Movement Model Research Articles

Identifying signals of memory from observations of animal movements

AbstractIncorporating memory (i.e., some notion of familiarity or experience with the landscape) into models of animal movement is a rising challenge in the field of movement ecology. The recent proliferation of new methods offers new opportunities to understand how memory influences movement. However, there are no clear guidelines for practitioners wishing to parameterize the effects of memory on moving animals. We review approaches for incorporating memory into step-selection analyses (SSAs), a frequently used movement modeling framework. Memory-informed SSAs can be constructed by including spatial-temporal covariates (or maps) that define some aspect of familiarity (e.g., whether, how often, or how long ago the animal visited different spatial locations) derived from long-term telemetry data. We demonstrate how various familiarity covariates can be included in SSAs using a series of coded examples in which we fit models to wildlife tracking data from a wide range of taxa. We discuss how these different approaches can be used to address questions related to whether and how animals use information from past experiences to inform their future movements. We also highlight challenges and decisions that the user must make when applying these methods to their tracking data. By reviewing different approaches and providing code templates for their implementation, we hope to inspire practitioners to investigate further the importance of memory in animal movements using wildlife tracking data.

Remote sensing and GPS tracking reveal temporal shifts in habitat use in nonbreeding Black‐tailed Godwits

Abstract Knowledge of the habitat requirements for migratory species throughout their full annual cycle is necessary for comprehensive species protection plans. By describing seasonal shifts of space‐use patterns in a key nonbreeding area, the Senegal Delta (Mauritania, Senegal), this study addresses a significant knowledge gap in the annual cycle of the rapidly declining continental Black‐tailed Godwit Limosa limosa limosa. We fitted continuous‐time stochastic‐process movement models with GPS location data to describe the core areas used by 22 GPS‐tagged godwits over the 2022–2023 nonbreeding period. We mapped key habitat types, such as floodplain wetlands and rice fields, via supervised classification of satellite imagery. Godwits in the Senegal Delta show a distinct shift in habitat use over the nonbreeding period. The core areas of godwits in the early stages of the nonbreeding period (the wet season) were primarily in natural wetlands and fields with newly planted rice. As the rice crop matured and became too dense, godwits moved towards more recently sown rice fields. Later, as floodwaters receded and rice fields dried out, godwits abandoned rice fields and shifted towards natural wetlands with fewer invasive plants, particularly within the marshes and shallow floodplains of nature‐protected areas in the lower Delta. Synthesis and applications: Our findings illustrate the shifting importance of natural and agricultural wetlands for godwits at different stages of the nonbreeding season. Protected areas in the Senegal Delta, particularly the Djoudj National Bird Sanctuary (Senegal) and Diawling National Park (Mauritania), are crucial habitats during the dry season as godwits prepare for their northward migration, whilst rice fields take a key role during the wet season. Conservation efforts should prioritize eradicating invasive plants from the Djoudj and Diawling, as well as promote agroecological management in specific rice production complexes indicated in this study.

A scoping review of social work with Roma and Traveller communities: introducing the ROMA model

ABSTRACT Although The Strasbourg Declaration on Roma presents a list of priorities that aim to address the social and economic marginalisation of Roma and Traveller people in Europe, the contribution that social work is making to efforts to achieve these aims is unclear. Therefore, a scoping review of current scholarship was conducted to summarise the existing body of knowledge and identify how social work can help to achieve The Strasbourg Declaration on Roma. The databases Academic Search Complete, SAGE Journals Online, ScienceDirect, and Social Care Online were searched resulting in the inclusion of 20 articles published between 2010 and 2024. Two themes were identified: (1) Antigypsyism and (2) Restorative Practice. The findings show that restorative practices could help to promote human rights and the social and intercultural inclusion of Roma and Travellers in Europe. Informed by the articles included in this scoping review, the ‘Reflection, Objective, Movement and Action (ROMA) Model: A Framework for Restorative Practice is introduced as a solution to enable social workers to achieve The Strasbourg Declaration on Roma and future national strategic frameworks for Roma and Traveller inclusion.

