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In this paper, we investigate the exponential synchronization problem for multi-link and multi-delayed inertial neural networks with Markov jump (MMDINNMJ) using an aperiodically intermittent adaptive control strategy. Different from most research on inertial neural networks, we take multi-link, multi-delay and Markov jump into account. The obstacle caused by the coexistence of Markov jump and multi-delay is avoided by using the delayed integral method while considering the exponential synchronization of MMDINNMJ. Additionally, under graph theory, Lyapunov stability theory and the developed control scheme, some novel sufficient conditions for synchronization at exponential rate in p th (p > 0) moment of underlying networks are determined, which are strongly related to multi-link topological structure, time delay, and Markov jump. Finally, two examples are given to demonstrate the viability of the theoretical conclusions. [ABSTRACT FROM AUTHOR]

In this paper we consider a class of nonlinear BVP involving fractional derivative in the ψ -Riemann–Liouville sense with nonlocal boundary conditions. By means of some properties of the Green's function and fixed point theorems due to Banach, Boyd-Wong, and Rus, existence of a unique solution is obtained. We have some examples that prove the theory is true. [ABSTRACT FROM AUTHOR]

The aim of this paper is to investigate the role of plankton populations in the aquatic reservoir on the transmission dynamics of acute cholera within the human communities. To this, we develop a nonlinear six dimensional mathematical model that combines the plankton populations with the epidemiological SIR-type human subpopulations and the V. cholerae bacterial population in the aquatic reservoir. It is assumed that the susceptible humans become infected either by ingesting zooplankton, which serves as a reservoir for the cholera pathogen, by free-living V. cholerae in the water, or by cholera-infected individuals. We explore the existence and stability of all biologically plausible equilibria of the system. Also, we determine basic reproduction number (R 0) and introduced an additional threshold, named planktonic factor (E 0), that is found to significantly affect the cholera transmission. Furthermore, cholera-free equilibrium encounters transcritical bifurcation at R 0 = 1 within the planktonic factor's unitary range. We perform some sensitivity tests to determine how the epidemic thresholds R 0 and E 0 will respond to change in the parametric values. The existence of saddle–node bifurcation is shown numerically. Our findings reveal that there are strong connections between the planktonic blooms and the cholera epidemic. We observe that even while eliminating cholera from the human population is very difficult, we may nevertheless lessen the epidemic condition by enhancing immunization, treatment and other preventive measures. [ABSTRACT FROM AUTHOR]

The present paper aims to develop a stable multistep numerical scheme for the non-linear generalized time-fractional diffusion equations (GTFDEs) with non-smooth solutions. Mesh grading technique is used to discretize the temporal direction, which results in 2 − α order of convergence (0 < α < 1). The spatial direction is discretized using a second order difference operator and the non-linear term is approximated using Taylor's series. Theoretical stability and convergence analysis is established in the L 2 -norm. Moreover, some random noise perturbations are added to investigate the numerical stability of the developed scheme. Finally, numerical simulations are performed on three test examples to verify the robustness and efficiency of the scheme. [ABSTRACT FROM AUTHOR]

Proposing new metaheuristic methods is crucial for continuous algorithmic improvement and the ability to effectively address increasingly complex real-world optimization problems. On the other hand, Evolutionary Game Theory analyzes how trough competition is possible to modify the strategies of individuals within a population in order to spread successful mechanisms and reduce or remove less successful strategies. This paper introduces a novel optimization approach based on the principles of evolutionary game theory. In the proposed method, all individuals are initialized using the Metropolis–Hasting technique, which sets the solutions at a starting point closer to the optimal or near-optimal regions of the problem. An original strategy is then assigned to each individual in the population. By considering the interactions and competition among different agents in the optimization problem, the approach modifies the strategies to improve search efficiency and find better solutions. To evaluate the performance of the proposed technique, it is compared with eight well-known metaheuristic algorithms using 30 benchmark functions. The proposed methodology demonstrated superiority in terms of solution quality, dimensionality, and convergence when compared to other approaches. [ABSTRACT FROM AUTHOR]

In this paper, a linearized numerical scheme of nonlinear variable-order fractional diffusion equation with time delay is constructed. We apply the L 2 − 1 σ formula to discretize the temporal derivative and second-order central difference scheme to discretize the spatial derivative. The proposed method is unconditionally stable and convergent with O τ 2 + h 2 , where τ and h are the time and space steps, respectively. Numerical experiment demonstrates the effectiveness and accuracy of the numerical scheme. [ABSTRACT FROM AUTHOR]

The dissemination of public health information through television and social media posts is essential for informing the public about the transmission of contagious diseases, which is crucial in preventing the spread of various infectious diseases. In this paper, we propose a non-linear mathematical model to assess the effect of advertisements through social media in creating awareness and limiting treatment on spreading infectious diseases. These initiatives may alter population behaviour and divide the susceptible population into subgroups. In addition, to comprehend these dynamics better, we use half-saturation constant rates for media coverage and treatment. The model's well-posedness and feasibility are evaluated. The possible biological equilibrium points are calculated. Local and global stability are carried out. The objective of our study is to produce the model's bifurcation. Transcritical, Saddle–node, Hopf bifurcation of codimension 1 and Cusp, Generalized-Hopf (Bautin), and Bogdanov–Takens (BT) bifurcation of codimension 2 are studied for this purpose. Due to the limited medical resources and supply efficiency, the model exhibits backward bifurcation, resulting in bistability. Moreover, the occurrence condition for stability and direction of Hopf bifurcation is discussed. This model study demonstrates that the system is significantly influenced by the pace with which awareness programmes are implemented and that raising this value above a threshold may result in continuous oscillation. Sensitivity analysis employs the normalized forward sensitivity index of the basic reproduction number to provide a comprehensive understanding of the effect of various parameters on accelerating and limiting disease spread. Further, the minimum possible cost is determined by formulating an optimal control system based on sensitivity analysis and applying Pontryagin's maximum principle. Methods of cost-effectiveness, such as ACER and ICER, are used to determine the most cost-effective control intervention strategy among all the strategies. Numerical simulations have been done to support all theoretical findings. • A non-linear model is proposed to assess the effect of advertisements through social media and limiting treatment on infectious diseases. • Due to backward bifurcation, R 0 ¡ 1 is insufficient to eliminate the sickness, and additionally, the model displays Hopf, Saddle–node, Bogdanov–Takens, and Generalized Hopf bifurcation. • Strategies having the highest infection-averted capacity using treatment and media implementation as control parameters are obtained. • Different control techniques are compared using numerical simulation, and sensitivity analysis is used to determine the appropriate control parameter. • Using method like ACER and ICER, we determine the most cost-effective strategy. [ABSTRACT FROM AUTHOR]

