Hong‐Bing Zeng

ORCID: 0000-0002-0226-2405
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About
Contact & Profiles
Research Areas
  • Stability and Control of Uncertain Systems
  • Neural Networks Stability and Synchronization
  • Matrix Theory and Algorithms
  • Stability and Controllability of Differential Equations
  • Advanced Memory and Neural Computing
  • Chaos control and synchronization
  • Neural Networks and Applications
  • Nonlinear Dynamics and Pattern Formation
  • Control Systems and Identification
  • Adaptive Control of Nonlinear Systems
  • stochastic dynamics and bifurcation
  • Quantum chaos and dynamical systems
  • Elasticity and Wave Propagation
  • Frequency Control in Power Systems
  • Microgrid Control and Optimization
  • Control and Stability of Dynamical Systems
  • Advanced Differential Equations and Dynamical Systems
  • Power System Optimization and Stability
  • Advanced Decision-Making Techniques
  • Muscle activation and electromyography studies
  • Geological Modeling and Analysis
  • Chaos-based Image/Signal Encryption
  • Prosthetics and Rehabilitation Robotics
  • Spectral Theory in Mathematical Physics
  • Distributed Control Multi-Agent Systems

Hunan University of Technology
2016-2025

Beijing Jingshida Electromechanical Equipment Research Institute
2022

Curtin University
2017

Yeungnam University
2014-2015

Central South University
2010-2014

Tongji Hospital
2012

Huazhong University of Science and Technology
2012

Chengdu Second People's Hospital
2011

Southwest Jiaotong University
2011

The free-weighting matrix and integral-inequality methods are widely used to derive delay-dependent criteria for the stability analysis of time-varying-delay systems because they avoid both use a model transformation technique bounding cross terms. This technical note presents new integral inequality, called free-matrix-based that further reduces conservativeness in those methods. It includes well-known inequalities as special cases. Using it investigate with time-varying delays yields less...

10.1109/tac.2015.2404271 article EN IEEE Transactions on Automatic Control 2015-02-19

10.1016/j.apm.2018.08.012 article EN publisher-specific-oa Applied Mathematical Modelling 2018-08-24

This article deals with the stability of neural networks (NNs) time-varying delay. First, a generalized reciprocally convex inequality (RCI) is presented, providing tight bound for combinations. includes some existing ones as special case. Second, in order to cater use RCI, novel Lyapunov-Krasovskii functional (LKF) constructed, which delay-product term. Third, based on RCI and LKF, several criteria delayed NNs under study are put forward. Finally, two numerical examples given illustrate...

10.1109/tnnls.2022.3144032 article EN IEEE Transactions on Neural Networks and Learning Systems 2022-02-02

This paper concerns the tracking control problem of nonlinear networked systems (NCSs) considering external disturbance and random package dropouts. The sensor samples system states periodically. sampled data packages may have dropouts while being transmitted through communication networks. Notice that number consecutive lost is usually lower upper bound. Then, an aperiodically model employed to describe such a system. By utilizing augmented state approach, transformed into stabilization for...

10.1109/tfuzz.2024.3377799 article EN IEEE Transactions on Fuzzy Systems 2024-03-19

This note is concerned with the stability analysis of linear discrete-time system a time-varying delay. A generalized free-weighting-matrix (GFWM) approach proposed to estimate summation terms in forward difference Lyapunov functional, and theoretical study shows that GFWM encompasses several frequently used estimation approaches as special cases. Moreover, an augmented functional delay-product type term constructed take into account delay changing information. As result, approach, together...

10.1109/tac.2015.2503047 article EN IEEE Transactions on Automatic Control 2015-11-24

This paper is concerned with the problem of stability neural networks time-varying delays. A novel Lyapunov-Krasovskii functional decomposing delays in all integral terms proposed. By exploiting possible information and considering independent upper bounds delay derivative various intervals, some new generalized delay-dependent criteria are established, which different from existing ones improve upon previous results. Numerical examples finally given to demonstrate effectiveness merits...

10.1109/tnn.2011.2111383 article EN IEEE Transactions on Neural Networks 2011-03-17

This article deals with the problem of stability and stabilization Takagi–Sugeno (T–S) fuzzy systems time-varying delay. First, a novel Lyapunov–Krasovskii functional is constructed, which dependent on membership functions takes more information delay into account. Next, based an <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$N$</tex-math></inline-formula> -order free-matrix-based integral inequality...

10.1109/tfuzz.2022.3204899 article EN IEEE Transactions on Fuzzy Systems 2022-09-07

This article investigates the problem of delay-dependent stability for one-area load frequency control (LFC) system with electric vehicles (EVs). Two closed-loop models LFC EVs are proposed, including model based on reconstructed technique and uncertain parameters that considers state charge. By employing Lyapunov-Krasovskii functional method, two criteria presented systems under study such a more accurate admissible delay upper bound (ADUB) can be obtained. Case studies finally carried out...

10.1109/tcyb.2022.3140463 article EN IEEE Transactions on Cybernetics 2022-01-25

This paper focuses on addressing the issue of absolute stability for uncertain Lur’e systems with time-varying delay using a delay-segmentation approach. The approach involves decomposing interval into two distinct subintervals unequal lengths. allows introduction delay-segmentation-based augmented Lyapunov–Krasovskii functional that ensures piecewise continuity at partition points. By selecting sets Lyapunov matrices in each interval, obtained results are less conservative, providing more...

10.3390/math12040583 article EN cc-by Mathematics 2024-02-15
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