A hybrid workflow connecting a network and an agent-based model for predictive pedestrian movement modelling

A hybrid workflow connecting a network and an agent-based model for predictive pedestrian movement modelling

Design optimization of floating offshore wind farms using a steady state movement and flow model

Abstract In this study, we demonstrate how to carry out the design optimization of floating offshore wind farms by considering the impacts brought by the movements of the floating wind turbines. A steady state movement and flow model is applied in the modelling process. This model is developed by building a turbine surrogate model for estimating the steady state movement and power production of floating wind turbines and incorporating it in an open-source static wind farm simulator, PyWake. Using this modelling methodology, layout optimization problems of floating offshore wind farms are solved by using algorithms like Random Search to maximize the energy yield while satisfying certain constraints. Case studies are carried out for two wind farms with met-ocean conditions from a real planned site in Scottland to show the potential of layout optimization for floating wind farms.

Course control in a self-consistent model of cuttlefish movement

We developed a simulation model to mimic cuttlefish movement. We developed a simulation model to mimic cuttlefish movement, representing an elongated body with two undulatory fins that generate propulsive forces for underwater movement. Our mathematical model concurrently solved equations for both body mechanics and fluid dynamics, using the Navier–Stokes equations to describe the latter. To implement this self-consistent model, we utilized deformable mesh techniques. This enabled us to compute both the apparatus’s movement performance characteristics and hydrodynamic flow parameters, such as vorticity and pressure fields. Our study focused on examining how oscillations of the left and right fins, each with different parameters, impact the apparatus’s maneuverability. We found that differences in frequencies between the left and right fins resulted in a peak turning angle velocity. We also explored how the interplay between hydrodynamic forces influences the apparatus’s course control.

Modeling of drug release, erosion and diffusion fronts movement in high viscosity HPMC matrices containing a cellulolytic enzyme

A formerly developed mathematical model describing drug release from hydrophilic matrices (HMs) took into account resistance to drug release given by its dissolution and by the presence of a growing gel layer. Such a model was applied to previously reported release data obtained from HMs made of hydroxypropyl methylcellulose (HPMC), where acetaminophen was used as model drug and a cellulolytic product was added as “active” excipient to attain zero-order release kinetics. The Levich theory applied to acetaminophen intrinsic dissolution rate (IDR) data highlighted the suitability of such a drug for modeling purposes, given its good surface wettability. First assessment of the model ability to describe drug release from the abovementioned systems was carried out on partially coated matrices, representing a simplified physical frame, but results were then confirmed on uncoated systems. Experimental and model release data showed good agreement; therefore, the release-describing equation was combined with that of the global mass balance to obtain two new equations related to erosion and diffusion fronts time evolution. Changes over time in the dissolution and gel contributions to total resistance, calculated using model output parameters, highlighted that the enzyme, through its hydrolytic activity on HPMC, was responsible for a time-dependent reduction of the resistance component related to gel layer.

Plexin-B2 Mediates Orthodontic Tension-Induced Osteogenesis via the RhoA/F-Actin/YAP Pathway.

