Finite-time Prescribed Performance Time-Varying Formation Control for Second-Order Multi-Agent Systems With Non-Strict Feedback Based on a Neural Network Observer

This paper studies the problem of time-varying formation control with finite-time prescribed performance for nonstrict feedback second-order multi-agent systems with unmeasured states and unknown nonlinearities.To eliminate nonlinearities,neural networks are applied to approximate the inherent dynamics of the system.In addition,due to the limitations of the actual working conditions,each follower agent can only obtain the locally measurable partial state information of the leader agent.To address this problem,a neural network state observer based on the leader state information is designed.Then,a finite-time prescribed performance adaptive output feedback control strategy is proposed by restricting the sliding mode surface to a prescribed region,which ensures that the closed-loop system has practical finite-time stability and that formation errors of the multi-agent systems converge to the prescribed performance bound in finite time.Finally,a numerical simulation is provided to demonstrate the practicality and effectiveness of the developed algorithm.

Currencies of greater interest for central Asian economies:an analysis of exchange market pressure amid global and regional interdependence

Central Asian Economies(CAEs)have diverse exchange rate policies.They have recorded higher volatility in the foreign exchange market since inception.High volatility of the transition era has drifted these economies towards partial dollarization.Monetary authorities in CAEs,(already have a challenge of maintaining monetary policy autonomy)have a gigantic task of price stability and stopping the spread of dollarization.This study is directed towards assessing the drivers and the determinants of foreign exchange market pressure in CAEs.The results,based on panel data analysis and the System GMM model,have provided useful insights about the exchange market pressure determinants particularly USD,Euro,Ruble,and Renminbi.The results show that China and Russia exchange market pressure has a negative effect on the exchange market pressure of CAEs.While the dollar index shows a positive impact on the exchange market pressure of CAEs.Overall,the findings imply that China and Russia currency appreciation results in a trade deficit across CAEs.The policy implication suggests that the floating exchange rate regime(inflation targeting regime)is not in favor of CAEs,and they must use managed-float to reduce their trade deficits.

Complementary-Label Adversarial Domain Adaptation Fault Diagnosis Network under Time-Varying Rotational Speed and Weakly-Supervised Conditions

Recent research in cross-domain intelligence fault diagnosis of machinery still has some problems,such as relatively ideal speed conditions and sample conditions.In engineering practice,the rotational speed of the machine is often transient and time-varying,which makes the sample annotation increasingly expensive.Meanwhile,the number of samples collected from different health states is often unbalanced.To deal with the above challenges,a complementary-label(CL)adversarial domain adaptation fault diagnosis network(CLADAN)is proposed under time-varying rotational speed and weakly-supervised conditions.In the weakly supervised learning condition,machine prior information is used for sample annotation via cost-friendly complementary label learning.A diagnosticmodel learning strategywith discretized category probabilities is designed to avoidmulti-peak distribution of prediction results.In adversarial training process,we developed virtual adversarial regularization(VAR)strategy,which further enhances the robustness of the model by adding adversarial perturbations in the target domain.Comparative experiments on two case studies validated the superior performance of the proposed method.

On the Application of Mixed Models of Probability and Convex Set for Time-Variant Reliability Analysis

In time-variant reliability problems,there are a lot of uncertain variables from different sources.Therefore,it is important to consider these uncertainties in engineering.In addition,time-variant reliability problems typically involve a complexmultilevel nested optimization problem,which can result in an enormous amount of computation.To this end,this paper studies the time-variant reliability evaluation of structures with stochastic and bounded uncertainties using a mixed probability and convex set model.In this method,the stochastic process of a limit-state function with mixed uncertain parameters is first discretized and then converted into a timeindependent reliability problem.Further,to solve the double nested optimization problem in hybrid reliability calculation,an efficient iterative scheme is designed in standard uncertainty space to determine the most probable point(MPP).The limit state function is linearized at these points,and an innovative random variable is defined to solve the equivalent static reliability analysis model.The effectiveness of the proposed method is verified by two benchmark numerical examples and a practical engineering problem.

