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The purpose of this paper is to develop a method for the existence, uniqueness and globally robust stability of the equilibrium point for Cohen–Grossberg neural networks with time-varying delays, continuous distributed delays and a kind of discontinuous activation functions.

Based on the Leray–Schauder alternative theorem and chain rule, by using a novel integral inequality dealing with monotone non-decreasing function, the authors obtain a delay-dependent sufficient condition with less conservativeness for robust stability of considered neural networks.

It turns out that the authors’ delay-dependent sufficient condition can be formed in terms of linear matrix inequalities conditions. Two examples show the effectiveness of the obtained results.

The novelty of the proposed approach lies in dealing with a new kind of discontinuous activation functions by using the Leray–Schauder alternative theorem, chain rule and a novel integral inequality on monotone non-decreasing function.

The susceptible-infectious-susceptible (SIS) infectious disease models without spatial heterogeneity have limited applications, and the numerical simulation without considering models’ global existence and uniqueness of classical solutions might converge to an impractical solution. This paper aims to develop a robust and reliable numerical approach to the SIS epidemic model with spatial heterogeneity, which characterizes the horizontal and vertical transmission of the disease.

This study used stability analysis methods from nonlinear dynamics to evaluate the stability of SIS epidemic models. Additionally, the authors applied numerical solution methods from diffusion equations and heat conduction equations in fluid mechanics to infectious disease transmission models with spatial heterogeneity, which can guarantee a robustly stable and highly reliable numerical process. The findings revealed that this interdisciplinary approach not only provides a more comprehensive understanding of the propagation patterns of infectious diseases across various spatial environments but also offers new application directions in the fields of fluid mechanics and heat flow. The results of this study are highly significant for developing effective control strategies against infectious diseases while offering new ideas and methods for related fields of research.

Through theoretical analysis and numerical simulation, the distribution of infected persons in heterogeneous environments is closely related to the location parameters. The finding is suitable for clinical use.

The theoretical analysis of the stability theorem and the threshold dynamics guarantee robust stability and fast convergence of the numerical solution. It opens up a new window for a robust and reliable numerical study.

This study aims to determine how Basel III capital requirements affect the stability of Islamic banks globally during the global financial crisis and the COVID-19 pandemic.

The secondary data for all Islamic banks worldwide from 2004 to 2021 is obtained from the FitchConnect database. The main technique was a two-step generalized method of moment (GMM) system, and the data were tested using pooled ordinary least squares, fixed effects and difference GMM models for robustness checks.

Regression results support the moral hazard hypothesis based on evidence that both the total capital ratio and the Tier 1 capital ratio have a statistically significant positive impact on the stability of Islamic banks globally. Furthermore, neither the global financial crisis of 2008–2009 nor COVID-19 (2020–2021) significantly impacted the stability of Islamic banks worldwide. The results are robust across alternative measures of stability, capital buffers, dummy variables and estimation techniques. According to the descriptive statistics, the number of Islamic banks that disclose their regulatory capital ratios to the public has increased over the study period, and the mean of total capital and Tier 1 ratios are considerably greater than what is required by Basel II and Basel III.

Bankers, regulators and policymakers should benefit from the evidence on capital and risk management in Islamic banking according to Basel Committee on Banking Supervision (BCBS) and Islamic financial services board (IFSB) international standards in various jurisdictions.

This research builds on earlier studies that were both beneficial and instructive by exploring the relationship between BCBS and IFSB capital guidelines and the trustworthiness of Islamic banks in greater depth. This study uses numerous capital ratios, buffers and stability measures to provide an international context for research on Islamic banking. In addition, the database is up-to-date to include information about the COVID-19 pandemic aftereffects in the year 2021. This study also introduces the Basel membership of Islamic banks to provide context for countries still at the Basel II stage or are yet to begin implementing the Basel III international standard.

Trajectory tracking is an important issue to underactuated unmanned surface vehicles (USVs). However, parametric uncertainties and environmental disturbances bring great challenges to the precise trajectory tracking control of USVs. This paper aims to propose a robust trajectory tracking control algorithm with exponential stability for underactuated USVs with parametric uncertainties and unknown environmental disturbances.

In this method, the backstepping method and sliding mode control method are combined to ensure that the underactuated USV can track and maintain the desired trajectory. In addition, a modified switching-gain adaptation algorithm is adopted to enhance the robustness and reduce chattering. Besides, the global exponential stability of the closed-loop system is proved by Lyapunov’s direct method.

The proposed method in this paper offers a robust trajectory tracking solution to underactuated USVs and it is verified by simulations and experiments. Compared with the traditional proportion-integral-derivative method and several state-of-the-art algorithms, the proposed method has superior performance in simulation and experimental results.

