Observation Interval Research Articles

Consensus of Time‐Varying Interval Uncertain Multiagent Systems via Reduced‐Order Neighborhood Interval Observer

This work focuses on a multiagent system (MAS) with time‐varying interval uncertainty in the system matrix, where multiple agents interact through an undirected topology graph and only the bounding matrices on the uncertainty in the system matrix are known. A reduced‐order interval observer (IO), which is named the reduced‐order neighborhood interval observer (NIO), is designed to estimate the relative state of each agent and those of its neighbors. It is shown that the reduced‐order IO can guarantee the consensus of the uncertain multiagent system. Finally, simulation examples are proposed to verify the theoretical findings.

Distributed Sliding Mode Fault‐Tolerant LFC for Multiarea Interconnected Power Systems under Sensor Fault

This paper focuses on the problem of load frequency control and sensor fault‐tolerant control in the multiarea power grid. To solve these problems, a sliding mode control strategy based on an interval observer is designed. First, an interval observer is designed to obtain the boundary estimation information of the system state online, which is used to reconstruct the load disturbance online. Based on the reconstructed values, an integral sliding mode controller is designed to keep the system frequency stable when the load is disturbed. Then, sensor fault is diagnosed by interval residual. An augmented observer is designed to estimate sensor fault online by equivalent transformation, and the sensor fault is compensated by the fault estimation to reduce the influence of fault on system performance and ensure the reliable and stable operation of the power system. The simulation results show the superiority of the proposed control strategy.

Dekomponovanje osnovnih pokazatelja smrtnosti u Srbiji u periodu 1990-2021

The research of thirty-year changes in the mortality of the population of Serbia (1990-2021) is given through two basic indicators of mortality. Using the decompose method to calculated the effect of population aging on the difference between crude mortality rates, as well as the contributions of specific mortality rates and leading causes of death in the changes in life expectancy. The crude death rate shows that the intensity of dying in Serbia is very high. The pandemic contributed to record values in the last two years. Overall, in the period 1990-2019, the negative contribution of the age structure is twice as intense as the positive effect of age-specific mortality rates. Aging is more intense in the female population, which explains the greater increase in the crude death rate in women. The data show that the importance of demographic aging has always been more pronounced. The main characteristic in the observed time interval is that mortality decreases at all ages and that all age groups had a positive effect on life expectancy, as well as that men and women in Serbia have a different pattern of decreasing mortality by age. The most significant effect on life expectancy was the reduction of infant mortality (a fifth of the total contribution), a common feature of the male and female populations. In other age groups, men have more pronounced contributions up to the age of 50, and women in older cohorts. Due to higher mortality rates, the space for improving mortality is greater in young and middle-aged men than in women, so the positive effects are more pronounced at these ages. The largest number of leading causes of death burdens the population of Serbia less now than three decades earlier. Cardiovascular diseases, as the leading cause of death, contributed the most to positive changes in mortality. The biggest effect of life expectancy is the reduction of mortality rates due to diseases of the circulatory system in the 65-79 year old population. Observed by gender, the effect is greater in the female population, where cardiovascular diseases contribute to the extension of life expectancy by as much as 67% or by 2.4 years, while in the male population the importance of cardiovascular diseases in the extension of life expectancy is lower and amounts to 42% or by 1.9 years. Tumors, as the second most common cause of death in Serbia, contribute negatively to those aged 50 and over and positively to younger age groups. The overall effect on life expectancy is positive, and mortality rates in men decline until the age of 60. In women, rates increase from age 50 or older, and of all causes of death, only tumors have an overall negative effect on life expectancy growth. Among the other causes, the importance of violent deaths and their positive effect should be singled out, due to the reduction of mortality rates at all ages, especially among the younger population. Positive changes in the age of 15-49 years in the male population contribute to an increase in life expectancy of even 1 year. In the female population, a positive contribution is also present at all ages, but the effect is significantly lower. The COVID-19 pandemic brought the highest increase in mortality in Serbia in the last 70 years. Mortality increased by 14% in the first year of the pandemic, and by 34% in the second, compared to the 2017-2019 average. The crude death rate has increased tremendously and for men in 2020 it is 18.0‰, and in 2021 it will show a maximum value of 21 deaths per 1,000 persons. For women, this mortality rate is 15.9‰ and 19.0‰ (in 2020 and 2021, respectively). Changes compared to the values from 2019, for both sexes, are solely the result of the increase in mortality by age, while changes in the distribution of the population by age had a negligible effect in this period. The last analyzed year (2021) brings a drop in life expectancy for men of as much as 3.4 years compared to the period before the pandemic. Women in Serbia have a slightly smaller decline in life expectancy in this period of 2.9 years.