Time-dependent model for two-phase flow in ultra-high water-cut reservoirs:Time-varying permeability and relative permeability

For the ultra-high water-cut reservoirs,after long-term water injection exploitation,the physical properties of the reservoir change and the heterogeneity of the reservoir becomes increasingly severe,which further aggravates the spatial difference of the flow field.In this study,the displacement experiments were employed to investigate the variations in core permeability,porosity,and relative permeability after a large amount of water injection.A relative permeability endpoint model was proposed by utilizing the alternating conditional expectation(ACE)transformation to describe the variation in relative permeability based on the experimental data.Based on the time dependent models for permeability and relative permeability,the traditional oil-water two-phase model was improved and discretized using the mimetic finite difference method(MFD).The two cases were launched to confirm the validation of the proposed model.The impact of time-varying physical features on reservoir production performance was studied in a real water flooding reservoir.The experimental results indicate that the overall relative permeability curve shifts to the right as water injection increases.This shift corresponds to a transition towards a more hydrophilic wettability and a decrease in residual oil saturation.The endpoint model demonstrates excellent accuracy and can be applied to time-varying simulations of reservoir physics.The impact of variations in permeability and relative permeability on the reservoir production performance yields two distinct outcomes.The time-varying permeability of the reservoir results in intensified water channeling and poor development effects.On the other hand,the time-varying relative permeability enhances the oil phase seepage capacity,facilitating oil displacement.The comprehensive time-varying behavior is the result of the combined influence of these two parameters,which closely resemble the actual conditions observed in oil field exploitation.The time-varying simulation technique of reservoir physical properties proposed in this paper can continuously and stably characterize the dynamic changes of reservoir physical properties during water drive development.This approach ensures the reliability of the simulation results regarding residual oil distribution.

Nuclear magnetic resonance experiments on the time-varying law of oil viscosity and wettability in high-multiple waterflooding sandstone cores

A simulated oil viscosity prediction model is established according to the relationship between simulated oil viscosity and geometric mean value of T2spectrum,and the time-varying law of simulated oil viscosity in porous media is quantitatively characterized by nuclear magnetic resonance(NMR)experiments of high multiple waterflooding.A new NMR wettability index formula is derived based on NMR relaxation theory to quantitatively characterize the time-varying law of rock wettability during waterflooding combined with high-multiple waterflooding experiment in sandstone cores.The remaining oil viscosity in the core is positively correlated with the displacing water multiple.The remaining oil viscosity increases rapidly when the displacing water multiple is low,and increases slowly when the displacing water multiple is high.The variation of remaining oil viscosity is related to the reservoir heterogeneity.The stronger the reservoir homogeneity,the higher the content of heavy components in the remaining oil and the higher the viscosity.The reservoir wettability changes after water injection:the oil-wet reservoir changes into water-wet reservoir,while the water-wet reservoir becomes more hydrophilic;the degree of change enhances with the increase of displacing water multiple.There is a high correlation between the time-varying oil viscosity and the time-varying wettability,and the change of oil viscosity cannot be ignored.The NMR wettability index calculated by considering the change of oil viscosity is more consistent with the tested Amott(spontaneous imbibition)wettability index,which agrees more with the time-varying law of reservoir wettability.

Numerical Simulation of Slurry Diffusion in Fractured Rocks Considering a Time-Varying Viscosity

To analyze the effects of a time-varying viscosity on the penetration length of grouting,in this study cement slur-ries with varying water-cement ratios have been investigated using the Bingham’sfluidflow equation and a dis-crete element method.Afluid-solid coupling numerical model has been introduced accordingly,and its accuracy has been validated through comparison of theoretical and numerical solutions.For different fracture forms(a single fracture,a branch fracture,and a fracture network),the influence of the time-varying viscosity on the slurry length range has been investigated,considering the change in the fracture aperture.The results show that under different fracture forms and the same grouting process conditions,the influence of the time-varying viscosity on the seepage length is 0.350 m.

Adaptive Event-Triggered Time-Varying Output Group Formation Containment Control of Heterogeneous Multiagent Systems

In this paper,a class of time-varying output group formation containment control problem of general linear hetero-geneous multiagent systems(MASs)is investigated under directed topology.The MAS is composed of a number of tracking leaders,formation leaders and followers,where two different types of leaders are used to provide reference trajectories for movement and to achieve certain formations,respectively.Firstly,compen-sators are designed whose states are estimations of tracking lead-ers,based on which,a controller is developed for each formation leader to accomplish the expected formation.Secondly,two event-triggered compensators are proposed for each follower to evalu-ate the state and formation information of the formation leaders in the same group,respectively.Subsequently,a control protocol is designed for each follower,utilizing the output information,to guide the output towards the convex hull generated by the forma-tion leaders within the group.Next,the triggering sequence in this paper is decomposed into two sequences,and the inter-event intervals of these two triggering conditions are provided to rule out the Zeno behavior.Finally,a numerical simulation is intro-duced to confirm the validity of the proposed results.

