一个新的固定时间稳定定理及其在BAM神经网络稳定性分析中的应用
Chuan Chen1,2, Lixiang Li3, Ling Mi4
1Key Laboratory of Computing Power Network and Information Security, Ministry of Education, Shandong Computer Science Center, Qilu University of Technology (Shandong Academy of Sciences), Jinan 250353, China.
Chaos (Woodbury, N.Y.)
|August 7, 2023
概括
一个新的固定时间 (FXT) 稳定性定理为稳定性分析提供了一个更简单的条件. 该定理应用于双向关联记忆神经网络 (BAMNNs),以确保在干扰下FXT的稳定性.
科学领域:
- 控制系统工程 控制系统工程
- 计算神经科学是一种神经科学.
- 非线性动力学是一种非线性动力学.
背景情况:
- 双向关联记忆神经网络 (BAMNNs) 对于关联记忆任务至关重要.
- 确保BAMNN的固定时间 (FXT) 稳定性,尤其是在干扰的情况下,仍然是一个挑战.
- 现有的稳定性分析方法可能是复杂的和依赖参数的.
研究的目的:
- 引入一个新的固定时间 (FXT) 稳定性定理,并简化判断条件.
- 使用滑动模式控制来研究扰乱的BAMNN的FXT稳定性.
- 为稳定性开始时间推导出易于计算的上限.
主要方法:
- 基于一个独特的判断条件,开发一个新的FXT稳定性定理.
- 设计新的滑动模式状态变量,以适应FXT稳定性定理.
- 实现双层滑动模式控制器,以管理BAMNN中的边界扰动.
主要成果:
- 新的FXT稳定性定理提供了稳定性时间限制和系统参数之间的直接关系.
- 拟议的滑动模式控制策略确保了扰乱的BAMNN的FXT稳定性.
- 通过模拟,已经得出了足够的条件来实现FXT稳定性,并通过模拟进行了验证.
结论:
- 开发的FXT稳定性定理简化了固定时间稳定性的分析.
- 拟议的控制方案有效地保证了BAMNN具有边界扰动的FXT稳定性.
- 该研究提供了一种实际方法,用于计算控制系统中的稳定性时间限制.
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