In this paper, stochastic predictive computing networks are exploited to investigate the dynamics of the SIS with vaccination impact based epidemic model (SISV-EM) represented by nonlinear systems of stochastic differential equations (SDEs) by exploitation of artificial neural networks (ANNs) with the backpropagated Levenberg-Marquardt technique (BLMT) i.e., (ANNs-BLMT) to approximate the solution behavior. The stochastic nonlinear SISV-EM is governed with three classes: susceptible, infectious, and vaccinated populations. The referenced or target datasets for ANNs-BLMT are constructed by employing Euler-Maruyama (EM) scheme for solving stochastic differential systems in case of sufficiently various nonlinear SISV-EM scenarios by varying the percentage of vaccination for newly born, the coefficient of transmission, the natural mortality rates, the infectious rates of recovery, the rate at which vaccinated people lose their immunity, the rate of death caused by disease, the proportion of vaccinated against susceptible and the white noise in the environment. Based on arbitrary training, testing, and validation samples from the referenced dataset, the ANNs-BLMT provides an approximate solution for the stochastic nonlinear SISV-EM, with significant correlations to the referenced results. Exhaustive simulation-based results using error histograms, mean square errors, and regression analyses further demonstrate that the proposed ANNs-BLMT is efficient, consistent, and accurate for solving SISV-EM. • A two-layer framework of ANNs-BLMT is proposed as an innovative technique based on a stochastic computing paradigm to investigate the dynamics of stochastic nonlinear SISV-EM. • Innovative technique based on a stochastic computing ANNs-BLMT to investigate the dynamics of stochastic nonlinear SISV-EM Reference dataset for ANNs -BLMT is developed with Euler-Maruyama (EM) scheme nonlinear SISV-EM with varying parametersMean square error criteria is used for training of ANNs-BLMT to find approximate solutions to a variety of SISV-EM scenarios Computation of error histogram illustration, regression metrics, and MSE learning curves prove the performance of ANNs-BLMT. • The mean square error criteria are effectively utilized in approximation theory to develop an objective function for training the ANNs-BLMT to determine approximate solutions to a variety of stochastic nonlinear SISV-EM scenarios. • The computation of error histogram illustration, regression metrics, and MSE learning curves significantly improve the performance, precision, and consistency of the ANNs-BLMT for solving the stochastic nonlinear SISV-EM. [ABSTRACT FROM AUTHOR]

The existing chaotic systems exhibit chaos degradation phenomena because of the limited chaotic precision in the real number field. In response to this deficiency, this paper proposes a chaotic bits XOR system (CBXS) in the integer field satisfying Devaney's chaos. That is, CBXS has the property of sensitivity of initial value, topological transitivity, and periodic point density. Then, a series of chaotic and random test results illustrate that the sequences generated by CBXS with linear feedback shift register (LFSR) in the finite field G F (2) have good random and chaotic performance. It can overcome the chaos degradation problem because it is generated in the integer field and can avoid the limited precision in the real number field. Finally, we employ the proposed CBXS to image encryption with the optimized Arnold's transformation. The experimental results verify that even after simple encryption, the cipher image still exhibits good encryption effect and efficiency, which illustrates the effectiveness of CBXS. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the pricing of European crude oil options under nonlinear dynamics with stochastic behaviour and jump risks, incorporating the features of arising convenience yield of crude oil and potential extreme fluctuation in the dynamics of crude oil prices. We present a closed-form solution to European crude oil option prices under an incomplete market setting, after deriving the pricing kernel with the equilibrium method and determining the risk neutral dynamics of crude oil prices. We extend our model to a mean-reverting stochastic volatility case, which also admits an analytical formula for the equilibrium price of European crude-oil options. Finally, our model is shown to be consistent with a number of interesting facts documented in the recent literature. [ABSTRACT FROM AUTHOR]

In this paper, a cortex-basal ganglia model about Parkinson's disease with two time delays is studied, and the critical conditions for Hopf bifurcation are derived. The results show that time delays can change the state of basal ganglia. The basal ganglia is stable when the delays are small. However, when the time delay is greater than the corresponding bifurcation critical point, different types of oscillations occur in the basal ganglia. The larger the time delays, the more active the neuronal clusters in the basal ganglia. Furthermore, the bidirectional Hopf bifurcation is found by studying the connection weights between different neural nuclei. Finally, the influence of connection weight and time delay which are related to the internal segment of the globus pallidus on its oscillation is discussed. Research shows that reducing the connection weight and the corresponding time delay in excitatory neuronal clusters, or increasing the connection weight and decreasing the corresponding time delay in inhibitory neuronal clusters, can improve the oscillation of Parkinson's disease. [ABSTRACT FROM AUTHOR]

