normal schedules under optimal conditions (maximum density and 50 cars). We also evaluated the profitability of tourism under different rabbit densities and money-back guarantee (MBG) rates. While introducing more cars increased profits, it decreased rabbit sighting rates and increased the likelihood of activating the MBG. In conclusion, our study showed that considering both animal behavior and human interests in developing a tourism management system can balance profitability and minimize the impact of overutilization.