Conditions For Global Stability Research Articles

An active queue management method for multiple bottleneck networks based on distributed average tracking

The active queue management (AQM) is a key technology for the information infrastructure and the Internet. The AQM for multiple bottleneck networks is especially challenging than that for single-bottleneck networks because the stability analysis of multiple bottleneck networks is more complex. In this paper, the active queue management problem for multiple bottleneck networks is considered. A novel random early detection algorithm is designed based on distributed average tracking technology, which is used to estimate the global queue length and improve the network's performance. Sufficient conditions for global asymptotic stability of the closed-loop active queue management system are presented, and some simulation results with NS-2 are given. Compared with the RED algorithm, simulation results show that the presented algorithm has smaller oscillations at routers, which highlights its effectiveness.

The Stability of a Predator–Prey Model with Cross-Dispersal in a Multi-Patch Environment

This paper investigates the stability of predator–prey models within multi-patch environments, with a particular focus on the influence of cross-dispersion across patches. We apply Kirchhoff’s matrix tree theorem and Liapunov’s method to derive criteria related to the cross-dispersion topology, thus solving the challenge of determining global asymptotic stability conditions. The method incorporates realistic ecological interactions and spatial heterogeneity, offering a framework for stability analysis. Our findings demonstrate that an appropriate level of cross-dispersion can effectively mitigate oscillations and foster convergence toward equilibrium. Two numerical examples validate these theoretical results and demonstrate the feasibility and effectiveness of the model across multiple patches.

Dynamic analysis and data-driven inference of a fractional-order SEIHDR epidemic model with variable parameters

To analyze and predict the evolution of contagion dynamics, fractional derivative modeling has emerged as an important technique. However, inferring the dynamical structure of fractional-order models with high degrees of freedom poses a challenge. In this paper, to elucidate the spreading mechanism and non-local properties of disease evolution, we propose a novel fractional-order SEIHDR epidemiological model with variable parameters, incorporating fractional derivatives in the Caputo sense. We compute the basic reproduction number by the next-generation matrix and establish local and global stability conditions based on this reproduction number. By using the fractional Adams–Bashforth method, we validate dynamical behaviors at different equilibrium points in both autonomous and non-autonomous scenarios, while qualitatively analyze the effects of fractional order on the dynamics. To effectively address the inverse problem of the proposed fractional SEIHDR model, we construct a fractional Physics-Informed Neural Network framework to simultaneously infer time-dependent parameters, fractional orders, and state components. Graphical results based on the COVID-19 pandemic data from Canada demonstrate the effectiveness of the proposed framework.

Current disturbance compensation of continuous model predictive control scheme for PMSMs

During the operation of a permanent magnet synchronous motor, limitations imposed by digital chips inevitably result in certain delays. Additionally, external environmental factors introduce variations in motor parameters. This study aims to comprehensively analyze these issues. Firstly, the control delay and disturbances caused by motor parameter changes are transformed into current disturbances using a uniform approach. Secondly, various sliding mode model predictive controllers are designed to effectively suppress the current disturbances arising from aforementioned reasons. Moreover, considering controller implementation aspects, this paper thoroughly discusses the influence of core controller parameters on current disturbances and their adaptability towards different parameter mismatches. Furthermore, extensive examination is conducted on global stability conditions for controller realization. Finally, experimental results validate that the proposed methods successfully optimize current disturbances originating from aforementioned causes.

Controllability and Optimal Fast Operation of Nonlinear Systems

A new method for solving the problem of controllability and optimal transient behavior of nonlinear systems subject to boundary conditions and constraints on control values was proposed. Unlike existing methods, this new approach is based on constructing a general solution of the integral equation for a linear controlled system, followed by transforming the original problem into a special initial optimal control problem. We propose a new method for studying the global asymptotic stability of dynamical systems with a cylindrical phase space with a countable equilibrium position based on a non-singular transformation of the equation of motion and estimation of improper integrals along the solution of the system. Conditions for global asymptotic stability were obtained without involving any periodic Lyapunov function, as well as the frequency theorem. The effectiveness of the proposed method is shown with an example.