This paper proposes a robust trajectory tracking control algorithm with exponential stability for underactuated USVs. The proposed method achieves exponential stability with better robustness and transient performance.

This study aims to analyze the factors that influenced the stability of Islamic banks in Asia.

The panel data consisted of 16 Asian countries operating Islamic banks from 2010 to 2019. The data were analyzed through dynamic panel regression using Arellano–Bond generalized method of moments (GMM).

This study provides novel insights into the factors influencing the stability of Islamic banks in Asia. The findings suggest that past financial stability, liquidity risk, loan risk, inflation, gross domestic product, government effectiveness, rule of law and control of corruption are all significant contributors to Islamic bank stability. Notably, political stability, voice and accountability and regulatory quality did not show a significant association.

The current study’s focus was solely on Islamic bank stability in Asian countries, which leaves room for further exploration. Future research could benefit from expanding the scope to encompass all nations with active Islamic banking institutions. In addition, incorporating a broader range of macroeconomic variables, such as exchange rates, interest rates, profit-sharing equivalents and investment rates, could provide deeper insights into the factors influencing Islamic bank stability across diverse contexts.

This study has significant practical implications for policymakers, bank managers and regulatory authorities seeking to enhance the stability of Islamic banks in Asia. By implementing robust risk management frameworks, adopting prudent regulatory policies, and actively fostering economic growth, policymakers can create an environment conducive to the sustained development and prosperity of Islamic banking institutions. Notably, promoting good governance practices and instituting effective crisis prevention measures can further bolster the resilience of the Islamic banking sector, enabling it to play a more dynamic role in contributing to the overall development and welfare of Asian societies.

The findings of this study carry significant social implications, highlighting the need for governments in Asian countries to prioritize public policies that promote good governance and ethical practices within the banking industry. Such policies, coupled with efforts to attract foreign investments and foster a stable and transparent banking sector, have the potential to generate far-reaching positive effects on society. Through economic growth stimulated by a robust Islamic banking sector, Asian countries can create new employment opportunities, improve living standards and ultimately enhance the overall well-being of their citizens.

This study contributes to the ongoing discourse on Islamic banking stability by offering novel insights and expanding the empirical knowledge base in this field. The dual application of robust regression methodologies – namely, GMM dynamic panel data models – presents a unique analytical framework for investigating the complex interplay between diverse variables and Islamic bank stability. This methodological choice fosters deeper understanding of the dynamic relationships at play, advancing our understanding of how specific factors influence the sector's resilience and performance. In addition, the study uses rigorous empirical techniques and engages with the extant literature to provide fresh perspectives and nuanced interpretations of the findings, further solidifying its contribution to the field's originality and richness.

This paper aims to present a three-axis attitude tracking control law to solve the attitude maneuver of a flexible satellite in the presence of parameter uncertainties and external disturbance.

Based on the relative dynamic equation where the relative attitude is described by quaternion, a robust control law composed of a proportional derivative (PD) part plus a signum function is designed and only requires the measurement of attitude and angular velocity. Furthermore, the stability analysis of the proposed control law is given through a two-step proof technique.

Numerical simulation results demonstrate that fine convergence of the attitude and angular velocity error and low-level vibration of flexible appendages are obtained by the proposed controllers.

The controller with the structure of a PD term plus a switching function about a sliding variable has low computational complexity and does not need to measure the modal variables of elastic appendages, so it can be used in orbit without modification.

The globally asymptotic stability of the controller in the presence of model uncertainties and external disturbances is proven rigorously through a two-step proof technique.

The purpose of this paper is to present a sliding mode controller design method for a class of uncertain nonlinear systems with uncertainties and to demonstrate a recursive derivative estimation procedure for the derivatives of system outputs.

A recursive derivative estimation procedure for the derivatives of system outputs is demonstrated. Radial basis function (RBF) neural networks are used to approximate the uncertainties and filters are introduced to estimate the derivatives of system outputs step‐by‐step. The adaptive tuning rules of RBF neural network weight matrices are derived by the Lyapunov stability theorem, which guarantees filter errors and network weight errors are bounded and exponentially converge to a neighborhood of the origin globally. The sliding mode controller is designed based on the estimation for the derivatives of system outputs such that the sliding surface converges to zero and the system control input is bounded.

The sliding mode controller can make the system output track the desired output with arbitrarily small tracking error. The filter errors and network weight estimation errors can be made arbitrarily small, and all the system signals are bounded. The proposed method does not need the supper bounds of the unmatched uncertainties and their any order derivatives.

