Article
Automation & Control Systems
Wei Mao, Surong You, Yanan Jiang, Xuerong Mao
Summary: This paper investigates the stabilization of hybrid neural networks using intermittent control based on continuous or discrete-time state observations. The stability criterion for hybrid neural networks under intermittent control with continuous-time state observations is established using exponential martingale inequality and the ergodic property of Markov chains. Furthermore, it is shown that hybrid neural networks can be stabilized by intermittent control based on discrete-time state observations using M-matrix theory and the comparison method. Two examples are provided to illustrate the theory.
NONLINEAR ANALYSIS-HYBRID SYSTEMS
(2023)
Article
Mathematics, Interdisciplinary Applications
Haiyan Yuan, Quanxin Zhu
Summary: This paper discusses the exponential stability of neutral stochastic functional differential equations with G-Levy jump. A discrete-time feedback control is designed to achieve feedback stability for a given mean square exponential unstable neutral stochastic differential equation. The H-infinity stable cadlag solution of the corresponding systems is obtained. The upper bound of state observation duration is derived and exponential stabilization conditions are established using the G-Lyapunov functional method. An example is presented to verify the results.
CHAOS SOLITONS & FRACTALS
(2023)
Article
Automation & Control Systems
Xiaoyue Li, Wei Liu, Qi Luo, Xuerong Mao
Summary: A new concept of stabilising hybrid stochastic systems in distribution using feedback controls based on discrete-time state observations is introduced in this paper. The theorems on the stabilisation of such systems are proved, and the lower bound of the duration between consecutive state observations is obtained. The implementation of the theorems is demonstrated through the design of feedback controls in different structures, and user-friendly rules are provided. Numerical examples are discussed to illustrate the theoretical results.
Article
Mathematics, Applied
Bingrui Zhang, Ailong Wu
Summary: This paper studies the stability of hybrid stochastic differential equations with multiple delays by intermittent control and time-varying delay observations. Sufficient criteria for ensuring the q-th moment exponential stability and almost sure exponential stability of the hybrid SDEs are derived using M-matrix theory, Lyapunov method, and the comparison principle. A simulation example is provided to illustrate the validity of the theoretical results.
MATHEMATICAL METHODS IN THE APPLIED SCIENCES
(2023)
Article
Automation & Control Systems
Wensheng Yin, Jinde Cao, Yong Ren, Guoqiang Zheng
Summary: This study offers new insights into the stabilization of stochastic differential equations driven by G-Brownian motion, providing specific discussions on pth moment and quasi-sure exponential stabilization problems through a comparative method. The exponential stabilization for equations with linear coefficients and equations with Lipschitz coefficients are demonstrated using tools from G-Ito stochastic analysis, along with an illustrative example.
SIAM JOURNAL ON CONTROL AND OPTIMIZATION
(2021)
Article
Mathematics
Pengju Duan
Summary: This paper investigates the exponential stability of a mild solution of stochastic differential equations driven by G-Brownian motion with aperiodically intermittent control. The addition of aperiodically intermittent control into the drift coefficients leads to the achievement of p-th exponential stability under suitable conditions. An example provided in the paper illustrates the effectiveness of the obtained results.
Article
Automation & Control Systems
Naiqin Zheng, Nani Han, Nallappan Gunasekaran
Summary: This paper investigates the exponential stability of stochastic complex networks with Markovian switching topologies. It emphasizes that the topological structure of the networks is Markovian switching and not all switching subnetworks need to have a spanning tree or be strongly connected. A new type of aperiodically intermittent discrete-time state observation control is proposed, which extends the existing discrete-time state observation control and intermittent control. Sufficient conditions for exponential convergence are derived based on the M-matrix, Lyapunov method, and graph theory. The average control rate in this paper is shown to be greater and less conservative than the rate proposed in existing literature. Theoretical results are applied to discuss the exponential stability of stochastic coupled oscillators and a communication network model, and numerical examples are given to verify the effectiveness of the results.
NONLINEAR ANALYSIS-HYBRID SYSTEMS
(2023)
Article
Engineering, Electrical & Electronic
Gongfei Song, Haiyang Wang, Tao Li, Yanqian Wang
Summary: This article presents new results on quantized discrete feedback control for stochastic delay systems using discrete-time state and mode observations (DSMO). The focus is on designing a control law that ensures stability of the integrated systems, even when the coefficients of the hybrid stochastic systems do not satisfy the linear growth condition (LGC). The correctness of these results is verified through a numerical case study.