Set-Membership Filtering Approach to Dynamic Event-Triggered Fault Estimation for a Class of Nonlinear Time-Varying Complex Networks

The present study addresses the problem of fault estimation for a specific class of nonlinear time-varying complex networks,utilizing an unknown-input-observer approach within the framework of dynamic event-triggered mechanism(DETM).In order to optimize communication resource utilization,the DETM is employed to determine whether the current measurement data should be transmitted to the estimator or not.To guarantee a satisfactory estimation performance for the fault signal,an unknown-input-observer-based estimator is constructed to decouple the estimation error dynamics from the influence of fault signals.The aim of this paper is to find the suitable estimator parameters under the effects of DETM such that both the state estimates and fault estimates are confined within two sets of closed ellipsoid domains.The techniques of recursive matrix inequality are applied to derive sufficient conditions for the existence of the desired estimator,ensuring that the specified performance requirements are met under certain conditions.Then,the estimator gains are derived by minimizing the ellipsoid domain in the sense of trace and a recursive estimator parameter design algorithm is then provided.Finally,a numerical example is conducted to demonstrate the effectiveness of the designed estimator.

Identification of time-varying system and energy-based optimization of adaptive control in seismically excited structure

The combination of structural health monitoring and vibration control is of great importance to provide components of smart structures.While synthetic algorithms have been proposed,adaptive control that is compatible with changing conditions still needs to be used,and time-varying systems are required to be simultaneously estimated with the application of adaptive control.In this research,the identification of structural time-varying dynamic characteristics and optimized simple adaptive control are integrated.First,reduced variations of physical parameters are estimated online using the multiple forgetting factor recursive least squares(MFRLS)method.Then,the energy from the structural vibration is simultaneously specified to optimize the control force with the identified parameters to be operational.Optimization is also performed based on the probability density function of the energy under the seismic excitation at any time.Finally,the optimal control force is obtained by the simple adaptive control(SAC)algorithm and energy coefficient.A numerical example and benchmark structure are employed to investigate the efficiency of the proposed approach.The simulation results revealed the effectiveness of the integrated online identification and optimal adaptive control in systems.

Time-varying parameters estimation with adaptive neural network EKF for missile-dual control system

In this paper, a filtering method is presented to estimate time-varying parameters of a missile dual control system with tail fins and reaction jets as control variables. In this method, the long-short-term memory(LSTM) neural network is nested into the extended Kalman filter(EKF) to modify the Kalman gain such that the filtering performance is improved in the presence of large model uncertainties. To avoid the unstable network output caused by the abrupt changes of system states,an adaptive correction factor is introduced to correct the network output online. In the process of training the network, a multi-gradient descent learning mode is proposed to better fit the internal state of the system, and a rolling training is used to implement an online prediction logic. Based on the Lyapunov second method, we discuss the stability of the system, the result shows that when the training error of neural network is sufficiently small, the system is asymptotically stable. With its application to the estimation of time-varying parameters of a missile dual control system, the LSTM-EKF shows better filtering performance than the EKF and adaptive EKF(AEKF) when there exist large uncertainties in the system model.

Time-Varying Mesh Stiffness Calculation and Dynamic Modeling of Spiral Bevel Gear with Spalling Defects

Time-varying mesh stiffness(TVMS)is a vital internal excitation source for the spiral bevel gear(SBG)transmission system.Spalling defect often causes decrease in gear mesh stiffness and changes the dynamic characteristics of the gear system,which further increases noise and vibration.This paper aims to calculate the TVMS and establish dynamic model of SBG with spalling defect.In this study,a novel analytical model based on slice method is proposed to calculate the TVMS of SBG considering spalling defect.Subsequently,the influence of spalling defect on the TVMS is studied through a numerical simulation,and the proposed analytical model is verified by a finite element model.Besides,an 8-degrees-of-freedom dynamic model is established for SBG transmission system.Incorporating the spalling defect into TVMS,the dynamic responses of spalled SBG are analyzed.The numerical results indicate that spalling defect would cause periodic impact in time domain.Finally,an experiment is designed to verify the proposed dynamic model.The experimental results show that the spalling defect makes the response characterized by periodic impact with the rotating frequency of spalled pinion.