This paper studies the dynamic output feedback (OF) control problem for unmanned aerial vehicles (UAVs) with limited network bandwidth by a genetic-algorithm-assisted design approach. In order to make full use of the limited network bandwidth, only partial measurement information is transmitted to the controller via the sensor-to-controller network. Round-Robin protocol is introduced to administrate the transmission rule. Sufficient conditions are presented to make sure that the closed-loop UAV system is exponentially stable with the required L 2 -gain performance. However, due to the nonlinear coupling terms of the dynamic OF controller parameters and some redundant variables in the system modeling, the established conditions are non-convex and difficult to be solved. Fortunately, genetic algorithms (GA) show good performance in solving optimization problem with nonlinear and non-convex constraints. Therefore, this paper skillfully combines GA with linear matrix inequality techniques to solve the established conditions. Finally, all the dynamic OF controller parameters and the minimal L 2 -gain can be obtained simultaneously. At the end of this paper, an UAV networked control example and a numerical example are performed to verify the effectiveness and superiorities of our method. [ABSTRACT FROM AUTHOR]

This study builds on a recent paper by Lai et al. (2018) in which a novel boundary integral formulation is presented for scalar wave scattering analysis in two-dimensional layered and half-spaces. The seminal paper proposes a hybrid integral representation that combines the Sommerfeld integral and layer potential to efficiently deal with the boundaries of infinite length. In this work, we modify the integral formulation to eliminate the fictitious eigenvalues by employing the integral equation of the Burton–Miller type. We also discuss reasonable parameter settings for the hybrid integral equation to ensure efficient and accurate numerical solutions. Furthermore, we extend the modified formulation for the scattering from a cavity in a half-space whose boundary is locally perturbed. To address the cavity scattering, we introduce a virtual boundary enclosing the cavity and couple the integral equation on it with the hybrid equation. The effectiveness of the proposed method is demonstrated through numerical examples. [ABSTRACT FROM AUTHOR]

This paper presents the regularization of the parametric integral equation system (PIES) and the integral identity for 2D problems governed by the Laplace equation in polygonal and smooth domains. Due to the singularity of PIES and the existence of near-singularities in the integral identity, significant errors occur in the results near the boundary, even in the case of smooth boundaries. Additionally, polygonal domains have corner points where the boundary is not smooth, resulting in even greater errors when finding solutions within the domain near these points. These errors increase significantly as the distance to the corner points decreases. The purpose of the presented regularization is to eliminate singularities in PIES and nearly singularities in the integral identity that occur near the boundary, thus improving the accuracy of solutions. The main idea of the regularization is to introduce a regularizing function with two unknown regularization coefficients that need to be determined. As a result, the modified PIES and the integral identity become nonsingular. The paper includes several numerical examples with boundaries described by Bézier and NURBS curves that demonstrate the reliability of the regularization approach and highlight significant improvements in accuracy near the boundary and corner points. [ABSTRACT FROM AUTHOR]

This paper proposes a novel procedure for discretizing uncertain time-invariant continuous-time linear systems in polytopic domains. The approach is based on multistep method theory and involves mixing models obtained with different multiples of a fixed step-size (sampling time), thereby increasing data availability. An optimization procedure is employed to determine the coefficients that minimize the residual discretization error, and then these coefficients are combined to construct an augmented structure for the discrete-time system. The discretization error is computed using a grid search and incorporated into the discrete-time system formulation. Using the resulting discrete-time system, a state feedback methodology is applied to synthesize digital controllers capable of stabilizing the original continuous-time system. The paper presents two sufficient Linear Matrix Inequality (LMI)-based conditions for designing robust controllers specific to the proposed structure. The first condition utilizes a constant Lyapunov function, while the second condition employs a parameter-dependent Lyapunov function. In both cases, the proposed conditions guarantee asymptotic stability for the continuous-time system in closed-loop. A numerical experiment is conducted to illustrate the validity and effectiveness of the proposed method. • Discretizatizing continuous-time time-invariant uncertain systems is an open problem. • Considering delayed steps in the discretization can provide more information. • Suitable discrete-time control design procedures are presented. [ABSTRACT FROM AUTHOR]

To solve the ship course control problem with nonlinear terms, input saturation, and complex noise, this paper proposes a saturated ship course control method with complex noise based on generalized fuzzy hyperbolic model (GFHM). Due to the characteristics of fewer identification parameters, GFHM can simplify the complexity of traditional ship fuzzy models. GFHM is more suitable for multi-variable nonlinear systems such as ships of which variables are limited and difficult to measure. Furthermore, to deal with the input rudder angle saturation problem caused by the limited capability to compensate the shipboard equipment controller, an auxiliary system is proposed. And the complex noise in the navigation environment is described by the random process. Then, a new type of ship fuzzy course controller is designed based on the theoretical framework of random differential equations (RDEs) and it is proved that the ship course system under the proposed GFHM-based controller is noise-to-state stable in probability (NSS-P) and the state is an asymptotic gain in probability (AG-P). The simulation results show that the proposed algorithm in this paper can effectively control the ship's course. [ABSTRACT FROM AUTHOR]