Bi-Temporal Semantic Reasoning for the Semantic Change Detection in HR Remote Sensing Images

Semantic change detection (SCD) extends the multiclass change detection (MCD) task to provide not only the change locations but also the detailed land-cover/land-use (LCLU) categories before and after the observation intervals. This fine-grained semantic change information is very useful in many applications. Recent studies indicate that the SCD can be modeled through a triple-branch convolutional neural network (CNN), which contains two temporal branches and a change branch. However, in this architecture, the communications between the temporal branches and the change branch are insufficient. To overcome the limitations in existing methods, we propose a novel CNN architecture for the SCD, where the semantic temporal features are merged in a deep CD unit. Furthermore, we elaborate on this architecture to reason the bi-temporal semantic correlations. The resulting bi-temporal semantic reasoning network (Bi-SRNet) contains two types of semantic reasoning blocks to reason both single-temporal and cross-temporal semantic correlations, as well as a novel loss function to improve the semantic consistency of change detection results. Experimental results on a benchmark dataset show that the proposed architecture obtains significant accuracy improvements over the existing approaches, while the added designs in the Bi-SRNet further improve the segmentation of both semantic categories and the changed areas. The codes in this article are accessible at <uri>https://github.com/ggsDing/Bi-SRNet</uri>.

A Tuned Whitening-Based Taylor-Kalman Filter for P Class Phasor Measurement Units

Protection-oriented (P Class) phasor measurement units (PMUs) are required to reconcile high measurement accuracy and low latency in order to promptly detect possible anomalous operating conditions in power systems. Most of the existing estimators of synchrophasor magnitude, phase, frequency, and rate of change of frequency (ROCOF) of voltage or current AC waveforms need to acquire the samples of at least two power line cycles to meet the P Class requirements specified in the IEEE/IEC Standard 60255-118-1:2018. In this article, instead, a multistep technique based on the combination of multiple signal classification (MUSIC), narrowband disturbance whitening, and Taylor–Kalman Filtering (TKF) is proposed to maximize accuracy even over one-cycle-long observation intervals. Both MUSIC and disturbance whitening rely on a common theoretical framework (i.e., signal and noise vector subspace decomposition) and they are applied to compensate for the detrimental effect of off-nominal frequency deviations and harmonic distortion, respectively. The use of cascaded dynamic estimators such as the TKF is motivated by the need to track possible in-band amplitude and phase oscillations or step-like changes with low latency. While the basic TKF is very sensitive to possible narrowband disturbances, the tuned whitening-based TKF (TW-TKF) described in this article ensures superior accuracy under the influence of harmonics and amplitude or phase step changes, with just a minor performance degradation in the other P Class testing conditions reported in the IEEE/IEC Standard 60255-118-1:2018.

