Article
Computer Science, Artificial Intelligence
Kai Wu, Jigui Jian
Summary: This article focuses on the global robust exponential dissipativity (GRED) of uncertain second-order BAM neural networks with mixed time-varying delays. New differential inequalities and Lyapunov-Krasovskii functionals are established to present new GRED criteria in the form of linear matrix inequalities. The correctness of the theoretical results is verified through simulation experiments.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2021)
Article
Computer Science, Artificial Intelligence
Yin Sheng, Tingwen Huang, Zhigang Zeng, Xiangshui Miao
Summary: This article investigates the Lagrange exponential stability and the Lyapunov exponential stability of memristive neural networks with discrete and distributed time-varying delays. The study uses inequality techniques, theories of the M-matrix, and the comparison strategy to consider the stability of the networks, providing less conservative methods for analyzing Lyapunov stability.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2021)
Article
Automation & Control Systems
Juan G. Rueda-Escobedo, Rene Metzkow, Johannes Schiffer
Summary: Interior permanent magnet synchronous machines (IPMSMs) are gaining popularity in e-mobility applications due to their wide constant power speed range when compared with other electric motors. However, the embedded magnets inside the rotor of IPMSMs introduce nonlinear phenomena and variations in the machine inductances, which complicate their control. We propose a control approach that exploits machine dynamics to achieve exponential current tracking in the presence of unknown and varying inductances.
Article
Computer Science, Artificial Intelligence
Qiao Chen, Xinge Liu, Xuemei Li
Summary: This paper presents an improved approach for the exponential stability of neural networks with time-varying delay, establishing a less conservative stability criterion by combining various inequalities. The effectiveness and benefits of the proposed method are illustrated through several numerical examples.
NEURAL COMPUTING & APPLICATIONS
(2022)
Article
Automation & Control Systems
El Hafid Chelliq, Mohammed Alfidi, Zakaria Chalh
Summary: In this paper, the admissibility and robust H infinity controller design are investigated for uncertain 2-D continuous singular systems with interval time-varying delays and norm-bounded parameter uncertainties. A new delay-dependent admissibility condition is obtained by utilizing an augmented Lyapunov-Krasovskii's functional and combining the Wirtinger inequality with an improved reciprocally convex approach. Then, a robust controller is designed based on a linear matrix inequality. Numerical examples are presented to demonstrate the effectiveness of the proposed methods.
INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE
(2023)
Article
Mathematics, Applied
Jie Pan, Zhaoya Pan
Summary: This paper focuses on the robust stability of uncertain parameter quaternionic neural networks (QNNs) with both time-varying delays and infinite distributed delays. A derivative formula of quaternionic function's norm is established to obtain algebraic standards for global robust exponential stability. The whole quaternionic method can reduce computation cost and is validated through numerical simulations.
APPLIED MATHEMATICS AND COMPUTATION
(2021)
Article
Automation & Control Systems
Tamas Baar, Tamas Luspay
Summary: The article presents a robust subsystem decoupling framework for uncertain linear systems with linear fractional representation. The proposed method relies on the synthesis of input- and output transformations to maximize excitation in a selected subsystem and minimize its effect on other parts of the dynamics. The optimization problem is subject to linear matrix inequality constraints and can be effectively solved. Numerical examples are provided to demonstrate the method and its possible applications.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2022)
Article
Computer Science, Interdisciplinary Applications
K. Pooja Lakshmi, T. Senthilkumar
Summary: This paper discusses the synchronization results of uncertain infinite time-varying flexible delayed impulsive neural networks with and without distributed delay, including robust exponential synchronization (RES) and exponential synchronization (ES). A new lemma based on the fundamental solution matrix is introduced to solve nonlinear neural networks using average impulsive interval (AII) and average impulsive delay (AID). Novel RES and ES results are examined for the proposed neural networks using the method of variation of constants. Numerical examples validate the proposed results and graphical representations demonstrate the effectiveness of flexible delayed impulsive control.
MATHEMATICS AND COMPUTERS IN SIMULATION
(2023)
Article
Computer Science, Artificial Intelligence
Xing He, Yu-bin Wu, Li-jun Song
Summary: The paper proposes an improved robust stability analysis method for linear systems with norm-bounded uncertainty and interval time-varying delay. The method divides the delay interval into multiple subintervals and introduces a new Lyapunov-Krasovskii functional for each subinterval. A novel delay-dependent stability criterion is proved using integral inequality approach. Numerical examples and a power system are used to verify the effectiveness of the proposed method.