CIRCUITS SYSTEMS AND SIGNAL PROCESSING
(2022)
Article
Mechanics
Gabriel Mercado-Vasquez, Denis Boyer, Satya N. Majumdar
Summary: Resetting the searcher's position to the starting point during a random search can decrease the mean completion time of the process. In this study, we theoretically investigate a protocol that can be implemented experimentally and exhibits unusual optimization properties. By controlling the switch-on and switch-off rates of the confining potential, various behaviors can be observed. These behaviors are not present in ideal resetting models.
JOURNAL OF STATISTICAL MECHANICS-THEORY AND EXPERIMENT
(2022)
Article
Automation & Control Systems
Pengfei Wang, Qianjing He, Huan Su
Summary: This article investigates the stabilization of discrete-time stochastic neural networks with time-varying delay using aperiodically intermittent control (AIC). It provides a comprehensive analysis of the stabilization of discrete-time delayed systems through AIC, exploring the Lyapunov function method and the Lyapunov-Krasovskii functional method. Three stabilization criteria are then presented, extending previous works from continuous-time to discrete-time frameworks, and the average activation time ratio (AATR) of AIC is estimated. It is highlighted that a more flexible estimation for the AATR can be obtained using the Lyapunov-Krasovskii functional method. Finally, numerical simulations are used to illustrate the differences and advantages of the three stabilization criteria.
IEEE TRANSACTIONS ON CYBERNETICS
(2023)
Article
Automation & Control Systems
Yihang Kong, Xinghui Zhang, Enyong Liu, Ancai Zhang, Jianlong Qiu
Summary: This research addresses the problem of finite-time tracking error constrained control for a class of non-strict stochastic nonlinear systems with unknown time-varying powers and multiple power terms. Based on the conversion from constrained tracking error to an unconstrained signal with the same effect, by adopting the backstepping technique together with adaptive neural network control, a controller with upper and lower time-varying power bounds is designed to meet the prescribed performance control scheme in finite-time. Finally, two simulation examples are shown to verify the effectiveness of the commendatory control method.
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS
(2023)
Article
Mechanics
Paul C. Bressloff
Summary: In this paper, diffusion in a domain Q with a partially absorbing target M and position and occupation time resetting is considered. The analysis of threshold absorption and the introduction of a generalized stochastic resetting protocol are presented. The study focuses on one-dimensional diffusion and explores the mean first passage time with resetting.
JOURNAL OF STATISTICAL MECHANICS-THEORY AND EXPERIMENT
(2022)
Article
Automation & Control Systems
Yanan Jiang, Liangjian Hu, Wei Mao, Jianqiu Lu, Xuerong Mao
Summary: This paper investigates the stabilization in distribution of hybrid stochastic differential equations (HSDEs) through periodically intermittent feedback controls. It is shown that the probability distributions of the solutions will converge to a stationary distribution. Firstly, sufficient conditions for stabilization in distribution of HSDEs are established using the theory of M-matrix and intermittent control strategy. Then, the existence and uniqueness of invariant probability distribution are proven, and the lower bound of the intermittent parameter 8* is obtained. Three numerical examples are discussed to support the theoretical analysis results.
NONLINEAR ANALYSIS-HYBRID SYSTEMS
(2023)
Article
Automation & Control Systems
Wei Mao, Junhao Hu, Xuerong Mao
Summary: For many real-world stochastic hybrid systems, it is more appropriate to discuss whether the probability distributions of their solutions will converge to a stationary distribution rather than studying if their solutions will converge to an equilibrium state. This article focuses on determining whether a stochastic state feedback control can make a given nonlinear hybrid differential equation, which is not stable in distribution, become stable in distribution. While the stabilisation by noise in terms of almost surely exponential stability of the equilibrium state has been well studied, little is known about the stabilisation in distribution by noise. This article initiates the study in this direction.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2023)
Article
Mathematics, Applied
Lichao Feng, Qiumei Liu, Jinde Cao, Chunyan Zhang, Fawaz Alsaadi
Summary: This paper investigates the stabilization of an unstable non-autonomous MJ-SDS system using discrete feedback control, and designs discrete control rules that can stabilize the system not only in terms of exponential decay rate, but also in terms of polynomial and general decay rates.
