稳定T-S模糊异步布尔控制网络在噪声下的时间延迟
Feifei Yang1, Yujie Sun2,3, Chuan Zhang4
1College of Computer Science, Taiyuan University of Technology, Jinzhong, 030600, China.
Scientific reports
|April 29, 2025
概括
这项研究涉及使用非周期性采样数据状态反的Takagi-Sugeno模糊异步布尔控制网络的稳定. 它为具有固定的和不固定的时间延迟的系统开发了条件,并通过示例证明了有效性.
科学领域:
- 控制理论 控制理论
- 网络化系统 网络化系统
- 模糊逻辑系统 模糊逻辑系统
背景情况:
- 塔卡吉-苏杰诺 (T-S) 模糊系统被广泛用于模拟非线性系统.
- 异步布尔控制网络 (ABCN) 由于异步更新,在控制设计中存在挑战.
- 采样数据控制引入时间延迟,使稳定性分析复杂化.
研究的目的:
- 在非周期性采样数据状态反控制下研究TS模糊ABCN的稳定问题.
- 开发足够和必要的条件来稳定这些复杂的系统.
- 将分析扩展到具有固定和非固定时间延迟的系统,包括噪音.
主要方法:
- 转换的TS模糊的ABCN到一个离散的时间延迟系统使用半张力积的理论.
- 对增强的ABCN的代数形式的导出.
- 使用各种分析方法开发稳定性条件.
- 在时间延迟分析中包括噪声.
主要成果:
- 为了稳定具有固定的时间延迟的TS模糊ABCN,我们得出了足够和必要的条件.
- 条件扩展,以解决有不确定的时间延迟和噪声的系统.
- 通过说明性示例验证了拟议方法的有效性.
结论:
- 拟议的控制策略有效地稳定了在非周期性采样数据条件下的TS模糊ABCN.
- 开发的条件为分析具有时间延迟和噪声的系统提供了强大的框架.
- 该方法与ABCN稳定现有技术相比,提供了一种优越的方法.
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