ESTIMATION OF MAXIMUM LIKELIHOOD IN THE CONDITIONS OF INSPECTIONS OF THE CURRENT STATE

The article discusses the algorithm and methods of statistical processing of one type of grouped data – interval-censored samples with overlapping observation intervals. The samples are censored by the observation time interval of the measured value. The samples consist entirely of such interval observations. The initial information was the data of one-time and multiple inspections of the structure in operation in order to detect damage in the form of cracks. The stage of appearance of the initial crack (macrocrack) in the zone of stress concentration is determined. A macrocrack, for objective reasons, cannot be directly detected during inspections. Examples of describing the time of formation of initial cracks in the form of interval-censored samples with intersecting observation intervals are presented. The main focus was on the development of methods for statistical processing of the studied samples. The maximum likelihood method was applied for parametric estimation of the time of appearance of macrocracks. Basic maximum likelihood equations are obtained for distributions with location and scale parameters. The computational procedure of the accumulation method with the use of Fisher’s information is applied. Expressions for calculating the variances of parameter estimates are obtained. An equation for checking the existence of a solution to the system of likelihood equations is presented. The appearance of macrocracks can have a different physical nature, for example, the accumulation of fatigue or instantaneous damage due to an overload exceeding the calculated one. Different physical nature implies different types of preventive work to prevent them and is described by different probabilistic models. A likelihood ratio criterion is proposed to test the statistical hypothesis about the situation of sudden appearance of macrocracks at a load exceeding the calculated one. The results obtained show the features of the structure of the studied samples and possible methods of statistical processing. Bibliography 11 titles Table 2.

Modeling the Electrocardiogram as Oscillatory Almost-Cyclostationary Process

A new model for the electrocardiogram (ECG) signal is proposed. Specifically, the ECG signal is modeled as an amplitude-modulated and time-warped version of a cyclostationary process which is the sum of a periodic signal and a zero-mean cyclostationary term. For the proposed model, the second-order characterization is derived in both time and frequency domains. The autocorrelation function is shown to be the superposition of amplitude- and angle-modulated sine waves and the Loève bifrequency spectrum a spread version of that of the underlying cyclostationary process. The signal model belongs the recently introduced class of the oscillatory almost-cyclostationary processes. A procedure for estimating the second-order statistical functions in both time and frequency domains is outlined. The effectiveness of the proposed model and of the estimation procedure is corroborated by measurements on real ECG signals. These measurements are in full agreement with the theoretical analytical expressions. The proposed model is shown to be effective with observation intervals much larger than those adopted up to now with the classical cyclostationary model and is suitable to be exploited for arrhythmia modeling and characterization, and for diagnosis and biometric purposes.

Non-Autonomous Hybrid Stochastic Systems with Delays

The aim of this paper is to study the dynamical behavior of non-autonomous stochastic hybrid systems with delays. By general Krylov-Bogolyubov's method, we first obtain the sufficient conditions for the existence of an evolution system of measures of the non-autonomous stochastic system and also give some easily verifiable conditions. We then prove a sufficient condition for convergence of evolution systems of measures as the delay approaches zero. As an application of the abstract theory, we first prove the existence of evolution systems of measures for stochastic system with time-vary delays, which comes from feedback control problem based on discrete-time state observations. Furthermore, when observation interval goes to zero, we show every limit point of a sequence of evolution system of measures of the non-autonomous stochastic system must be a evolution system of measures of the limiting system.

Non-zero-sum neutrality test for the tropical rain forest community using long-term between-census data.

For community ecologists, “neutral or not?” is a fundamental question, and thus, rejecting neutrality is an important first step before investigating the deterministic processes underlying community dynamics. Hubbell's neutral model is an important contribution to the exploration of community dynamics, both technically and philosophically. However, the neutrality tests for this model are limited by a lack of statistical power, partly because the zero‐sum assumption of the model is unrealistic. In this study, we developed a neutrality test for local communities that implements non‐zero‐sum community dynamics and determines the number of new species (N sp) between observations. For the non‐zero‐sum neutrality test, the model distributed the expected N sp, as calculated by extensive simulations, which allowed us to investigate the neutrality of the observed community by comparing the observed N sp with distributions of the expected N sp derived from the simulations. For this comparison, we developed a new “non‐zero‐sum N sp test,” which we validated by running multiple neutral simulations using different parameter settings. We found that the non‐zero‐sum N sp test rejected neutrality at a near‐significance level, which justified the validity of our approach. For an empirical test, the non‐zero‐sum N sp test was applied to real tropical tree communities in Panama and Malaysia. The non‐zero‐sum N sp test rejected neutrality in both communities when the observation interval was long and N sp was large. Hence, the non‐zero‐sum N sp test is an effective way to examine neutrality and has reasonable statistical power to reject the neutral model, especially when the observed N sp is large. This unique and simple approach is statistically powerful, even though it only employs two temporal sequences of community data. Thus, this test can be easily applied to existing datasets. In addition, application of the test will provide significant benefits for detecting changing biodiversity under climate change and anthropogenic disturbance.