Concentrated on the marine surface vessel (MSV) with input saturation, model uncertainties and unknown disturbances, this paper proposes the error-constrained line-of-sight guidance-based prescribed performance dual event-triggered path following control (ECLOS-PPDETPFC) strategy which applies the dual relative threshold event-triggered mechanism (ETM) to both guidance and controller of the MSV path following. We apply the prescribed performance function (PPF) as the bounds of asymmetric modified barrier Lyapunov function (AMBLF) to construct the prescribed performance asymmetric modified barrier Lyapunov function (PPAMBLF). In guidance, event-triggered error-constrained line-of-sight (ETECLOS) is constructed by relative threshold ETM and AMBLF to reduce the calculation pressure and keep position errors within the constraint range; In controller, prescribed performance event-triggered path following control (PPETPFC) is based on the relative threshold ETM and PPAMBLF, which makes the heading error meet the prescribed performance requirements, while reducing the loss of actuator. At the same time, the adaptive auxiliary systems are used to compensate the influence of input saturation, radial basis function neural networks (RBFNNs) and adaptive laws are used to approximate the model uncertainties and composite disturbances. According to the Lyapunov stability theory, all signals are semi-globally uniformly ultimately bounded (SGUUB) and the Zeno phenomenon is avoided. Finally, the comparative experiment shows the effectiveness and superiority of the designed control strategy. • This paper proposes the error-constrained line-of-sight guidance-based prescribed performance dual event-triggered path following control (ETECLOS-PPETPFC) strategy. • This control strategy applies the dual relative threshold event-triggered mechanism (ETM) to both guidance and controller of the MSV path following, which can reduce controller calculation pressure and actuator loss. • This control strategy can reduce the update frequency of guidance heading angle and controller. • This control strategy can not only constrain the errors of MSV position, but also make the heading error meet the prescribed performance requirements. [ABSTRACT FROM AUTHOR]

This paper provides a semi-analytical solution for the scattering of seismic waves by the composite topography of the alpine valley based on the scaled boundary finite element method (SBFEM). Firstly, the near-field finite region is discretized using a quadtree mesh decomposition technique. The input of seismic waves is transformed into the traction force acting on the interface between the near and far fields, and thus the numerical modeling of the scattering of seismic waves by the composite terrain of the alpine valley is established. Then, the accuracy of this paper's method is verified by comparing the results with the existing results. Finally, the effects of related parameters such as mountain, valley and seismic waves on ground motion are discussed in detail. The results show that there are significant dynamic interactions between the alpine and valley, that the alpine has an inhibiting effect on the ground motion in the valley region under the vertical incidence of seismic waves, and the valley has an amplifying effect on the slope surface of the alpines close to the side of the valley. [ABSTRACT FROM AUTHOR]

In this paper, an adaptive partitioning strategy and the proper orthogonal decomposition–Galerkin method are combined to formulate an adaptive partitioned reduced order model (APROM) for fast solution of peridynamic (PD) models involving fractures. A boundary layer separation approach is presented to tackle the inaccurate reproduction of nonlocal boundary conditions in the reduced order model (ROM). Cracks invariably make ROM results more sensitive to the snapshots, i.e. a set of high-fidelity solutions simulated by the full order model (FOM), and this challenge is overcome by an adaptive partitioning strategy. The internal computational domain is divided into two parts: the crack region is modeled by full PD model, and the remaining region is dimensionally reduced. The partitioned configuration is automatically updated with the damage evolution. Several numerical tests are executed to verify the performance of the APROM, which shows that the APROM is able to successfully simulate various fracture phenomena. A significant improvement in computational efficiency is found: the number of degrees of freedom in the full PD model is greatly reduced, leading to an approximately 10 times improvement in CPU time without loss of accuracy. This paper provides strong theoretical support for accelerating PD solutions, thereby promoting the practical application of PD theory in large-scale engineering projects. [ABSTRACT FROM AUTHOR]

This paper proposed an Immersion and Invariance (I&I) adaptive fault-tolerant safe control scheme for a class of safety-critical (SC) systems with parametric faults. The scheme combines I&I Adaptive Control Lyapunov Function (I&I aCLF) with I&I Adaptive Control Barrier Function (I&I aCBF) to shape the transient performance of constrained states. Forward invariance of a safe set is achieved through online parameter adaptation, and the parameter convergence is guaranteed through I&I adaptation law. The conservatism is reduced by both shaping transient performance and ensuring parameters convergence. A SC controller guaranteeing stability and safety is obtained by solving an optimization problem with safety constrain, and an analytical solution is provided to facilitate the calculation and execution of the SC controller. A numerical simulation is carried out to illustrate the effectiveness of the proposed method. • This paper presents I&I aCLF and I&I aCBF, which are used to design controllers for ensuring the stability and safety of nonlinear systems with parametric faults. • The proposed controller provides less conservatism and improves the transient performance of constrained states. The parameter convergence is guaranteed by the proposed adaptation law. • To facilitate the calculation and execution of the controller, an analytical controller for a class of SC systems with parametric faults is given. [ABSTRACT FROM AUTHOR]

To capture the underlying dynamics of the COVID-19 pandemic, we develop a stochastic SEIABR compartmental model, where the concentration of coronaviruses in the environment is considered. This paper is the first attempt to introduce the Black-Karasinski process as the random fluctuations in the modeling of epidemic transmission, and it is shown that Black-Karasinski process is a both mathematically and biologically reasonable assumption compared with existing stochastic modeling methods. We first obtain two critical values R 0 S and R 0 E related to the basic reproduction number R 0 of deterministic system. It is theoretically proved that (i) if R 0 S > 1 , the stochastic model has a stationary distribution ℓ (·) , which implies the long-term persistence of COVID-19; (ii) the disease will go extinct exponentially when R 0 E < 1 ; (iii) R 0 S = R 0 E = R 0 if there is no environmental noise in COVID-19 transmission. Then, we study the local stability of the endemic equilibrium P * of deterministic system under R 0 > 1. By developing an important lemma for solving the relevant Fokker-Planck equation, an approximate expression of probability density function of the distribution ℓ (·) around P * is further derived. Finally, several numerical examples are performed to substantiate our theoretical results. It should be mentioned that the techniques and methods of analysis in this paper can be applied to other complex high-dimensional stochastic epidemic systems. [ABSTRACT FROM AUTHOR]

