一个冲动的方法,以国家估计为多级单一扰乱复杂网络在比特率限制下的比特率
IEEE transactions on cybernetics
|March 3, 2025
概括
本研究介绍了一种冲动估计方法,用于具有比特速率约束的复杂网络. 它确保有边界的估计错误,优化比特速率分配,以提高网络系统的性能.
科学领域:
- 控制系统工程 控制系统工程
- 网络化系统 网络化系统
- 信号处理 信号处理
背景情况:
- 调查离散时间多速单一扰乱复杂网络的状态估计.
- 解决了无线通信中比特率限制所带来的挑战,用于远程估计.
- 强调需要使用高效的估计方法,进行定期,受限制的测量.
研究的目的:
- 开发一种冲动估计方法,用于最终的边界状态估计.
- 建立条件,确保估计错误动态的指数边界性.
- 为比特速率分配和估计器增益设计引入一个优化算法.
主要方法:
- 使用冲动估计方法进行定期测量校正.
- 在冲动机制下使用代分析来导出稳定性条件.
- 开发了一个资源分配和控制器设计的优化算法.
主要成果:
- 为估计错误的指数边界性建立了足够的条件.
- 展示了估计性能和比特速率分配之间的相关性.
- 通过模拟示例验证拟议的方法.
结论:
- 冲动估计方法有效地处理复杂网络中的比特速率约束.
- 开发的优化算法促进了高效的资源管理,以改善估计.
- 这些发现为在受约束的网络系统中进行状态估计提供了强大的框架.
相关概念视频
State Space Representation
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The frequency-domain technique, commonly used in analyzing and designing feedback control systems, is effective for linear, time-invariant systems. However, it falls short when dealing with nonlinear, time-varying, and multiple-input multiple-output systems. The time-domain or state-space approach addresses these limitations by utilizing state variables to construct simultaneous, first-order differential equations, known as state equations, for an nth-order system.
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Consider an RLC circuit, a...
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Nonlinear systems often require sophisticated approaches for accurate modeling and analysis, with state-space representation being particularly effective. This method is especially useful for systems where variables and parameters vary with time or operating conditions, such as in a simple pendulum or a translational mechanical system with nonlinear springs.
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In signal processing, a continuous-time signal can be sampled using an impulse-train sampling technique, followed by the zero-order hold method. Impulse-train sampling involves the use of a periodic impulse train, which consists of a series of delta functions spaced at regular intervals determined by the sampling period. When a continuous-time signal is multiplied by this impulse train, it generates impulses with amplitudes corresponding to the signal's values at the sampling points.
In the...
In the...
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The transformation process begins with the state-space representation, characterized by the state equation and the output equation. These equations are typically represented as:
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