Article
Automation & Control Systems
Qianghui Zhou, Xiang Xu, Lu Liu, Gang Feng
Summary: This article investigates the output feedback stabilization problem of linear time-varying (LTV) systems with infinite distributed input delays. A novel observer is designed to estimate the system states and then a low gain output feedback controller is developed based on the estimated states. The resulting closed-loop control system is shown to be globally exponentially stable under some mild assumptions. To the best of our knowledge, the output feedback stabilization problem of LTV systems with infinite distributed input delays has not yet been studied in open literature. Two numerical examples are provided to illustrate the effectiveness of the proposed controllers.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2023)
Article
Automation & Control Systems
Stephen Arockia Samy, Yang Cao, Raja Ramachandran, Jehad Alzabut, Michal Niezabitowski, Chee Peng Lim
Summary: This article investigates the global asymptotic stability and synchronization analysis of uncertain multi-agent systems with multiple time-varying delays and impulsive perturbations. Through mathematical proofs, the existence and uniqueness of equilibrium points are established, and a pining control strategy is designed to achieve global asymptotic stability and synchronization. Numerical calculations and simulations are provided to verify the theoretical findings.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2022)
Article
Mathematics, Interdisciplinary Applications
Jin Yang, Jigui Jian
Summary: This paper focuses on the existence conditions of quasi-invariant set, global attracting set, and global exponential attracting set of competitive neural networks with time-varying and infinite distributed delays. A new bidirectional delay integral inequality and a novel integro-differential inequality are established. The obtained conditions and frameworks provide insights into the dynamics of the discussed system.
CHAOS SOLITONS & FRACTALS
(2023)
Article
Mathematics, Applied
JunMin Park, Nam Kyu Kwon, Seok Young Lee
Summary: This paper addresses the stability analysis of linear discrete-time systems with time-varying delays. To reduce conservatism in stability criteria, the paper proposes extended affine Bessel summation inequalities that provide affine upper bounds of an extended summation quadratic function. It also provides notes on the correlation among several summation inequalities, demonstrating that an increase in the degree of the developed affine Bessel summation inequalities only reduces conservatism. Two numerical examples effectively demonstrate the reduction of conservatism due to the proposed summation inequalities in terms of stability regions expressed as delay bounds.
APPLIED MATHEMATICS AND COMPUTATION
(2023)
Article
Computer Science, Artificial Intelligence
Tingting Zhang, Jigui Jian
Summary: This article studies the global asymptotic synchronization of second-order fuzzy memristive neural networks with infinite distributed and time-varying delays through feedback control and adaptive control schemes. New criteria are directly acquired based on Lyapunov stability theory and Barbalat Lemma to ensure the synchronization. The global asymptotic synchronization is directly analyzed via new Lyapunov-Krasovskii functionals without reduced-order means, compared to existing methods.
KNOWLEDGE-BASED SYSTEMS
(2021)
Article
Automation & Control Systems
Yin Sheng, Zhigang Zeng, Tingwen Huang
Summary: This article investigates the global stability of bidirectional associative memory neural networks with discrete and distributed time-varying delays. The research focuses on the global asymptotic stability and global exponential stability of the networks, using comparison strategy and inequality techniques. The results show that the stability of the networks has certain special properties.
IEEE TRANSACTIONS ON CYBERNETICS
(2022)
Article
Mathematics
Issaraporn Khonchaiyaphum, Nayika Samorn, Thongchai Botmart, Kanit Mukdasai
Summary: This research investigates finite-time passivity analysis of neutral-type neural networks with mixed time-varying delays. New sufficient conditions for finite-time stability and passivity are proposed and demonstrated through numerical examples. The proposed criteria are less conservative than prior studies in terms of larger time-delay bounds.
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
Antonio Gonzalez, Pedro Garcia
Summary: This study investigates the robust stabilization of discrete-time systems with time-varying input delays and model uncertainties using predictor-based anti-disturbance output-feedback control strategies. By considering unknown but bounded time-varying delays, the complexity of the control synthesis algorithm is notably reduced. An illustrative example from the literature demonstrates the superior robust performance of the proposed method.
Article
Automation & Control Systems
Yige Guo, Xiang Xu, Lu Liu, Yong Wang, Gang Feng
Summary: This paper investigates the stabilization problem of discrete-time linear systems with infinite distributed input delays. A novel framework is adopted to analyze the stability of the concerned systems. Two truncated predictor feedback controllers are developed for two classes of discrete-time linear systems with infinite distributed input delays via the low gain method, and it is shown that these systems are globally exponentially stable under the designed controllers. This is the first time that the stabilization problem of discrete-time linear systems with infinite distributed input delays is considered, and simulation examples demonstrate the effectiveness of the proposed controllers.
Article
Automation & Control Systems
Haik Silm, Rosane Ushirobira, Denis Efimov, Emilia Fridman, Jean-Pierre Richard, Wim Michiels
Summary: The distributed estimation problem for continuous-time observer nodes is addressed in this paper, with a focus on modeling digital communication with variable sampling intervals, transmission delays, and packet dropouts. An LMI for designing observer gains is derived using Halanay's inequality, ensuring exponential stability with a selected convergence rate. A comparison of the maximal delay in a numerical example demonstrates the advantage of a distributed observer over a centralized one.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2021)
Article
Mathematics, Applied
Chen Wang, Hai Zhang, Hongmei Zhang, Weiwei Zhang
Summary: This paper discusses the globally projective synchronization of Caputo fractional-order quaternion-valued neural networks, deriving an algebraic criterion without decomposing the networks into subsystems. The effectiveness of the proposed result is illustrated through MATLAB toolboxes and numerical simulations.
Article
Chemistry, Multidisciplinary
Siheng Zong, Yu-Ping Tian
Summary: This paper investigates the consensus problem of multi-agent systems with increasing communication distances, modeling the system using a time-delay system. It is proven that under certain topological conditions, the system can achieve consensus, and the growth rate of the maximum delay is negatively correlated with the rate of achieving consensus.
APPLIED SCIENCES-BASEL
(2021)
Article
Mathematics, Applied
Jenjira Thipcha, Presarin Tangsiridamrong, Thongchai Botmart, Boonyachat Meesuptong, M. Syed Ali, Pantiwa Srisilp, Kanit Mukdasai
Summary: This paper investigates the robust stability analysis issue for discrete-time neural networks with interval time-varying leakage and discrete and distributed delays using a rebuilt summation inequality. A novel inequality, less conservative than the well-known Jensen inequality, is considered and applied in the context of discrete-time delay systems. Stability and passivity criteria are obtained in terms of linear matrix inequalities (LMIs) using various techniques. Numerical examples are provided to demonstrate the validity and efficiency of the theoretical findings of this research with the assistance of the LMI Control toolbox in Matlab.
Article
Computer Science, Artificial Intelligence
Hao Zhang, Zhigang Zeng
Summary: This paper revisits the drive-response synchronization of a class of recurrent neural networks with unbounded delays and time-varying coefficients. A generalized scalar delay differential inequality considering indefinite self-feedback coefficient and unbounded delay is established, and novel criteria for network synchronization are derived. The results have been improved compared to existing ones, and a vector form differential inequality is derived to obtain a more refined synchronization criterion.