This paper focuses on the robust sliding mode passive control (SMPC) problem for uncertain Markovian jump discrete systems under the finite time setting. For the considered model, the phenomenon of stochastic communication delays (SCDs) is depicted via some Bernoulli distributed stochastic variables, which involve inaccurate occurrence probability information. In view of initial condition, a common form of sliding surface is chosen. Further, the sliding motion equation can be given for the original system. Our aim of this paper is to propose some potential sufficient criteria for finite-time boundedness and passive requirement of the sliding motion. With the same objective, a comprehensive reaching condition is also utilized to construct the robust sliding mode passive controller such that the controlled system can be kept remain in a region of the sliding surface thereafter. Finally, an example is given to show the usefulness of our proposed scheme here. [ABSTRACT FROM AUTHOR]

• A fixed-time unknown observer is devised to estimate the matched/mismatched unknowns simultaneously within a fixed time. • By using an auxiliary function, a nonsingular fixed-time control framework is proposed without using any piecewise function. • The EMG signals are incorporated into the proposed fixed-time control framework and improves the tracking performance. [Display omitted] In this paper, a fixed-time personalized variable gain control (FTPGC) scheme is developed for a class of teleoperation systems. Efforts in this paper seek to improve the tracking performance under different operation intentions for teleoperation systems in the presence of time varying delays and uncertainties. By virtue of nonsmooth analysis, a fixed-time unknown observer (FUO) is firstly devised for the teleoperation systems such that the matched/mismatched unknowns can be observed within a fixed time. Meanwhile, with the help of an auxiliary function, a novel nonsingular fixed-time control framework is subsequently constructed without using any piecewise continuous switching functions. Moreover, the FUO and a variable gain involving electromyographic are incorporated into the fixed-time control framework, and thereby resulting the FTPGC scheme to improve trajectory tracking performance in the presence of unknowns and different operation intentions. The fixed-time stability of the entire FTPGC scheme is derived by rigorously theoretical analysis. Finally, comprehensive experiments and comparisons are conducted to demonstrate the effectiveness and feasibility of the proposed scheme. [ABSTRACT FROM AUTHOR]

• For the fast-varying delay, an improved analytical method based on Lyapunov-Krasovskii (LK) functionals is given by introducing and proving a new lemma, which is not only independent of the upper bound of time-varying delay, but also independent of the derivative of the time-varying delay. Hence, the developed analytical method greatly expands the application range of the LK functional. • For unknown nonconstant control coefficients, an output feedback control strategy based on the compensated system is proposed. As an intermediate link, the adaptive fuzzy system is introduced into the controller indirectly by the compensation system, so as to avoid the algebraic-loop problem. Hence, the cooperative design of the compensation system, the state observer and the controller is one of the innovations in this paper. • Considering the problems of state immeasurability and time-varying delay comprehensively, an adaptive fuzzy output-feedback control law is proposed based on an improved average dwell time, which relaxes the constraints between the LK functional of each subsystem in switched large-scale interconnected nonlinear systems. In this paper, an adaptive fuzzy decentralized output-feedback control is developed for the uncertain switched large-scale interconnected nonlinear system, which contains fast time-varying delays and unknown nonconstant control coefficients. By introducing and proving a new lemma, an improved analysis method is given based on the Lyapunov-Krasovskii (LK) functional, and it gets rid of the dependence of LK functional design on the bound of the derivative of the delay. Immeasurable states are estimated by co-designing the decentralized state observer and the innovative compensation system, which eliminates a widely adopted but strict assumption that the unknown control coefficient must be constant. By comprehensively designing the state observer, the compensation system and LK functionals, a novel adaptive fuzzy decentralized output-feedback control law is proposed, and stability of the closed-loop system is guaranteed theoretically based on an improved average dwell time. Finally, the effectiveness is further verified by complete simulation experiments. [ABSTRACT FROM AUTHOR]

The fixed-time tracking control issue is investigated for a class of high-order nonlinear delayed systems subject to mismatched disturbances in this paper. Wherein, the fuzzy logic system is applied in dealing with the nonlinear functions and the power integrator technique is appropriately introduced to address the high-order terms in the considered system. Different from the conventional methods of using the Lyapunov-Krasovskii functional approach to cope with the delayed terms in the previous work, the adaptive backstepping method is utilized in this paper. The main purpose of the addressed control problem is to design a suitable adaptive fuzzy fixed-time controller such that the closed-loop system is stable and guaranteed to be bounded in a fixed-time interval. Subsequently, the specific control law is deduced through the inductive method, and the upper bound on the settling time for the fixed-time control is given. Finally, the simulation examples are given to illustrate the feasibility and effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

• Almost sure stability is studied for a semi-Markov system with/without asynchronous controller. • A new stochastic Lyapunov function is established based on the random switching time and a newly segment bounded function. • Improved sufficient conditions are proved by the ergodicity of semi-Markov process, which improve known results on stability. • Conditional probability is introduced to solve the asynchronous problem between the system and the controller. • The converge rate of the system is optimized due to the introduction a newly segment bounded function. The purpose of this paper is to study almost sure exponential stability (ASES) of a class of semi-Markov jump systems with/without asynchronous controller. Based on the stationary distribution and ergodicity of semi-Markov switching process, sufficient stability conditions of semi-Markov jump systems are established firstly, which significantly improved some known results. Then, the sufficient conditions of ASES for semi-Markov jump systems with asynchronous controller is investigated. To be pointed out that the stochastic Lyapunov function constructed in this paper is new, which couples the switching points of semi-Markov process and a newly defined segment bounded function. Finally, two examples are given to show the superiority of our conclusions. [ABSTRACT FROM AUTHOR]