Article
Physics, Applied
Weipeng Tai, Dong Xu, Tong Guo, Jianping Zhou
Summary: This paper proposes a design method based on linear matrix inequalities for exponential passive filter design of switched neural networks with time-delay and reaction-diffusion terms. By separating the system into real-valued and complex-valued parts, the method can be extended to the complex-valued case as well.
MODERN PHYSICS LETTERS B
(2021)
Article
Mathematics, Applied
Suriguga, Yonggui Kao, Chuntao Shao, Xiangyong Chen
Summary: This paper investigates the mean square exponential stability of high-order Markovian jump reaction-diffusion HNNs with uncertain transition rates and time-varying delays using Lyapunov-Krasovskii functional method and LMI. The study shows that the known information of part of the transition rates can reveal the stability of the system. A numerical example is provided to illustrate the validity of the model.
APPLIED MATHEMATICS AND COMPUTATION
(2021)
Article
Mathematics, Applied
A. Nasira Banu, K. Banupriya, R. Krishnasamy, A. Vinodkumar
Summary: This paper investigates the problem of robust stability analysis for a type of uncertain stochastic switched inertial neural networks (SSINNs) with time-varying delay. The original second-order system is transformed into first-order differential equations using the variable transformation method. Sufficient conditions in terms of linear matrix inequalities (LMIs) are obtained using Lyapunov-Krasovskii functional (LKF), state-dependent switching (SDS) method, and Jensen's integral inequality to ensure the robust, global, and asymptotic stability of the uncertain SSINNs with time-varying delay. It is demonstrated that the stability of the system composed of all unstable subsystems can be achieved by utilizing the SDS law. Numerical simulations are provided to validate the effectiveness of the proposed SDS law.
MATHEMATICAL METHODS IN THE APPLIED SCIENCES
(2023)
Article
Automation & Control Systems
Yassine Boukal, Mohamed Zasadzinski, Michel Darouach, Nour Eddine Radhy
Summary: This article presents a robust H-infinity observer-based controller for Uncertain Fractional-Order Systems with Time-Varying-Delay, ensuring the stability of estimation errors and system stabilization through a convex optimization problem with a Linear Matrix Inequality constraint.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2021)
Article
Computer Science, Artificial Intelligence
Hong Cheng, Xiucai Huang, Hongwei Cao
Summary: This paper proposes a method to achieve asymptotic tracking control for uncertain nonlinear strict-feedback systems with unknown time-varying delays and unknown control direction. The Lyapunov-Krasovskii functional is used to deal with the time delays, and the neural network is applied to compensate for the unknown terms arising from the derivative of the Lyapunov-Krasovskii functional. An NN-based adaptive control scheme is constructed based on backstepping technique, and the output tracking error is ensured to converge to zero asymptotically. The proposed method settles the singularity issue commonly encountered in coping with time delay problems and improves the transient performance with proper choice of design parameters.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2023)
Article
Energy & Fuels
Adrian Ramirez
Summary: This research proposes the use of intentional time delays as part of controllers to achieve proper output voltage regulation in fuel cell systems. Through stability theory, simple stability conditions are derived to achieve robustness and H-infinity performance based on Lyapunov methods and L-2 gain analysis.
INTERNATIONAL JOURNAL OF ENERGY RESEARCH
(2022)
Article
Mathematics, Interdisciplinary Applications
Bo Li, Tian Huang
Summary: This paper proposes an approximate optimal strategy based on a piecewise parameterization and optimization (PPAO) method for solving optimization problems in stochastic control systems. The method obtains a piecewise parameter control by solving first-order differential equations, which simplifies the control form and ensures a small model error.
CHAOS SOLITONS & FRACTALS
(2024)
Article
Mathematics, Interdisciplinary Applications
Guram Mikaberidze, Sayantan Nag Chowdhury, Alan Hastings, Raissa M. D'Souza
Summary: This study explores the collective behavior of interacting entities, focusing on the co-evolution of diverse mobile agents in a heterogeneous environment network. Increasing agent density, introducing heterogeneity, and designing the network structure intelligently can promote agent cohesion.
CHAOS SOLITONS & FRACTALS
(2024)
Article
Mathematics, Interdisciplinary Applications
Gengxiang Wang, Yang Liu, Caishan Liu
Summary: This investigation studies the impact behavior of a contact body in a fluidic environment. A dissipated coefficient is introduced to describe the energy dissipation caused by hydrodynamic forces. A new fluid damping factor is derived to depict the coupling between liquid and solid, as well as the coupling between solid and solid. A new coefficient of restitution (CoR) is proposed to determine the actual physical impact. A new contact force model with a fluid damping factor tailored for immersed collision events is proposed.
CHAOS SOLITONS & FRACTALS
(2024)