New text classification algorithm based on interdependence and equivalent radius

To improve the traditional classifying methods, such as vector space model （VSM）-based methods with highly complicated computation and poor scalability, a new classifying method （ called IER） is presented based on two new concepts： interdependence and equivalent radius. In IER, the attribute is selected according to the value of interdependence, and the classifying rule is based on equivalent radius and center of gravity. The algorithm analysis shows that IER is good at classifying a large number of samples with higher scalability and lower computation complexity. After several experiments in classifying Chinese texts, the conclusion is drawn that IER outperforms k-nearest neighbor （kNN） and classifcation based on the center of classes （CCC） methods, so IER can be used online to automatically classify a large number of samples while keeping higher precision and recall.

Effect of Starch/Polylactic Acid Ratio on the Interdependence of Two-Phase and the Properties of Composites

Starch/polylactic acid(PLA) composites were prepared by melt extrusion, with corn starch and PLA as raw materials, glycerol as the plasticizer. Effects of starch/PLA ratio on the interdependence of two-phase and other properties of the composites were studied. The combination of results of TGA with SEM indicated that the interdependence between starch and PLA was increased gradually as the starch/PLA ratio reduced. DSC results showed that the glass transition temperature(Tg), melting temperature(Tm) and degree of crystallinity of PLA in composites were increased gradually, whereas the cold crystallization temperature(Tc) was gradually decreased as the starch/PLA ratio reduced. The rheological properties of composites were closely related with the interdependence of two-phase, with reducing starch/PLA proportion, the interdependence was increased, and then the strain for storage modulus was firstl reduced and then gradually increased. Frequency scanning showed that the storage modulus and complex viscosity were decreased with reducing starch content. As the starch/PLA ratio reduced, the matrix phase PLA was increased, so that the strength of composites was increased gradually, whereas water absorption rate was decreased gradually.

Time-variant fragility analysis of the bridge system considering time-varying dependence among typical component seismic demands

This paper presents a copula technique to develop time-variant seismic fragility curves for corroded bridges at the system level and considers the realistic time-varying dependence among component seismic demands. Based on material deterioration mechanisms and incremental dynamic analysis, the time-evolving seismic demands of components were obtained in the form of marginal probability distributions. The time-varying dependences among bridge components were then captured with the best fitting copula function, which was selected from the commonly used copula classes by the empirical distribution based analysis method. The system time-variant fragility curves at different damage states were developed and the effects of time-varying dependences among components on the bridge system fragility were investigated. The results indicate the time-varying dependence among components significantly affects the time-variant fragility of the bridge system. The copula technique captures the nonlinear dependence among component seismic demands accurately and easily by separating the marginal distributions and the dependence among them.

Regional Interdependence: A Model That Needs to Be Integrated in the Functional Evaluation and Physiotherapy Treatment—Part 1

Background: Rehabilitation is increasing the need to use codes in order to make both a functional diagnosis and a therapeutic intervention as correct and targeted as possible. Thus, it is very important to integrate the model of Regional Interdependence (RI) in the classical rehabilitation evaluation methods, since it will be of help for understanding, solving dysfunctional problems, and improving the patient management, which is often difficult given the fact that there is no concordance on functional tests and timing of treatments. The RI should be added to the functional evaluation each time that a patient presents symptoms in a specific location, which interest also distal regions. This is due to the functional and anatomical connections of the myofascial system, vascular, autonomic nervous system (ANS), the peripheral nervous system (PNS) and the neuro-immunoendocrine system. The RI can be summarized into three groups that are correlated when it comes to applying it practically: upper, bottom and front quadrant. Adding the concept of RI to the clinical and therapeutically practice, it would have positive effects on improving the quality of life and allocate better health’s resources. The aim of this paper is to make the functional assessment in clinical practice faster and more standardized.