APPLIED MATHEMATICS AND COMPUTATION
(2022)
Article
Business, Finance
Chuangxia Huang, Yunke Deng, Xin Yang, Xiaoguang Yang, Jinde Cao
Summary: This paper aims to develop a novel network indicator for the rapid and accurate detection of financial crises. By constructing complex networks and extracting the Laplacian energy measure, this indicator successfully detects major financial events and outperforms traditional indicators in terms of accuracy and response speed.
EUROPEAN JOURNAL OF FINANCE
(2023)
Article
Computer Science, Artificial Intelligence
Ying Zhang, Rencan Nie, Jinde Cao, Chaozhen Ma
Summary: This paper proposes a self-supervised framework based on contrastive auto-encoding and convolutional information exchange for multi-modal medical fusion tasks. The proposed method constructs positive and negative result pairs and utilizes a novel contrastive loss to avoid information redundancy. It combines transformer and convolution neural networks in parallel to preserve both global and local features, and adopts a contribution estimation model for multi-modal medical image fusion. Experimental results show that the proposed method outperforms other state-of-the-art fusion approaches.
IEEE COMPUTATIONAL INTELLIGENCE MAGAZINE
(2023)
Article
Automation & Control Systems
Muhammed Syed Ali, Muhammed Haneef Mubeen Tajudeen, Grienggrai Rajchakit, Porpattama Hammachukiattikul, Jinde Cao
Summary: This study addresses the problem of fault-tolerant control for a multi-agent system with input delay and sensor failures. The communication topology is an undirected subgraph with directed connections between the followers and leader. The Lyapunov approach is used to identify criteria for consensus control. A fault-tolerant controller based on observed descriptors is proposed to solve actuator problems, sensor faults, and state estimations. The Artstein-Kwon-Pearson reduction method is applied to minimize data size. Numerical examples are provided to demonstrate the theoretical results.
ASIAN JOURNAL OF CONTROL
(2023)
Article
Mathematics, Interdisciplinary Applications
Wen-Jing Li, Zhi Chen, Jun Wang, Luo-Luo Jiang, Matjaz Perc
Summary: Relationships in social networks change over time due to factors such as mobility and preferences for moral behavior, which affect cooperation in collaborative networks. Individuals tend to move towards sites with high degrees, resulting in networks with higher average degrees and promoting cooperation. However, excessive mobility can lead to network structure dilution and well-mixed conditions. Optimal network reciprocity and robust cooperation require limited mobility, and similar patterns may apply to other forms of moral behavior.
CHAOS SOLITONS & FRACTALS
(2023)
Article
Mathematics, Interdisciplinary Applications
Peng Zhu, Min Xiao, Xia Huang, Fuchen Zhang, Zhen Wang, Jinde Cao
Summary: In recent years, the control of time evolution in ordinary differential systems has developed rapidly, while the control of spatiotemporal evolution dynamics in partial differential systems remains an open question. Turing pattern is a main spatiotemporal evolution behavior in mussel-algal ecosystems and controlling it can restore the ecosystem's stability. However, there has been limited research on the optimal control of Turing pattern in the mussel-algal system. This paper proposes a proportional-derivative (PD) control strategy for the reaction-diffusion mussel-algae model with time delays and demonstrates its efficiency and feasibility through numerical simulations.
CHAOS SOLITONS & FRACTALS
(2023)
Article
Automation & Control Systems
Taixiang Zhang, Xiaodi Li, Jinde Cao
Summary: This article studies the finite-time stability of impulsive switched systems and proposes sufficient criteria based on multiple Lyapunov functions and dwell time condition. The results show that by effectively controlling the impulses and dwell time, the system can be stabilized in finite time.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2023)
Article
Remote Sensing
Xianyue Wang, Longxia Qian, Jian Shi, Mei Hong, Jinde Cao
Summary: This article presents an efficient feature extraction framework, called the dual feature fusion model (DFFM), to address issues in hyperspectral image applications. The framework utilizes a novel two-order feature fusion and a valid three-order feature fusion method to maintain spatial structure integrity and save computing costs. It also automatically selects a suitable number of features and is robust to noise and training sets. Experimental results demonstrate that the framework outperforms state-of-the-art techniques in classification precision and execution time across various training sizes.