Stability Radii-Based Interval Observers for Discrete-Time Nonlinear Systems

In this paper, we investigate the interval observer problem for a class of discrete-time nonlinear systems, in absence or presence of external disturbances and parametric uncertainties. The interval observers depend on the design of two preserving order observers, providing lower and upper estimations of the state. The main objective is to apply the stability radii notions and cooperativity property in the estimation error systems in order to guarantee that the lower/upper estimation is always below/above the real state trajectory at each time instant from an appropriate initialization, and the estimation errors converge asymptotically towards zero when the disturbances and/or uncertainties are vanishing. For the disturbed case, the estimation errors practically converge to a vicinity of zero, while the lower/upper estimations preserve the partial ordering with respect to the state trajectory. The design conditions, that are valid for Lipschitz nonlinearities, can be expressed as Linear Matrix Inequalities (LMIs). A numerical simulation example is provided to verify the effectiveness of the proposed method.

Event-Triggered Control for Discrete-Time Systems Using a Positive Systems Approach

We provide an output feedback event-triggered controller for discrete-time linear systems. We make novel use of positive systems, interval observers, an event-triggered state estimator, and triggering times that are computed from estimator values. This provides a discrete-time analog of our recent positive systems approach for continuous-time systems. A key novel ingredient in our discrete-time event triggers is their use of vectors of absolute values, instead of the usual Euclidean norm. We illustrate the benefits of our method using a model for event-triggered BlueROV2 underwater vehicles.

Breeding and Post-Breeding Behavior of the Ghost Bat (Macroderma gigas) at Perth Zoo

Understanding the behavior of wildlife in zoo environments is necessary to determine species’ welfare states and minimize stress whilst optimizing social groupings, particularly where breeding programs are being undertaken. This observational study investigated the behavior and welfare of six groupings of ghost bats (Macroderma gigas) across the breeding and post-breeding seasons within Perth Zoo, Western Australia. Scan sampling was used to record behavioral states and interactions along with spatial preferences within enclosures for 198 hours of observations. A total of 11,895 interval observations were conducted during the study period. Exploratory behavior was correlated with enclosure size, with 18.7% of the total observations in the largest enclosure compared with only 7.1% of them in the smallest enclosure. Male ghost bats engaged in negative behaviors in 40.2% of observed male-male interactions, regardless of the season. Non-breeding females engaged in more female-female negative behaviors during the breeding season, while negative behaviors increased in the breeding female group after the end of the breeding season. This study highlights areas where management practice may be optimized in a zoo setting and provides evidence to consider revising standards of enclosure size for chiropteran species. An increase in heating structures and feeding platforms could also reduce the number of negative interactions between individuals. Given that ghost bats in the wild are listed as Vulnerable, zoo population management and breeding may form an integral part of conservation planning for this species in the near future. As the first published study of zoo-housed ghost bats, these findings help provide insight into the behaviors and interactions of ghost bats in different social groupings across the breeding and post-breeding seasons.