This study aims to investigate the role of Plexin-B2 in tension-induced osteogenesis of periodontal ligament stem cells (PDLSCs) and its biomechanical mechanism. In vitro, cyclic tension simulated orthodontic forces to assess Plexin-B2 expression in PDLSCs. We then knocked out Plexin-B2 using lentivirus to explore its role in tension-induced osteogenesis. Invivo, we used nickel-titanium springs to establish orthodontic tooth movement (OTM) models in mice. Local periodontal Plexin-B2 expression was knocked down using adeno-associated viruses (AAVs) to study its influence on new bone formation under mechanical tension in OTM models. Molecular mechanisms were elucidated by manipulating Plexin-B2 and RhoA expression, assessing related proteins, and observing F-actin and Yes-associated protein (YAP) through immunofluorescence. Plexin-B2 expression in PDLSCs increased under cyclic tension. Decrease of Plexin-B2 reduced the expression of osteogenic protein in PDLSCs and negatively affected new bone formation during OTM. RhoA expression and phosphorylation of ROCK2/LIMK2/Cofilin decreased in Plexin-B2 knockout PDLSCs but were reversed by RhoA overexpression. The level of F-actin decreased in Plexin-B2 knockout PDLSCs but increased after RhoA rescue. Nuclear YAP was reduced in Plexin-B2 knockout PDLSCs but increased after RhoA overexpression. Plexin-B2 is involved in tension-induced osteogenesis. Mechanistically, the RhoA signaling pathway, the F-actin arrangement, and the nuclear translocation of YAP are involved in the mechanotransduction of Plexin-B2.

Catalpol Enhances Osteogenic Differentiation of Human Periodontal Stem Cells and Modulates Periodontal Tissue Remodeling in an Orthodontic Tooth Movement Rat Model.

This study examines the effects and mechanisms of catalpol (CAT) on the proliferation and osteogenic differentiation of cultured human periodontal ligament stem cells (hPDLSCs) in vitro and assesses the impact of CAT on periodontal remodeling in vivo using an orthodontic tooth movement (OTM) model in rats. hPDLSCs were cultured in a laboratory setting, and their proliferation and osteogenic differentiation were assessed using the Cell-counting Kit-8 (CCK-8), Alizarin Red Staining (ARS), quantitative calcium assay, alkaline phosphatase (ALP) staining and activity assay, and immunofluorescence assay. Additionally, the expression of collagen type 1 (COL-1), ALP, and runt-related transcription factor-2 (RUNX-2) was evaluated through qRT-PCR and Western blot analysis. To verify the function of the estrogen receptor-α (ER-α)-mediated phosphatidylinositol-3-kinase-protein kinase B (PI3K/AKT) pathway in this mechanism, LY294002 (a PI3K signaling pathway inhibitor) and the ER-α specific inhibitor methyl-piperidine-pyrazole (MPP) were used. The osteogenic markers ER-α, AKT, and p-AKT (phosphoprotein kinase B) were identified through Western blot analysis. Eighteen male Sprague-Dawley rats were assigned to two groups randomly: a CAT group receiving CAT and a control group receiving an equivalent volume of saline. Micro-computed tomography (micro-CT) analysis was employed to evaluate tooth movement and changes in alveolar bone structure. Morphological changes in the periodontal tissues between the roots were investigated using hematoxylin and eosin (HE) staining and tartaric-resistant acid phosphatase (TRAP) staining. The expression of COL-1, RUNX-2, and nuclear factor-κB (NF-κB) ligand (RANKL) was assessed through immunohistochemical staining (IHC) to evaluate periodontal tissue remodeling. Tests were analyzed using GraphPad Prism 8 software. Differences among more than two groups were analyzed by one-way or two-way analysis of variance (ANOVA) followed by the Tukey's test. Values of p < 0.05 were regarded as statistically significant. In vitro experiments demonstrated that 10μM CAT significantly promoted the proliferation, ALP activity, and calcium nodule formation of hPDLSCs, with a notable increase in the expression of COL-1, ALP, RUNX-2, ER-α, and p-AKT. The PI3K/AKT pathway was inhibited by LY294002, and further analysis using MPP suggested that ER-α mediated this effect. In vivo, experiments indicated that CAT enhanced the expression of COL-1 and RUNX-2 on the tension side of rat tooth roots, reduced the number of osteoclasts on the compression side, inhibited RANKL expression, and suppressed OTM. CAT can promote hPDLSCs proliferation and osteogenic differentiation in vitro through the ER-α/PI3K/AKT pathway and enhance periodontal tissue remodeling in vivo using OTM models. These findings suggest the potential for the clinical application of catalpol in preventing relapse following OTM.