Autonomy and interdependence: quandaries in research ethics

The autonomy of research participants is crucial in research ethics without which it will be difficult to carry out research. Central to the concept of autonomy is the debate on whether the cultural norms of individuals (particularly women) should be given priority in settings where these norms require that researchers should go through male heads such as husbands and traditional leaders. This paper examines issues relating to the autonomy of women in research ethics. It highlights the far-reaching implications of autonomy for women participating in research using Islam as a religion and Africa as case studies. The paper takes a look at what obtains in Ghana and Nigeria as African countries with diverse religious sects highlighting at the same time the extent to which women are autonomous in some Islamic parts of India and Pakistan. The paper stresses that in spite of certain factors limiting the autonomy of women in Africa and Islam, there is need for a more robust account of autonomy. It takes a relational approach to autonomy concluding at the same time that the best way to do bioethics is to be culture-sensitive.

Resilient Time-Varying Formation-Tracking of Multi-UAV Systems Against Composite Attacks: A Two-Layered Framework

This paper studies the countermeasure design problems of distributed resilient time-varying formation-tracking control for multi-UAV systems with single-way communications against composite attacks,including denial-of-services(DoS)attacks,false-data injection attacks,camouflage attacks,and actuation attacks(AAs).Inspired by the concept of digital twin,a new two-layered protocol equipped with a safe and private twin layer(TL)is proposed,which decouples the above problems into the defense scheme against DoS attacks on the TL and the defense scheme against AAs on the cyber-physical layer.First,a topologyrepairing strategy against frequency-constrained DoS attacks is implemented via a Zeno-free event-triggered estimation scheme,which saves communication resources considerably.The upper bound of the reaction time needed to launch the repaired topology after the occurrence of DoS attacks is calculated.Second,a decentralized adaptive and chattering-relief controller against potentially unbounded AAs is designed.Moreover,this novel adaptive controller can achieve uniformly ultimately bounded convergence,whose error bound can be given explicitly.The practicability and validity of this new two-layered protocol are shown via a simulation example and a UAV swarm experiment equipped with both Ultra-WideBand and WiFi communication channels.

Adversarial Training-Aided Time-Varying Channel Prediction for TDD/FDD Systems

In this paper, a time-varying channel prediction method based on conditional generative adversarial network(CPcGAN) is proposed for time division duplexing/frequency division duplexing(TDD/FDD) systems. CPc GAN utilizes a discriminator to calculate the divergence between the predicted downlink channel state information(CSI) and the real sample distributions under a conditional constraint that is previous uplink CSI. The generator of CPcGAN learns the function relationship between the conditional constraint and the predicted downlink CSI and reduces the divergence between predicted CSI and real CSI.The capability of CPcGAN fitting data distribution can capture the time-varying and multipath characteristics of the channel well. Considering the propagation characteristics of real channel, we further develop a channel prediction error indicator to determine whether the generator reaches the best state. Simulations show that the CPcGAN can obtain higher prediction accuracy and lower system bit error rate than the existing methods under the same user speeds.

Use of fractal geometry to propose a new mechanism of airway-parenchymal interdependence

The topic of airway-parenchymal interdependence (API) is of great importance to those interested in identifying factors that influence airway patency. A carefully designed experiment has raised questions about the classical concept of API. This paper proposes a new mechanism of API. The pulmonary lobe is an aggregated body consisting of many Miller’s lobular polyhedrons and a fractal bronchial tree. The fractal cartilaginous bronchial tree was assumed to be characterized by both Horton’s ratio (Lj+1/Lj=2λ, where Lj+1, and Lj denote the mean lengths of branches at Horsfield’ order of j + 1 and j) and power laws between diameters and lengths of branches. Fluid dynamic parameters of fractal trees were assumed to be interrelated among powers and λ. A non-cartilaginous lobular bronchiole is adjoined to the edge of a lobular polyhedron, and is encircled by an inextensible basement membrane to reflect a reversible relationship of rlLl = constant(c), where rl and Ll denote the diameter and the length of a lobular bronchiole, respectively. API at the level of the lobu-lar bronchiole was described by log(rl) = -(1+λ)/(1+5λ)log(hl/c), where rl and hl denote the diameter of the lobular bronchiole and the parenchymal parameter relating the size of the lobular polyhedron, respectively. If the distribution in sizes of the lobular polyhedrons was described by a Weibull’s probability density function characterized by the shape parameter m as well as the fractal parameter λ = 0.5, the diameter R of a cartilaginous bronchial branch was determined by log(R) = F - 3/7log(h/c), where F(m) denotes a function of m, and h denotes the mean size of the polyhedrons in the lobe. As a conclusion, API can be described by a combination of both lobular API and corresponding adaptive changes in the degree of contraction of airway smooth muscles.