在4D卡普托分数模型中,通过超混沌动态导航气候复杂性及其控制
Manisha Krishna Naik1, Chandrali Baishya1, R N Premakumari1
1Department of Studies and Research in Mathematics, Tumkur University, Tumkur, Karnataka, 572103, India.
Scientific reports
|August 3, 2024
概括
这项研究使用4D微分方程将海水,冰和温度动态与气候变化联系起来. 先进的控制器管理系统混乱,确认稳定性和突出海冰.
科学领域:
- 气候动力学 气候动力学
- 混沌理论 混沌理论
- 分数微积分的计算.
背景情况:
- 人为全球变暖带来了重大的气候挑战.
- 了解海水,海冰和温度的相互作用对于气候建模至关重要.
研究的目的:
- 分析海水,海冰,海温和表面温度之间的联系,使用4D超混乱的卡普托分数微分方程.
- 研究这些因素对气候变化和全球变暖的影响.
- 开发和评估滑动模式控制器,以管理分数系统中的混乱.
主要方法:
- 利用4D超混乱的卡普托分数微分方程来建模气候动态.
- 采用利亚普诺夫指数和庞卡尔部分来证明混乱的运动.
- 在数值模拟中应用了预测器-校正器方法.
- 设计并实施了两个滑动模式控制器,以管理系统混乱并确保全球稳定性.
主要成果:
- 建立了海洋参数和表面温度之间的深厚联系,影响了气候.
- 证实了在不确定性下控制的4D分数系统的全球稳定性.
- 证明了滑动模式控制器在管理混乱和识别关键控制变量的有效性.
- 通过对比模拟和观测数据的相关性图表验证了模型的可信性.
结论:
- 4D超混沌分数模型准确地代表了由海洋参数影响的气候动态.
- 滑动模式控制器可以有效地稳定混乱的气候系统.
- 海冰反射在维持气候稳定方面发挥着至关重要的作用.
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