A network evaluation of human and animal movement data across multiple swine farm systems in North America

INTRODUCTIONThe U.S. swine industry is vulnerable to the rapid spread of disease due to systemic structural issues. While animal movement networks are used to identify disease spread risks and design response plans, human movement between farms were rarely accounted for. Human movements, when integrated with animal movement models, create a different, more inclusive, and accurate network structure when compared to animal movements alone. METHODSOne year of propriety farm visit data was analyzed and consisted of anonymized property IDs, location, and user/truck IDs, along with visit dates, property, vehicle, and entry types from three swine management companies. A static directed network was created using the igraph package in R for all movements, with separate sub-networks for each entry type (animal, human, and subsets of vehicle types). Network statistics for each sub-network were compared. RESULTSThe full network included 455 properties, 11 property types, 9 vehicle types, 12 entry types, and 320001 edges (trips between properties). The longest path length was 10 in the animal movement network but decreased to 5 for the full and human movement network, while the average path length decreased from 3.2 to 2.2. Edge density increased from 0.03 to 0.09 for the human network and 0.1 for the full network. For all network properties examined, the full and human movement networks demonstrated higher connectivity than the animal network. A heavy right skew in the degree distributions indicates a 'hub' structure (scale-free-like network) and the shorter path lengths indicates a small-world network topology. DISCUSSIONThe full network is very well connected, more so than expected based on animal movement alone. Hubs may indicate points of disease susceptibility and 'super-spreader' properties. The high connectivity shows that swine farm networks may be more susceptible to spready of an introduced disease than expected from previous analyses. CONCLUSIONSMonitoring human, as well as animal movement, provides for a more complete and accurate understanding of swine farm biosecurity risks.

‘Must Fall’ movements globally: transnational flows of South African student activism

This article demonstrates an important case of transnational activist influence from the Global South to both Global North and other Global South contexts. While protests, slogans, strategies and demands are expressions of a specific context-bound protest culture, they have the potential to resonate globally. In this way, specific protests become a model for other social movements, although not without tension or reconfigurations of activism. In this article, we explore the transnational flow of the ideas around ‘Must Fall’, developed initially by the South African student movement. From 2015, several university-based protests in South Africa coalesced under the slogan ‘Must Fall’, most prominently #RhodesMustFall and #FeesMustFall. This ‘Must Fall’ idea resonated transnationally in multiple contexts. However, protests using ‘Must Fall’ also drew from other resources and held different meanings across the different contexts, creating a complex transnational flow of partially connected protests across Africa, Europe, and the US. Nevertheless, the ‘Must Fall’ protests were similar in expressing a need for a radical change to rupture and overcome structures of oppression, especially those shaped by colonialism. This article analyses the Global South genesis and meaning of the ‘Must Fall’ protests and how they travelled, resonating differently in both Southern and Northern contexts.

Deep Convolutional Transformer Network for Stock Movement Prediction

The prediction and modeling of stock price movements have been shown to possess considerable economic significance within the finance sector. Recently, a range of artificial intelligence methodologies, encompassing both traditional machine learning and deep learning approaches, have been introduced for the purpose of forecasting stock price fluctuations, yielding numerous successful outcomes. Nonetheless, the identification of effective features for predicting stock movements is considered a complex challenge, primarily due to the non-linear characteristics, volatility, and inherent noise present in financial data. This study introduces an innovative Deep Convolutional Transformer (DCT) model that amalgamates convolutional neural networks, Transformers, and a multi-head attention mechanism. It features an inception convolutional token embedding architecture alongside separable fully connected layers. Experiments conducted on the NASDAQ, Hang Seng Index (HSI), and Shanghai Stock Exchange Composite (SSEC) employ Mean Absolute Error (MAE), Mean Square Error (MSE), Mean Absolute Percentage Error (MAPE), accuracy, and Matthews Correlation Coefficient (MCC) as evaluation metrics. The findings reveal that the DCT model achieves the highest accuracy of 58.85% on the NASDAQ dataset with a sliding window width of 30 days. In terms of error metrics, it surpasses other models, demonstrating the lowest average prediction error across all datasets for MAE, MSE, and MAPE. Furthermore, the DCT model attains the highest MCC values across all three datasets. These results suggest a promising capability for classifying stock price trends and affirming the DCT model’s superiority in predicting closing prices.