Dual CAR-T cell therapy for glioblastoma: strategies to cure tumour diseases based on a mathematical model

AbstractThe CAR-T cell immunotherapy entails the genetic reprogramming of T-lymphocytes, which then engage with cancer cells, triggering an anti-tumour immune response. While this treatment has gained approval for hematological cancers, addressing solid tumours presents new obstacles. Challenges include the heterogeneity of antigen expression within solid tumours, encompassing antigen-positive non-tumoural cells, the presence of immune inhibitory molecules, and the difficulty of CAR-T cell trafficking within the tumour microenvironment. In this article, we analytically study a generalisation of a mathematical model proposed by León-Triana et al. (Cancers 13(4):703, 2021a. https://doi.org/10.3390/cancers13040703, Commun Nonlinear Sci Numer Simul 94:105570). This model focuses on the dynamics of glioblastoma, the most aggressive brain tumour, and its response to CAR-T cell treatment. We study the basic properties of the model, the dynamics of the solutions of the model when the treatment is not sustained during the time, and finally we study analytically the model when the therapy is constant, periodic and/or impulsive. We derive sufficient conditions for global stability of tumour-free equilibrium, as well as necessary and sufficient conditions for local stability of the equilibrium obtaining conditions for an effective treatment. Finally, we perform different numerical simulations to find the strategies to keep the tumour under control. The obtained results are based on a combination of different analytical techniques in differential equations, dynamical systems and numerical simulations.

Global Stability of Phase-Change Neural Networks With Mixed Time Delays.

Phase-change memory (PCM) is a novel type of nonvolatile memory and is suitable for artificial neural synapses. This article investigates the Lagrange global exponential stability (LGES) of a class of PCNNs with mixed time delays. First, based on the conductivity characteristics of PCM, a piecewise equation is established to describe the electrical conductivity of PCM. By using the proposed piecewise equation to simulate the neural synapses, a novel PCNN with discrete and distributed time delays is proposed. Then, using comparative theory and fundamental inequalities, the LGES conditions based on the M -matrix are proposed in the sense of Filippov, and the exponential attractive set (EAS) is obtained based on M -matrix and external input. Moreover, the Lyapunov global exponential stability (GES) conditions of PCNNs without external input are obtained by using the inequality technique and eigenvalue theory, which is a form of M -matrix. Finally, two simulation examples are given to verify the validity of the obtained results.

Optimism leads to optimality: Ambiguity in network formation

We analyze a model of endogenous two-sided network formation where players are affected by uncertainty about their opponents' decisions. We model this uncertainty using the notion of equilibrium under ambiguity as in Eichberger and Kelsey (2014). Unlike the set of Nash equilibria, the set of equilibria under ambiguity does not always include underconnected and thus inefficient networks such as the empty network. On the other hand, it may include networks with unreciprocated, one-way links, which comes with an efficiency loss as linking efforts are costly. We characterize equilibria under ambiguity and provide conditions under which increased player optimism comes with an increase in connectivity and realized benefits in equilibrium. Next, we analyze network realignment under a myopic updating process with optimistic shocks and derive a global stability condition of efficient networks in the sense of Kandori et al. (1993). Under this condition, a subset of the Pareto optimal equilibrium networks is reached, specifically, networks that maximize the players' total benefits of connections.

New global exponential stability conditions for nonlinear delayed differential systems with three kinds of time-varying delays

For a class of nonlinear differential systems with heterogeneous time-varying delays, including distributed, leakage and transmission time-varying delays, a novel global exponential stability (GES) analysis method was developed. Based on the GES definition, some sufficient conditions and rigorous convergence analysis of nonlinear delayed differential systems are presented directly, which ensure all states to be globally exponentially convergent. The proposed analysis method not only avoids the construction of the Lyapunov–Krasovskii functional, but also uses some simple integral reduction techniques to determine the global exponential convergence rate. Furthermore, the main advantages and low calculation complexity are demonstrated through a theoretical comparison. Finally, three numerical examples are provided to verify the effectiveness of the theoretical results.

Asymptotic stability results of generalized discrete time reaction diffusion system applied to Lengyel-Epstein and Dagn Harrison models

In this research paper, we delve into the analysis of a generalized discrete reaction-diffusion system. Our study begins with the discretization of a generalized reaction-diffusion model, achieved through second-order and L1-difference approximations. We explore the local stability of its unique solution, both in the absence and presence of the diffusion term. To determine the conditions for global asymptotic stability of the steady-state solution, we employ suitable techniques including the direct Lyapunov method. To illustrate the practical application of this theoretical framework, we provide several numerical simulations that examine both the Lengyel-Epstein reaction-diffusion model and the discrete Degn-Harrison reaction-diffusion model. These simulations serve to validate the predictions of asymptotic stability.