Zonotopic Kalman Filter-Based Interval Estimation for Discrete-Time Linear Systems With Unknown Inputs

This letter proposes an unknown input zonotopic Kalman filter-based interval observer for discrete-time linear time-invariant systems. In such contexts, a change of coordinates decoupling the state and the unknown inputs is often used. Here, the dynamics are rewritten into a discrete-time linear time-invariant descriptor system by augmenting the state vector with the unknown inputs. A zonotopic outer approximation of the feasible state set is then obtained with a prediction-correction strategy using the information from the system dynamics, known inputs and outputs. Bounds for both the state and unknown inputs are obtained from this zonotopic set. The efficiency of the proposed interval observer is assessed with numerical simulations.

L₁-Robust Interval Observer Design for Uncertain Nonlinear Dynamical Systems

This paper presents a novel interval observer design for uncertain locally Lipschitz continuous-time (CT) and discrete-time (DT) systems with noisy nonlinear observations that is input-to-state stable (ISS) and minimizes the L1-gain of the observer error system with respect to the uncertainties. Using mixed-monotone decompositions, the proposed observer is correct and positive by construction without the need for additional constraints/assumptions. This, in turn, allows us to directly leverage techniques for positive systems to design an ISS and L1-robust interval observer via mixed-integer (linear) programs instead of semi-definite programs with linear matrix inequalities. Further, our observer design offers additional degrees of freedom that may serve as a surrogate for coordinate transformations. Finally, we demonstrate the effectiveness of our proposed observer on some CT and DT systems.

H∞-Optimal Interval Observer Synthesis for Uncertain Nonlinear Dynamical Systems via Mixed-Monotone Decompositions

This paper introduces a novel H&#x221E;-optimal interval observer synthesis for bounded-error/uncertain locally Lipschitz nonlinear continuous-time (CT) and discrete-time (DT) systems with noisy nonlinear observations. Specifically, using mixed-monotone decompositions, the proposed observer is correct by construction, i.e., the interval estimates readily frame the true states without additional constraints or procedures. In addition, we provide sufficient conditions for input-to-state (ISS) stability of the proposed observer and for minimizing the H&#x221E; gain of the framer error system in the form of semi-definite programs (SDPs) with Linear Matrix Inequalities (LMIs) constraints. Finally, we compare the performance of the proposed H&#x221E;-optimal interval observers with some benchmark CT and DT interval observers.

Simultaneous interval state and fault estimation for continuous-time switched systems

This paper deals with simultaneous interval state and fault estimation for continuous-time switched systems subject to unknown but bounded state disturbances. By taking the actuator fault vector as a part of an extended state vector, the original system is transformed into an augmented descriptor system. Under this augmented descriptor form, and by using a new structure of interval observers, the conservatism of observer gain matrices can be significantly reduced. The effect of disturbances is attenuated based on an L∞ approach. Then, the interval observer gains are computed by solving Linear Matrix Inequalities (LMIs) derived from a common Lyapunov function. Finally, a simulation example is given to illustrate the effectiveness of the proposed method.

Bayesian Prediction Intervals Based on Type‐I Hybrid Censored Data from the Lomax Distribution under Step‐Stress Model

The Bayesian prediction of future failures from Lomax distribution is the subject of this research. The observed data is censored using a Type‐I hybrid censoring scheme under a step‐stress partially accelerated life test. There are two types of sampling schemes considered: one‐sample and two‐sample. We create predictive intervals for failure observations in the future. Bayesian prediction intervals are constructed using MCMC algorithms. After all, two numerical examples, simulation study and a real‐life example are provided for both one‐sample and two‐sample methods for the purpose of illustration.