Method for Determining the Conditions for Ensuring Stable Rearward Movement of a Semi-trailer Combination with Non-turning Semi-trailer Wheels

The efficiency of organising freight transport and using motor transport in a Smart City depends on a set of its properties, which in the process of operation determine its suitability for use in given operating conditions. Vehicles have different overall dimensions and designs, which determine their maneuverability and directional stability, their ability to make a curve-line movement in the city, as well as to move safely in reverse. Nowadays, tractor-trailer combinations with non-turning semi-trailer wheels are widely used for freight transport. Such a scheme of vehicle construction does not ensure its directional stability when reversing, which can lead to the folding of the tractor and semi-trailer and loss of mobility of the combination. In the absence of additional special systems, the driver controls the rearward movement of the road train using the steering wheel and rear-view mirrors, and the accuracy of delivery to the object depends on the level of the driver's training. The research of driver's reaction time spent on situation assessment, decision making, and realisation has been carried out. It has been revealed that with manual control, there are difficulties connected with training of drivers to estimate the parameters of movement and control of the road train, in particular, with the process of parking and its accurate delivery to the object. With the help of the developed mathematical model of the rearward movement of the road train and the proposed new turn control law, the research of maneuvering of the road train during its delivery to the object has been carried out and the results confirming the possibilities of building an automated system allowing to reduce the influence of the human factor on the parking process, as well as to reduce the time required to perform the maneuver have been obtained. The conducted analysis of system stability with the help of Routh–Hurwitz criterion has determined the conditions of providing stability of the system moving in reverse. The method of controlling the backward movement of the road train and the design of the device realising it has been developed. The results of simulation modeling allowed us to find the necessary values for the control law for the movement of road trains of different lengths, as well as the preferred variants of the initial positions of the road train for the realisation of its precise delivery to the object.

On plutonium-241 and americium in the two-component nuclear energy system

The paper deals with the influence of the strategy for using separated plutonium from spent fuel of thermal and fast reactors, as well as homogeneous burning of americium in the BN reactor core on the balance of americium in the Russian nuclear fuel cycle throughout the 21st century. The assessment is carried out with the use of mathematical modeling of nuclear materials movement including nuclide transformations throughout the nuclear energy system based on the CYCLE code. Scenario modeling of the americium and Pu-241 accumulation was carried out in Russia’s two-component nuclear energy system model with thermal (VVER) and fast (BN) reactors. In so doing, spent nuclear fuel (SNF) reprocessing was simulated in 2 options: as priority reprocessing of SNF of VVER reactors (1) or SNF of BN reactors (2). In addition to americium accumulation in the system without burning, the accumulation of this actinide was studied taking into account its homogeneous burning in the MOX-fuel of fast reactors at the level of its equilibrium content of ~1%. It has been shown that the priority reprocessing of VVER spent fuel makes it possible to reduce the americium accumulation by the end of the century by ~8 tons, and the effect is achieved by using freshly separated plutonium with short-term cooling, thus, by priority the americium source is eliminated, without directly handling it. Homogeneous addition of americium to the fuel of fast reactors of the BN-1200 type at a level of ~1% makes it possible to stop accumulation of americium in a two-component energy system by 2070, stabilizing it at a level of ~40 tons in the scenario with priority reprocessing of VVER SNF and ~50 tons in the scenario with priority reprocessing of BN SNF.