The system output and uncertainties are required to be sufficiently smooth in the proposed method. In practice, this condition is always satisfied generally.

This paper contains very useful advice for researchers on the sliding mode control and the use of neural networks.

The paper presents a new sliding mode controller design method based on recursive derivative estimation of system outputs using neural networks. The paper is aimed at theoretical researchers, especially those who have interest in sliding mode control, neural networks, adaptive techniques, and recursive estimation.

Quadrotor micro aerial vehicle (MAV) is nonlinear and under actuated plant, and it is difficult to obtain an accurate mathematical model for quadrotor MAV due to uncertainties. The purpose of this paper is to propose one robust control strategy for quadrotor MAV to accommodate system uncertainties, variations, and external disturbances.

The robust control strategy is composed of two self‐organizing interval type‐II fuzzy neural networks (SOIT‐IIFNNs) and one PD controller: the PD controller is adopted to control the attitude and position; one of the SOIT‐IIFNNs is designed to learn the inverse model of quadrotor MAV online; the other SOIT‐IIFNNs is the copy of the former one to compensate for model errors, system uncertainties and external disturbances, both structure and parameters of SOIT‐IIFNNs are tuned online at the same time, and then the stability of the resulting quadrotor MAV closed‐loop control system is proved using Lyapunov stability theory.

The validity of the proposed control method has been verified through real‐time experiments. The experimental results show that the performance of SOIT‐IIFNNs is significantly improved compared with Backstepping‐based controller.

This approach has been used in quadrotor MAV, the controller works well, and it could guarantee quadrotor MAV control system with good performances under uncertainties, variations, and external disturbances.

The proposed SOIT‐IIFNNs controller is interesting for the design of an intelligent control scheme. The main contributions of this paper are: the overall closed‐loop control system is globally stable, demonstrated by Lyapunov stable theory; the tracking error can be asymptotically attenuated to a desired small level around zero by appropriate chosen parameters and learning rates; and the quadrotor MAV control system based on SOIT‐IIFNNs controller can achieve favorable tracking performance.

In this paper, the authors take an amorphous flattened air-ground wireless self-assembling network system as the research object and focus on solving the wireless self-assembling network topology instability problem caused by unknown control communication faults during the operation of this system.

In the paper, the authors propose a neural network-based direct robust adaptive non-fragile fault-tolerant control algorithm suitable for the air-ground integrated wireless ad hoc network integrated system.

The simulation results show that the system eventually tends to be asymptotically stable, and the estimation error asymptotically tends to zero with the feedback adjustment of the designed controller. The system as a whole has good fault tolerance performance and autonomous learning approximation performance. The experimental results show that the wireless self-assembled network topology has good stability performance and can change flexibly and adaptively with scene changes. The stability performance of the wireless self-assembled network topology is improved by 66.7% at maximum.

The research results may lack generalisability because of the chosen research approach. Therefore, researchers are encouraged to test the proposed propositions further.

This paper designs a direct, robust, non-fragile adaptive neural network fault-tolerant controller based on the Lyapunov stability principle and neural network learning capability. By directly optimizing the feedback matrix K to approximate the robust fault-tolerant correction factor, the neural network adaptive adjustment factor enables the system as a whole to resist unknown control and communication failures during operation, thus achieving the goal of stable wireless self-assembled network topology.

Amidst the backdrop of a wide array of structural developments that have revolutionized the competitive landscape of Indian commercial banking, this paper aims to empirically examine the role of two external monitoring mechanisms – competition and concentration on financial stability and further highlights the significance of bank-level heterogeneity in the nexus.

The study uses the Lerner index, defined through a translog specification, as a measure of market power. A system generalized method of moments technique accounts for the dynamic associations among the competition-concentration-stability nexus. The study further examines the moderating effect of ownership, size and capitalization on the nexus. The study also uses the Boone indicator and comments on the competition-bank stability relationship after controlling for bank governance.

The findings indicate that banks are less stable in a more competitive and higher concentrated environment. Exploring bank-level heterogeneity, first, the authors report that as competition increases, state-owned banks have greater incentives to undertake risky activities than private and foreign banks, which point to implicit sovereign guarantees that characterize the former. Second, the authors document an adverse influence of competition on the soundness of larger banks consistent with the “too-big-to-fail” assertion. Third, results corroborate the disciplinary role of regulatory capital and lend support to stricter capital norms under Basel III in a more competitive environment.

This paper is perhaps the first to capture competition and concentration in a single model; to reconcile conflicting evidence on competition-risk nexus; to shed light on the joint effect of competition and Basel accords for Indian banks.