СТРУКТУРУВАННЯ ЕКСПЕРИМЕНТАЛЬНИХ ДАНИХ ПРАЦЕЗДАТНОСТІ АРКОВОГО КРІПЛЕННЯ ДЛЯ ІМОВІРНІСНОЇ ОЦІНКИ СТАНУ ВІДКАТНИХ ШТРЕКІВ

Purpose. Structuring of experimental data of mine observations of the performance of arched flexible supports to establish a probabilistic assessment of the state of haulage drifts of steep coal seams in the excavation areas of a coal mine. Methods. The methodological basis of the research is an integrated approach, including the analysis and generalization of scientific achievements on the problem under study; mine observations of the state of development workings; analytical calculations using the basic provisions of probability theory, mathematical statistics using differential equations. Results. A probabilistic assessment of the state of the haulage drift under different protection methods, used to predict the stability of section development workings, was obtained from the experimental data of mine observations (observation time t = 4280 hours) of the performance of the arched pliable lining installed in the working along the length of the excavation section. After the sample was formed, the calculation of a statistical assessment of the reliability of the support operation was performed: the indicators of the failure rate λ and the recovery rate μ were established. Dependencies are obtained that allow assessing the state of development workings along the length of the excavation section and in the zone of influence of the stopping operations. It is proved that in the steady mode of operation of the haulage drift, with an increase in the failure rate of the arch support by 5 times, the availability factor, as a function of the reliability and maintainability of the support, changes from 0.9 to 0.5, which leads to a deterioration in time, approximately by 60 %, operational characteristics of the support in the supported development. Novelty. The probabilistic assessment of the loss of stability of the haulage drift along the length of the excavation section is based on the structuring of the data on the performance of arched supports and depends on the method of protection of the working, the intensity of failures of the arched supple support and the frequency of its damage, when in the desired interval of observations when forming the sample, the position of the stopping front is taken into account. Practical relevance. For the reuse of development workings with a store method of preparing steep seams and a descending order of mining floors, a conceptual model is proposed that allows predicting the state of haulage drifts along the length of the excavation area, taking into account the method of protection.

РАЗРАБОТКА ТЕХНОЛОГИИ ВИРТУАЛЬНОЙ РЕАЛЬНОСТИ VR-PACE ДЛЯ ДИАГНОСТИКИ И ТРЕНИРОВКИ УРОВНЯ МАСТЕРСТВА ХОККЕИСТОВ

Relevance: in the last decade, virtual reality (VR) technologies have been actively introduced into the training process in various types of sprints. At the same time, there are studies showing the inconsistency of VR for the formation of sports skills and their transfer to real conditions. But despite this, the use of VR can be useful for practicing specifi c motor skills and cognitive functions, for example, anticipation. Objective: to develop VR-PACE technology (VR Technology for training Puck hitting And HOSKE skill Eff ectiveness) using virtual reality aimed at diagnosing and analyzing the skill level of a hockey player, as well as their training. Methods: within the framework of the study, a simulation virtual environment was developed that simulates a hockey fi eld (ice arena in Sochi) and sets four diffi culty levels (four blocks) depending on the speed of the puck and the distance to it. Th e study involved 22 people, 13 of whom were professional hockey players (Mage = 20 ± 2.5), and seven were beginners in hockey (Mage = 20 ± 1.4). Results: it was found that professional hockey players have a signifi cantly smaller amplitude of head vibrations during the refl ection of pucks, that is, they understand the position of their body well enough during certain actions, and they do not need to observe the full trajectory of the puck. Th ere were also signifi cant diff erences in the speed of response to the presented washers in the block with the fastest speed of presentation of 2 washers. Th e results obtained may indicate a better formation of technical and tactical, temporal and spatial factors in professional hockey players. Conclusions: the adequacy of the developed tools for the analysis of professional skills of hockey players was demonstrated. It was also shown that the skill level of a hockey player is determined by the formation of a set of parameters, including spatial, temporal, technical and tactical abilities. Th is is manifested in the automation of a number of skills, as well as the optimization of motor responses: 1) higher and more stable amplitude of movements over the entire observation interval and minimization of unnecessary movements; 2) higher reaction speed to more complex pucks (close to real game situations); 3) concentration of attention on signifi cant signals, anticipation.

Interval observer based control via event-triggered scheme: from single harmonic oscillator to the coupled ones

Interval observer based control via event-triggered scheme: from single harmonic oscillator to the coupled ones