Visualization Analysis of Integrating College Sports Training and Psychology into Basketball Physical Education Teaching System Based on Image Recognition Algorithm

ABSTRACT On this basis, a basketball movement model based on ORB (Oriented FAST and Rotated BRIEF) local feature extraction has been proposed, and a basketball teaching visualization analysis system has been constructed. By extracting images from athletes’ videos in basketball, and using their training as a standard, tracking the frequency of their various celebration postures appearing and improving their scores in the game, corresponding feature points are extracted, and then the BP (back propagation) neural network algorithm is used to classify feature points. Ten different participants were selected from 10 games. Their movements were tracked, and then the extracted feature actions were imported into the visualization system for visual analysis, comparing the changes before and after psychological intervention. The results showed that there were significant differences in scores, errors, hit rates, steals, and motivation among subjects who received psychological cues and incentives compared to the data before psychological counseling. The scores and positive and negative values increased to 2–4 points, which had a certain positive impact on the competitive results.

Model-based estimation of heart movements using microwave Doppler radar sensor.

Heart rate is one of the most crucial vital signs and can be measured remotely using microwave Doppler radar. As the distance between the body and the Doppler radar sensor increases, the output signal weakens, making it difficult to extract heartbeat waveforms. In this study, we propose a new template-matching method that addresses this issue by simulating Doppler radar signals. This method extracts the heartbeat waveform with higher accuracy while the participant is naturally sitting in a chair. An extended triangular wave model was created as a mathematical representation of cardiac physiology, taking into account heart movements. The Doppler radar output signal was then simulated based on this model to automatically obtain a template for one cycle. The validity of the proposed method was confirmed by calculating the PPIs using the template and comparing their accuracy to the R-R intervals (RRIs) of the electrocardiogram for five participants and by analyzing the signals of eight participants in their natural state using the mathematical model of heart movements. All measurements were conducted from a distance of 500 mm. The correlation coefficients between the RRIs of the electrocardiogram and the PPIs using the proposed method were examined for five participants. The correlation coefficients were 0.93 without breathing and 0.70 with breathing. This demonstrates a higher correlation considering the long distance of 500 mm, and the fact that body movements were not specifically restricted, suggesting that the proposed method can successfully estimate RRI. The average correlation coefficients, calculated between the Doppler output signals and the templates for each of the eight participants, exceeded 0.95. Overall, the proposed method showed higher correlation coefficients than those reported in previous studies, indicating that our method performed well in extracting heartbeat waveforms. Our results indicate that the proposed method of remote heart monitoring using microwave Doppler radar demonstrates higher accuracy in estimating the RRI of the electrocardiogram while at rest sitting in a chair, and the ability to extract the heartbeat waveforms from the measured Doppler output signal, eliminating the need to create templates in advance as required by conventional template matching methods. This approach offers more flexibility in the measurement environment than conventional methods.

Pedestrian safety behavior modeling method in human-vehicle-intelligence shared road space

In the context of the development of autonomous vehicles sharing road resources with traditional traffic participants in the future, modeling the safe behavior of pedestrians in the shared road space between people, vehicles and intelligence is crucial for the simulation development and reliability and safety testing of autonomous vehicles. To meet this demand, the safe movement behavior of pedestrians is first analyzed, and on this basis, the traditional pedestrian social force model is improved to construct a momentum model for the interactive movement of pedestrians with other pedestrians, traditional vehicles and autonomous vehicles in the shared road space; then, the safety parameters of the model are calibrated using a data set of human-vehicle interactive movement and a genetic algorithm, and a typical shared road space scenario is built to verify the effectiveness of the model. The simulation results show that the model can simulate the real safe movement behavior of pedestrians, and has better simulation effects when used in tasks such as human-vehicle-intelligence shared road space simulation.

