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Sampled-Data Control for Exponential Synchronization of Delayed Inertial Neural Networks With Aperiodic Sampling and
IEEE Transactions on Neural Networks and Learning Systems
|September 22, 2022
Summary
This study achieves exponential synchronization for inertial neural networks (INNs) using a novel quantized sampled-data controller. The method accounts for heterogeneous time-varying delays and aperiodic sampling, offering less conservative synchronization conditions.
Area of Science:
- Control Theory
- Computational Neuroscience
- Applied Mathematics
Background:
- Inertial Neural Networks (INNs) are crucial for modeling complex dynamical systems.
- Heterogeneous time-varying delays (HTVDs) and aperiodic sampling introduce significant challenges in network synchronization.
- State quantization further complicates the analysis and control design for INNs.
Purpose of the Study:
- To develop a novel quantized sampled-data (QSD) controller for achieving exponential synchronization in INNs.
- To address the complexities introduced by HTVDs, aperiodic sampling, and state quantization.
- To derive less conservative synchronization conditions with enhanced flexibility.
Main Methods:
- Design of a novel QSD controller with time-varying control gain.
- Proposal of a refined Lyapunov-Krasovskii functional (LKF) incorporating HTVD bounds.
- Utilization of an improved looped-functional method to handle practical sampling patterns.
Main Results:
- Novel exponential synchronization conditions for INNs under aperiodic sampling and state quantization are derived.
- The proposed method effectively handles HTVDs by utilizing their lower and upper bounds.
- Less conservative and more flexible synchronization criteria are achieved compared to existing methods.
Conclusions:
- The developed QSD controller and LKF-based method provide an effective approach for exponential synchronization of INNs.
- The findings offer significant advancements in the control of complex neural network systems with practical constraints.
- Numerical simulations validate the effectiveness and advantages of the proposed synchronization strategy.
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