This paper investigates the adaptive fixed-time tracking control problem for a class of stochastic nonlinear systems with constrained states and input saturation. By utilizing a barrier Lyapunov function (BLF), the issue caused by constrained states is settled. Simultaneously, a smooth function is constructed to approximate input saturation and the unknown nonlinear function is approximated by neural networks (NNs). In view of the fixed-time tracking control problem of stochastic nonlinear systems, a fixed-time stability lemma for stochastic nonlinear systems has been established and proved. Under the designed controller, the closed-loop system is semi-globally fixed-time stable in probability (SGFSP), and all the states are constrained within a compact set. Moreover, the controlled system in this paper achieves equilibrium within a fixed-time internal. Lastly, the presented method is verified by a simulation example. [ABSTRACT FROM AUTHOR]

Data interpolation is a fundamental problem in many applied mathematics and scientific computing fields. This paper introduces a modified implicit local radial basis function interpolation method for scattered data using polyharmonic splines (PS) with a low degree of polynomial basis. This is an improvement to the original method proposed in 2015 by Yao et al.. In the original approach, only radial basis functions (RBFs) with shape parameters, such as multiquadrics (MQ), inverse multiquadrics (IMQ), Gaussian, and Matern RBF are used. The authors claimed that the conditionally positive definite RBFs such as polyharmonic splines r 2 n ln r and r 2 n + 1 "failed to produce acceptable results". In this paper, we verified that when polyharmonic splines together with a polynomial basis is used on the interpolation scheme, high-order accuracy and excellent conditioning of the global sparse systems are gained without selecting a shape parameter. The scheme predicts functions' values at a set of discrete evaluation points, through a global sparse linear system. Compared to standard implementation, computational efficiency is achieved by using parallel computing. Applications of the proposed algorithms to 2D and 3D benchmark functions on uniformly distributed random points, the Halton quasi-points on regular or Stanford bunny shape domains, and an image interpolation problem confirmed the effectiveness of the method. We also compared the algorithms with other methods available in the literature to show the superiority of using PS augmented with a polynomial basis. High accuracy can be easily achieved by increasing the order of polyharmonic splines or the number of points in local domains, when small order of polynomials are used in the basis. MATLAB code for the 3D bunny example is shared on MATLAB Central File Exchange (Yao, 2023). [ABSTRACT FROM AUTHOR]

Recently, we derived the Green's function for an infinite thick laminated composite plate subjected to concentrated forces and moments. By serving this Green's function as the fundamental solutions, in this paper for the first time we develop the associated boundary element method (BEM), which is applicable to general problems of thick laminated plates with various types of deformations. For example, the in-plane stretching and out-of-plane bending deformations may be coupled together, which occurs for the unsymmetric laminated composite plates. Besides, the transverse shear deformations are also incorporated based upon the first order plate theory. To complete the entire development of the proposed BEM, all the involved issues, such as the boundary integral equations, the fundamental solutions and their derivatives, the mathematical formulation for the selected isoparametric quadratic boundary element, and the treatments of singular integrals are elaborated in this paper. The calculations of complete solutions at boundary or internal points are provided as well. The accuracy and efficiency of the proposed BEM are demonstrated through numerical examples, which show that it outperforms the conventional finite element method and is applicable for general thick laminated plates with unrestricted coupling effects. [ABSTRACT FROM AUTHOR]

This paper proposes a novel isogeometric topology optimization method to obtain the hierarchical structures, where a special porous microstructures of identical topologies but with different length-width ratios are considered. First, the floating projection technique without penalization is adopted to find the topological configurations of hierachical structures, which make the optimized hierachical structures not easy to fall into the local optimums. Second, the isogeometric analysis based on the non-uniform rational B-spline basis functions, is utilized to calculate the structural compliances and sensitivity information. Third, this paper presents a limited number of microstructures with the changing aspect ratios, to satisfy arbitrary boundary conditions of macrostructures. The macroscopic equivalent properties are evaluated by the isogeometric analysis-based homogenization method. Finally, four numerical examples are provided to illustrate the effectiveness of the proposed method in designing hierarchical structures, and the influence of micro-structural properties on the macro-structural performances. [ABSTRACT FROM AUTHOR]

In this paper, we are concerned with the dynamic feedback design for linear systems with input disturbance. We propose a new approach to design dynamic feedback such that the disturbance in the control channel can be compensated effectively. An interesting characteristic about the disturbance robustness of dynamic feedback is found. Thanks to this interesting characteristic, we just need to consider the disturbance-free system to make the dynamic feedback design. This fact is well validated by several dynamic feedback laws proposed in this paper. Our results are available for the regular linear system with harmonic disturbance. Moreover, the stabilization of an unstable heat equation with general periodic disturbance is also investigated. In order to validate the theoretical results visually, some numerical simulations are given to show the effectiveness of the proposed dynamic feedback. [ABSTRACT FROM AUTHOR]

This paper presents a complete control architecture for the implementation of adaptive sliding controllers (ASMC) in quadrotors. Aiming into presenting a control solution for real-world scenarios, this paper presents a comparative study evaluating the advantages and disadvantages of the three most common methods to implement adaptive sliding mode controllers in quadrotors. Namely, two of the compared methods aim to reduce the SMC gains to ones that keep the tracking errors inside a user-defined bound, while the third method consists of obtaining the minimal SMC gain which permits the sliding mode to exist. To inspect the compared methods in realistic and harsh conditions, the three controllers are tested far from quasi-static motion and under severe disturbances. The quadrotor was subjected to disturbances such as stabilization under intermittent wind, landing precisely subject to wind-gusts, high-speed trajectory tracking while carrying an unmodeled suspended payload with a center-of-mass offset, and trajectory tracking with a damaged propeller. The performance of the analyzed adaptive sliding mode controllers was also compared to the industrial standard PID controller. Our experimental analysis demonstrates that, in face of such disturbances, one of the analyzed adaptive sliding mode controllers excels when compared to the others, and every ASMC excels when compared to the PID. [ABSTRACT FROM AUTHOR]