Fire Safety Assessment of a Typical Sports Hall Building Based on Fire Dynamics and Crowd Movement Models

Fire risk analysis is one of the essential components of building design to ensure the safety of occupants and properties in case of fires. Currently, the Ministry of Public Works and Housing Regulation No. 20/PRT/M/2009 provides guidelines for conducting a fire risk analysis, however, without a clear consideration of fire dynamics in the estimation of the fire risk level. In this work, we investigate the fire safety aspects of a typical sports hall buildings by a fire dynamics deterministic model (Fire Dynamics Simulator (FDS) of the National Institute of Science and Technology, USA) and crowd movement model for occupant evacuation (Pathfinder of Thunderhead Engineering). Systematic investigations were made on the effects of the fire growth category and smoke extraction system on the Available Safe Egress Time (ASET). The results of ASET were then compared to the Required Safe Egress Time (RSET) which is obtained from the evacuation model. Our results suggest that ASET decreases exponentially with fire growth rate, especially from slow to medium growth rate. The fire growth rate significantly affects the acceptable fire risk of ASET longer than RSET. Occupant capacity, fire management systems, and smoke extraction systems play important roles in reducing fire risk. However, as the fire growth rate increases, the effects of smoke extraction in maintaining safe conditions diminish. This study provides recommendations to reduce risks to the occupants in case of fire, contributing to the considerations of the design and management of a typical sports hall building.

Learning to Move Like Professional Counter‐Strike Players

AbstractIn multiplayer, first‐person shooter games like Counter‐Strike: Global Offensive (CS:GO), coordinated movement is a critical component of high‐level strategic play. However, the complexity of team coordination and the variety of conditions present in popular game maps make it impractical to author hand‐crafted movement policies for every scenario. We show that it is possible to take a data‐driven approach to creating human‐like movement controllers for CS:GO. We curate a team movement dataset comprising 123 hours of professional game play traces, and use this dataset to train a transformer‐based movement model that generates human‐like team movement for all players in a “Retakes” round of the game. Importantly, the movement prediction model is efficient. Performing inference for all players takes less than 0.5 ms per game step (amortized cost) on a single CPU core, making it plausible for use in commercial games today. Human evaluators assess that our model behaves more like humans than both commercially‐available bots and procedural movement controllers scripted by experts (16% to 59% higher by TrueSkill rating of “human‐like”). Using experiments involving in‐game bot vs. bot self‐play, we demonstrate that our model performs simple forms of teamwork, makes fewer common movement mistakes, and yields movement distributions, player lifetimes, and kill locations similar to those observed in professional CS:GO match play.

МЕТОДИКА ЕКСПЕРИМЕНТАЛЬНИХ ДОСЛІДЖЕНЬ СПРОЩЕНОЇ МОДЕЛІ БПЛА ТИПУ БІКОПТЕР

Modern aircraft are usually statically unstable objects. Due to this, increased maneuverability and controllability is achieved. One of the promising directions is the development and implementation of UAVs of the bicopter or convertible type. Their movement is provided by two screw electric drives. The non-identity of the engine parameters and the peculiarities of the movement of UAVs of this type cause special requirements for the control systems. To ensure sustainability, modeling and conducting research with the help of various tools is necessary. The most available models of unstable movements are pendulum devices of various types, which allow studying stabilization processes. The purpose of the work is to use a computer stabilization system of a simplified bicopter UAV model by changing the thrust of the engines. The tasks of the work are: development of a computer stabilization system for the angle of pitch or roll, creation and verification of stabilization algorithms on a laboratory bench using an ARDUINO controller, research of the functional capabilities of angular stabilization circuits. The object of the study: a computer control system of an aircraft that performs the task of stabilizing a UAV. Subject of research: processes of stabilization of the angular position of a simplified bicopter model. When performing the work, a control law using angular and angular velocity feedback was chosen. A variant of aircraft stabilization when using engine thrust control is proposed. The control law of the computer stabilization system, which is implemented on the ARDUINO controller, was selected and tested. The applied value of the work is the further use of the obtained results in modern samples of bicopters.