混合事件触发的跟踪控制与非线性网络系统的关键学习
IEEE transactions on cybernetics
|January 12, 2026
概括
一个新的混合事件触发 (ET) 控制框架优化了非线性网络控制系统的跟踪. 这种方法通过使用自适应性关键符和减少连续触发来节约网络资源,从而提高了系统稳定性.
科学领域:
- 控制系统工程 控制系统工程
- 网络化系统 网络化系统
- 非线性动力学是一种非线性动力学.
背景情况:
- 网络控制系统 (NCS) 面临带宽和稳定性有限的挑战.
- 优化跟踪对于许多NCS应用程序至关重要.
- 传统的基于事件的控制需要持续评估条件,消耗资源.
研究的目的:
- 为离散时间非线性NCS开发一种新的混合事件触发 (ET) 控制框架.
- 为了解决最佳的跟踪问题,同时节约网络资源.
- 为了确保错误系统的稳定性.
主要方法:
- 通过结合系统状态和参考轨迹,构建了一个增强的工厂.
- 开发了一种混合ET机制,以恒定的间隔来实现事件沉默.
- 使用模型,批评和行动网络实现了在线自适应式批评算法.
主要成果:
- 将最佳跟踪问题转化为最佳调节问题.
- 减轻了有限的网络带宽,并消除了持续触发条件评估.
- 将追踪控制政策实时调整到最佳水平.
结论:
- 拟议的混合ET控制框架有效地解决了在非线性NCS中的最佳跟踪问题.
- 该方法节约了网络资源,并提高了系统的稳定性.
- 适应性批评技术可以实时优化控制策略.
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