Mathematical model of mosquito population dynamics with constants and periodic releases of Wolbachia-infected males

In this article, we propose three mathematical models of mosquito dynamics. The first model describes the dynamics of wild mosquitoes in combination with mechanical control and larvicide. For this model, we derive a threshold parameter N , called the basic number of offspring, and show that the trivial equilibrium is globally asymptotically stable when N ≤ 1 , while if N > 1 , the non-trivial equilibrium is globally asymptotically stable. In the second model, we evaluated a constant release of Wolbachia-infected males in the wild mosquito population. Our analysis identified a critical threshold for releasing Wolbachia-infected male mosquitoes M i crit to reduce or eliminate the wild mosquito population. In the third model, we assessed wild mosquito dynamics by periodically releasing Wolbachia-infected male mosquitoes. The analysis of this model produced two thresholds, T ∗ the threshold on the release period and Λ ∗ the threshold on the release quantity. The existence of trivial periodic solutions is obtained, and the corresponding local and global stability conditions are proved by Floquet's theory and Lyapunov's stability theorem, respectively. We also prove the existence conditions for non-trivial periodic solutions and their local stability. Finally, we perform some numerical simulations to illustrate our theoretically pertinent results.

Optimal control of rotavirus infection in breastfed and non-breastfed children

According to the World Health Organization’s guidelines, a two-year mandatory breastfeeding period is strongly recommended, supported by research demonstrating its significant benefits in reducing childhood illnesses and mortality rates. The present study is designed to address this recommendation by focusing on a specific infection, namely rotavirus. Acknowledging this evidence, researchers recognize the need for a deeper understanding of the dynamics of rotavirus disease. In response, our study focuses on constructing and analyzing an SIR epidemic model uniquely designed for transmitting rotavirus in children. The model partitions the children population into three compartments: susceptible, infected, and recovered. To enhance precision, we further categorize susceptible children based on breastfeeding status and infected individuals based on infectious or non-infectious nature. This detailed categorization enables a thorough examination of rotavirus transmission dynamics. The proposed model analyzes two equilibria, disease-free and endemic, revealing local and global stability conditions determined by the basic reproduction number (R0). Our exploration extends to local stability analysis for the endemic equilibrium when R0>1 and global stability assessment using the Lyapunov theory under specific conditions. Subsequently, we employ optimal control theory through Pontryagin’s maximum principle to minimize the cost burden associated with disease control in children. Then, our work provides a sensitivity analysis of different parameters for the basic reproduction number to enhance our understanding of model dynamics. Finally, numerical simulations conducted with MATLAB and Python software validate our analytical findings, offering a comprehensive and practical assessment of the proposed model’s implications for controlling rotavirus transmission in children.

Stabilization of a Chain of Three Integrators Subject to a Phase Constraint

The problem of stabilizing a chain of three integrators subject to a phase constraint is studied. Continuous constrained control in the form of nested sigmoids, which guarantees the fulfillment of the phase constraint, is synthesized. A Lyapunov function is constructed, and necessary and sufficient conditions of global stability of the closed-loop system are established. The discussion is illustrated by numerical examples.

A new analytical study of prey–predator dynamical systems involving the effects of Hide-and-Escape and predation skill augmentation

The aim of this work is to provide a comprehensive analysis of the dynamics within an ecosystem characterized by interactions between prey and predators, through a combination of theoretical analysis and numerical simulation. The study investigates the impact of two pivotal effects: the “Hide-and-Escape” behavior exhibited by prey and the “Predation Skill Augmentation” strategy adopted by predators. Theoretical analysis identifies three equilibrium points, all of which show positive characteristics. Furthermore, local stability conditions are determined for each of these equilibrium points. The derivation of global stability conditions is also presented, and their validity and importance as local stability conditions for the coexistence point are demonstrated. In addition, Kolmogorov conditions for coexistence and extinction are verified, as well as local bifurcation analysis. For the validity of the results, a numerical simulation of the system using MATLAB is conducted.

Observer-based fuzzy control for fractional order PMSG wind turbine systems with adaptive quantized-mechanism

This study aims to present an observer-based fuzzy control approach for a wind turbine system (WTS) equipped with a fractional-order permanent magnet synchronous generator (PMSG) by utilizing an adaptive quantized-mechanism. To do this, firstly, the fractional order control is introduced into the nonlinear PMSG model to improve the convergence rate beyond the existing integer order control techniques. In the next step, the nonlinear PMSG model is converted into linear sub-models using Takagi–Sugeno (T–S) fuzzy models. Using a fractional order Lyapunov function, an adaptive quantization mechanism, and a linear matrix inequality (LMI), we then obtain the necessary conditions for global stabilization of the PMSG-based WTS. Finally, the method proposed in this study demonstrates its superiority and efficiency through comparison with existing methods.