INTERNATIONAL JOURNAL OF REMOTE SENSING
(2023)
Article
Computer Science, Artificial Intelligence
Lianglin Xiong, Li Cai, Jinde Cao, Tao Wu, Haiyang Zhang
Summary: In this paper, the authors address the issue of stability and stabilization for semi-Markov jump memristive neural networks (SMJMNNs) with stochastic quantized sampled-data control (QSDC) law. They establish a model of memristive neural network (MNN) with mixed semi-Markov jump and propose a stochastic QSDC scheme that considers the influence of transmission delay. They also develop a more general weak infinitesimal operator and construct stochastic Lyapunov functionals (LFs) to reduce conservatism and establish a stochastic stability criterion for SMJMNNs based on the constructed LFs.
KNOWLEDGE-BASED SYSTEMS
(2023)
Article
Computer Science, Artificial Intelligence
Yanbu Guo, Dongming Zhou, Xiaoli Ruan, Jinde Cao
Summary: The study presents a feature extraction model based on variational gated autoencoder for inferring potential disease-miRNA associations. Experimental results show that the proposed model achieves remarkable association prediction performance, validating the efficacy of the variational gate mechanism and contrastive cross-entropy loss for inferring disease-miRNA associations.
Article
Physics, Multidisciplinary
Yuwei Yang, Zhuoxuan Li, Jun Chen, Zhiyuan Liu, Jinde Cao
Summary: This paper proposes an extreme learning machine (ELM) algorithm based on residual correction and Tent chaos sequence (TRELM-DROP) for accurate prediction of traffic flow. The algorithm reduces the impact of randomness in traffic flow through the Tent chaos strategy and residual correction method, and avoids weight optimization using the iterative method. A DROP strategy is introduced to improve the algorithm's ability to predict traffic flow under varying conditions.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Multidisciplinary Sciences
Andre S. S. Sunahara, Arthur A. B. Pessa, Matjaz Perc, Haroldo V. V. Ribeiro
Summary: This study investigates the COVID-19 pandemic in the city of Maringa, Brazil, and finds that despite prompt and robust interventions, cases increased exponentially during the early spread of the disease. Non-pharmaceutical interventions had a significant impact on controlling the pandemic, but the city's measures were primarily reactive. Maringa faced six waves of cases, with the third and fourth waves being the deadliest and overwhelming the local healthcare system. The study highlights the heterogeneities in the spread and impact of the disease compared to the national context and other similarly sized cities. Importance rating: 8 out of 10.
SCIENTIFIC REPORTS
(2023)
Article
Automation & Control Systems
Xiaodi Li, Wenlu Liu, Sergey Gorbachev, Jinde Cao
Summary: This article investigates the event-triggered impulsive control (ETIC) problem for a class of nonlinear time-delay systems subject to exogenous disturbances. An original event-triggered mechanism (ETM) based on Lyapunov function approach is constructed, which utilizes the information of system state and external input. The article presents sufficient conditions for achieving input-to-state stability (ISS) of the considered system and establishes the relationship among ETM, exogenous input, and impulse action. The article also excludes possible Zeno behavior induced by the proposed ETM and provides the design criterion for ETM and impulse gain for impulsive control systems with delay.
IEEE TRANSACTIONS ON CYBERNETICS
(2023)
Article
Engineering, Electrical & Electronic
Hongling Qiu, Jun Shen, Jinde Cao, Heng Liu
Summary: This paper investigates the Loo-gain of incommensurate fractional-order delayed positive systems (FODPSs). It proposes necessary and sufficient criteria for achieving the positivity and stability of FODPSs with mixed delays. The validity of the theoretical results is demonstrated through numerical simulation.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS
(2023)
Article
Mathematics, Applied
Wenjie Li, Yajuan Guan, Jinde Cao, Fei Xu
Summary: This article establishes the global stability of the disease-free equilibrium in a degenerate diffusion system involving environmental transmission and spatial heterogeneity. It provides important insights into the transmission dynamics of avian influenza virus among avian, poultry, and human populations.
APPLIED MATHEMATICS LETTERS
(2024)
Article
Computer Science, Artificial Intelligence
Hanjie Liu, Jinde Cao, Wei Huang, Xinli Shi, Xingye Zhou, Zhuoxuan Li
Summary: A data-driven multidimensional framework is proposed to evaluate pavement condition by utilizing multilayer network representation learning. The method can capture the nonlinear interactions among performance attributes and provide a more in-depth understanding of pavement service condition. Experimental results demonstrate the effectiveness of this method in multi-attribute evaluation.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
