基于交换模糊竞争性网络系统的基于收自适应控制的规定的时间同步,具有时间变化的延迟
Dongdong Gao1, Fanchao Kong2, Tingwen Huang3
1College of Mathematics and Computer Science, Tongling University, Tongling, Anhui 244000, China; Anhui Engineering Research Center of Intelligent Manufacturing of Copper-based Materials, Tongling University, Tongling, 244000, China.
概括
本研究引入了复杂神经网络的新控制方法,具有延迟和切换,确保在设定的时间内保持稳定. 这些适应性策略比以前的方法更快地稳定系统.
科学领域:
- 控制理论 控制理论
- 人工智能的人工智能
- 动态系统 动态系统
背景情况:
- 不连续的模糊中性类型竞争神经网络 (FNTCNNs) 是一般化的单一扰乱的菲利普洛夫系统.
- 对于具有时间变化的延迟和干扰的系统来说,规定的时间稳定性是一个重大挑战.
- 对于复杂的,不连续的系统,现有的控制方法缺乏效率.
研究的目的:
- 为奇异扰乱的菲利普洛夫系统开发一种新的规定的时间稳定定定理.
- 为FNTCNN设计适应性规定的时间控制策略,具有切换和时间变化的延迟.
- 确保在定义的时间内稳定系统状态和控制策略.
主要方法:
- 使用调整函数,比较原理和不平等技术开发新的稳定性定理.
- 应用单一规范和新的稳定性定义,用于异常扰乱的系统.
- 利用差异性纳入理论和菲利普洛夫的适应性控制设计框架.
主要成果:
- 对于异常扰乱的菲利普洛夫系统,建立了一个新的规定的时间稳定定定理.
- 为FNTCNN设计了适应性规定时间控制策略,实现了稳定.
- 在规定的时间内将控制策略和系统状态的趋同证明为零.
结论:
- 建议的控制策略有效地实现了FNTCNN的规定的时间稳定.
- 新的稳定性定理为分析复杂的动态系统提供了基础.
- 数字模拟证实了开发方法在多剂系统上的有效性.
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