Global Exponential Stability Conditions for Discrete-Time BAM Neural Networks Affected by Impulses and Time-Varying Delays

Global Exponential Stability Conditions for Discrete-Time BAM Neural Networks Affected by Impulses and Time-Varying Delays

Effects of stochastic perturbations on a phytoplankton allelopathy competitive system

In this paper, we investigate stochastic models of two species competitive phytoplankton system with allelopathic interaction. We construct stochastic models from deterministic models by introducing three different stochastic perturbations to the equations. For the first model, we prove that this model is asymptotically stable in probability at three different equilibrium points. It is also shown that the system is positively recurrent under some conditions. For the second model, we study the extinction, existence of positive recurrence and global asymptotic stability under some sufficient conditions. For the last system, almost sufficient and necessary conditions for global asymptotic stability, the existence of positive recurrence and extinction of each population are established. In addition, using a suitable stochastic Lyapunov method, we prove that there is a unique solution to three models, we also discuss the ultimate boundedness of the three stochastic systems. Moreover, some numerical simulations are introduced to illustrate our mathematical results. We show that stochastic models still retain the desirable stability of their deterministic counterparts if stochastic perturbations are relatively small.

The structural stability of the phenomenological models with the symmetry group L=3 m and their phase diagrams

We propose a method of investigating the structural stability of phenomenological models of the phase transition by means of the singularity theory (catastrophe theory) combined with the Poincare normal form theory. Also we find the structurally-stable thermodynamic potential models invariant under the order parameter symmetry group L = 3 m and with n = 1∼5 varying parameters, which are defined in the ranges of modules satisfying the conditions of global minimality and thermodynamic stability. And various phase diagrams of the potential models are constructed, and based on these, the theoretical T-x-P phase diagram for Ni1-xCuxCr2O4 solid solutions is constructed, which is in good agreement with the experimental data.

Co-infection dynamics between HIV-HTLV-I disease with the effects of Cytotoxic T-lymphocytes, saturated incidence rate and study of optimal control

The spreading of HIV or HTLV-I among the cells has received the great attention in recent modelling study to explore the virus infection dynamics. The co-infection of HIV and HTLV-I with the effect of Cytotoxic T-lymphocytes (CTLs) immune response is also important from epidemiological point of view. To identify the co-infection scenario of HIV and HTLV-I with the CTLs effect we proposed in this paper a six compartmental ODE-model with uninfected, HIV-infected, HTLV-I infected CD4+T cells and free HIV virus particles with HIV specific CTLs and HTLV-I specific CTLs. The rates of infection of the cases are considered here saturated type and proliferation rate of uninfected and HIV infected CD4+ T-cells are of logistic terms. To establish the well-posedness of the model we have shown that the solution of the proposed model is non-negative and bounded. We obtain the basic reproduction number which is the maximum of the HIV-related reproduction and the HTLV-I related reproduction number. Along with the disease free equilibrium point the system contains other seven endemic equilibrium points containing infection by single disease or both. Analytically, we establish the local and global stability conditions of the equilibrium points and also we establish that the system experiences transcritical bifurcation by the generation of only HIV or HTLV-I infected endemic equilibrium point. Using numerical simulations, we validate the theoretical results and found two infection paths, one initiating with HIV and other with HTLV-I, both cases ultimately become co-infected. Finally, using the optimal control analysis we found the optimal policy for treatment using AVR, RTI & PI for HIV or AZT for HTLV-I control and lastly concluded by some recommendations.

Stability and Bifurcation Control for a Generalized Delayed Fractional Food Chain Model

In this paper, a generalized fractional three-species food chain model with delay is investigated. First, the existence of a positive equilibrium is discussed, and the sufficient conditions for global asymptotic stability are given. Second, through selecting the delay as the bifurcation parameter, we obtain the sufficient condition for this non-control system to generate Hopf bifurcation. Then, a nonlinear delayed feedback controller is skillfully applied to govern the system’s Hopf bifurcation. The results indicate that adjusting the control intensity or the control target’s age can effectively govern the bifurcation dynamics behavior of this system. Last, through application examples and numerical simulations, we confirm the validity and feasibility of the theoretical results, and find that the control strategy is also applicable to eco-epidemiological systems.