This paper discusses a distributed time-varying convex optimization problem that agents have different Hessian matrices with inequality constraints. The objective is to minimize the sum of local time-varying objective functions of agents constrained by time-varying inequalities. Under the condition of undirected connected graph, a distributed continuous time consistency algorithm is designed based on average consensus estimator, sign function and log-barrier penalty function. The main idea of the algorithm proposed in this paper is to use the estimator to estimate the global information, make the state of agents reach consensus and achieve gradient descent to track the optimal solution. Theoretical findings show that all agents can reach an agreement, the proposed algorithm can track the optimal solution of the time-varying optimization problem. The effectiveness of the theoretical results is verified through a numerical examples. [ABSTRACT FROM AUTHOR]

In this paper, we construct an improved Implicit–Explicit (IMEX) numerical scheme based on the conservation form of the advection–diffusion equations and study the numerical stability of the method in case of a nonlinear advection–diffusion Lotka–Volterra model. The classical numerical methods might be unsuitable for providing accurate numerical results for advection–diffusion problem in which advection dominates diffusion. An improved numerical scheme is proposed, which can preserve the positivity for arbitrary stepsizes. The convergence, boundedness, existence and uniqueness of the numerical solutions are investigated in paper. A threshold value denoted by R 0 Δ x , is introduced in the stability analysis. It is shown that the numerical semi-trivial equilibrium is locally asymptotically stable if R 0 Δ x < 1 and unstable if R 0 Δ x > 1. Moreover, the limiting behaviors of the threshold value are exhibited. Finally, some numerical simulations are given to confirm the conclusions. [ABSTRACT FROM AUTHOR]

This paper deals with the non-linear Susceptible–Infected–Hospitalized–Recovered model with Holling type II incidence rate, treatment with saturated type functional response for the prevention and control of disease with limited healthcare facilities. The well-posedness of the model is ensured with the help of the non-negativity and boundedness of the solution of the system. The feasibility of the model with DFE (Disease-free equilibrium) and EE (endemic equilibrium) is analysed. The local and global stability are discussed with the help of the computed basic reproduction number R 0. At R 0 = 1 , we use the Centre manifold theory to analyse the transcritical bifurcation exhibited by the system. It is found that the disease is not eradicated even if R 0 < 1 due to the occurrence of backward bifurcation. The occurrence condition of Hopf bifurcation is obtained. The optimal control theory is used to analyse the effects of the minimum possible medical facilities, hospital beds, and awareness creation on the population dynamics. The Hamiltonian function is constructed with the extended optimal control model and solved by Pontryagin's maximum principle to get the minimum possible expenditure. Different types of control strategies are shown by numerical simulation. The sensitivity analysis is discussed with the help of a crucial parameter that depends on the reproduction number. Further, the model is simulated numerically to support the theoretical studies. This paper emphasizes the significance of treatment intensity, the total number of hospital bed available and their occupancy rate as vital parameters for prevention of disease prevalence. • A nonlinear model is proposed to study the spread and control of infectious diseases with limited healthcare facilities. • Due to backward bifurcation, R 0 < 1 is insufficient to eliminate the disease, and the system exhibits periodic oscillation due to the emergence of Hopf bifurcation. • Using Pontryagin's maximum principle, effects of the limited medical facilities, hospital beds, and awareness-building initiatives are examined to determine the minimum possible expenses. • Sensitivity analysis is used to determine the appropriate control parameter and cost-effectiveness analysis is used for finding most optimal strategy. [ABSTRACT FROM AUTHOR]

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Lightweight laminate composite sandwich-like materials are one of the most used composite materials. When a laminate composite is punched normally to the surface, the outer skin layer plays a protective role, which is studied in the present work by elucidating the corresponding stress distribution in the core. First, a theoretical framework is developed to predict the stress distribution in the core corresponding to different mechanical properties of the skin. Thus, the location of the highest stress is predicted and a potential failure domain in the core of the laminate composite is established. The theory is verified by novel photoelastic experiments developed and conducted in this work. In addition, a micromechanical model of behavior of paper filaments under compression is proposed and verified experimentally. Based on this model, a novel method of measuring Young's modulus and Poisson's ratio of compressed paper is proposed and demonstrated. [ABSTRACT FROM AUTHOR]

This work focuses on the study of ink seepage and spreading into paper to ease the deciphering of digitized ancient documents and therefore make them legible and researchable. A three-dimensional model is proposed for the simulation of ink seepage into paper at the fiber level. The model takes into account a finite volume of ink and describes the system state through gravity, cohesion and adhesion force interactions. At the mesoscopic scale, the writing paper is modeled using a discretized fiber structure generated using a numerical deposition procedure. A modified Monte Carlo method is introduced for the simulation of the ink dynamics. Finally a multiphase lattice Boltzmann method is suggested to fine-tune the mesoscopic variational model parameters and it is shown that the ink seepage behaviors predicted by the proposed model can resemble those predicted by a method relying on first principles. [ABSTRACT FROM AUTHOR]

One of the most important characteristics of the photovoltaic (PV) modules is their long lifetime (around 25 years). However, recent investigations have shown that PV modules may suffer significant degradation before that time; that is why the development of diagnostic techniques is important for the customers of PV systems. In this paper two indicators to quantify the degradation of a PV module are presented. Such indicators use the single-diode model to represent a PV module without degradation and combine such information with the experimental measurements to estimate the increase in the series resistance and/or the decrease in the parallel resistance with respect to reference values. The estimation of those variations allows the quantification of the module degradation. Simulation results comparing the proposed indicators with the fill factor (a traditional indicator to quantify the electrical quality of a PV module), and other indicators to estimate the series resistance are presented to illustrate the advantages of the proposed indicators. [ABSTRACT FROM AUTHOR]

