延迟竞争-合作惯性神经网络的双重同步:一个信号补偿加上事件触发的控制器
Ruixue Fu1, Yu Xue2, Xian Zhang2
1School of Mathematical Science, Heilongjiang University, Harbin, 150080, PR China.
概括
本研究介绍了一种新的复合控制策略,用于具有时间变化的延迟的竞争合作惯性神经网络 (CCINNs). 该方法有效地实现双边同步,降低通信成本.
科学领域:
- 控制理论 控制理论
- 计算神经科学是一种神经科学.
- 网络科学 网络科学
背景情况:
- 竞争合作惯性神经网络 (CCINNs) 由于非奇偶激活函数,惯性条款和时间变化的延迟而呈现复杂的动态.
- 传统的事件触发控制方法与这些联合挑战作斗争,限制了同步.
- 双重同步对于理解复杂的网络行为至关重要.
研究的目的:
- 调查CCINNs的双边同步与时间变化的延迟.
- 开发一种新的复合材料控制策略,克服现有方法的局限性.
- 为了减少通信开销,同时确保同步.
主要方法:
- 将CCINN系统转换为可管理的坐标框架,使用签名图的结构平衡条件.
- 一个复合控制策略,集成一个信号补偿控制器 (SCC) 和一个事件触发控制器 (ETC).
- 理论分析的参数化系统解决方案,避免复杂的Lyapunov功能方法.
主要成果:
- 拟议的复合控制策略有效地解决了非奇数激活函数,惯性动态和时间变化的延迟.
- 与连续控制相比,集成的SCC和ETC显著降低了通信开销.
- 建立了错误系统的指数趋同标准,证明了理论上的稳定性.
- 一个数值示例证实了拟议的同步方案的实际有效性.
结论:
- 开发的复合控制策略为复杂的CCINN中双方同步提供了有效的解决方案.
- 这种方法通过事件触发机制来最大限度地降低通信成本,从而提高效率.
- 这些发现有助于推进复杂动态系统的控制理论.
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