Density-dependent selection is a universal feature in the evolution of populations, and such an adaptive behavior can change the survival strategy of species during evolution. In this paper, we investigate the role of adaptive behavior in biodiversity in the system of cyclic competition. By incorporating a density-dependent mechanism into intraspecific competition, which is well-known as a key mechanism leading to biodiversity, we studied how such adaptive intraspecific competition can affect biodiversity and collective behavior during the evolution of cyclically competing species. Microscopically, we found that species can coexist strongly and are spirally entangled or collectively united by presenting two distinct pattern formations on spatially extended systems. While the adaptive mechanism can always promote species coexistence in a mean-field manner for particular sensitivity to the group scale, corresponding spatial dynamics exhibit nonmonotonic features for the robustness of extinction at moderately high mobility regime over the critical mobility when the associated mean-field system exhibits asymptotically stable heteroclinic cycles. The findings can shed light on a new aspect of the collective behavior of coexisting populations which may indicate the possibility of changing the survival strategies of each group to maintain the coexistence of cyclically competing populations. • The effect of the adaptive intraspecific competition is studied. • Species biodiversity is promoted at moderately high mobility values. • Anomalous viability accompanies the change of new pattern formation for coexistence. • The role of adaptive intraspecific competition is studied quantitively. • Critical degrees of adaptive intraspecific competition are discussed. [ABSTRACT FROM AUTHOR]

This paper deals with smart grid concept and its reliability in presence of renewable energies. Around the globe an adjustment of electric energy is required to limit CO2 gas emission, preserve the greenhouse, limit pollution, fight climate change and increase energy security. Subsequently renewable energy expansion is the real test for designers and experts of smart grid system. This initiative has made significant progress toward the modernization and growth of the electric utility infrastructure and aims to integrate it into today's advanced communication era, both in function and in architecture. The study is focused on the difference between a conventional grid and a smart grid concept and the integration of renewable energy in a smart grid system where grid control is a must for energy management. Assuring a good grid reliability, taking the right control measures in order to preserve continuous electricity supply for the customers are challenges highlighted in the present paper. [ABSTRACT FROM AUTHOR]

To investigate accurately unique and advanced wave properties in elastic metamaterials advanced and efficient numerical methods are needed. The paper presents an extended boundary integral equation method for simulating elastic wave scattering by doubly periodic arrays of rectangular crack-like voids. The convergence of the arising double series is proved and the convergence rate is carefully analyzed. Employing the results of the investigation of the convergence rate, an algorithm for fast numerical calculation of double series is proposed to reduce computational costs through preliminary analytical evaluation and the proposed summation strategy. The efficiency of the extended boundary integral equation method is demonstrated and examples of the calculated transmission coefficients exhibiting the influence of the introduction of the doubly periodic array are given. [ABSTRACT FROM AUTHOR]

• The stratification and anisotropy of the soil are taken into consideration. • The impact of the bedrock underlying the soil is taken into account. • The stiffness of the footing is considered. • Explicit expressions for stress and displacement are provided. This paper presents explicit expressions of stress and displacement in the physical domain of layered transversely isotropic soil under strip footing for the first time. The method proposed in this study is not only applicable to analysing problems related to flexible footings, but can also be utilized for analysing problems related to rigid footings. The stress function of each layer can be represented by two single-valued analytic functions. Each layer of soil is mapped to a unit circle using affine and conformal transformations. Within the unit circle, the single-valued analytic function can be expanded into a Taylor series with unknown coefficients. By establishing equations based on the boundary conditions and stress-displacement continuity conditions, the unknown coefficients can be determined. To validate the proposed method, the calculation results were compared with ANSYS finite element results. [ABSTRACT FROM AUTHOR]

Time-domain boundary element method (TDBEM) can be applied in studying transient acoustic wave problems, especially in solving exterior problems. However, in order to avoid calculations of coefficients at different time steps, TDBEM usually requires storing or recomputing the coefficients at each time step. This can lead to significant amount of memory usage or long computing time. In this paper, an acoustic TDBEM based on a kernel-function library (KFL-BEM) is proposed, in order to reduce the memory consumption of the time-domain conventional BEM (CBEM) and speedup the computation. In this approach, the storage requirement is reduced from O (N 2 N t min) to O (N 2), where N represents the number of degrees of freedom of the model, and N t min is the minimum number of time steps for which coefficients need to be computed and stored. To demonstrate the effectiveness of the KFL-BEM, two verification examples are presented using the problems of a pulsating sphere and sound propagating in a channel. Compared with the CBEM, the KFL-BEM can save significantly the memory storage as it does not require storing coefficients for any previous time steps. This method can also be applied to solve vibro-acoustic problems in the time domain. As an example, the acoustic radiation responses of a tuning fork under different striking loads are studied using the finite element method and the proposed KFL-BEM, which clearly shows the potentials of the KFL-BEM in solving time-domain acoustic problems. [ABSTRACT FROM AUTHOR]

This paper tackles the problem of nonfragile state estimation for semi-Markovian switching complex-valued networks with time-varying delay. The concerned transition rates of the semi-Markov process are uncertain, including both the completely unknown ones and the inaccurately known ones with known bounds. To reduce the communication burden, a particular event-triggered generator is constructed, which depends on the latest available measurement output and a predefined positive threshold. Combining the stochastic analysis method with the Lyapunov stability theory, some less conservative criteria are obtained to ascertain the global asymptotic stability of the estimation error system in the mean-square sense. In addition, by solving some matrix inequalities, the desired nonfragile estimator gains are explicitly designed. Finally, a numerical example with simulations is given to illustrate effectiveness of the established estimation scheme. [ABSTRACT FROM AUTHOR]