基于网络系统的平均化技术的预测性代学习控制,具有色通道和数据丢失的网络系统.
Zhenxuan Li1, Zhiyang Zhang1, Chenkun Yin2
1Beijing Institute of Petrochemical Technology, Beijing, China.
ISA transactions
|July 27, 2025
概括
本研究介绍了一种基于平均值的一般预测代学习控制 (GA-PILC),用于面临数据丢失和色通道的网络系统. 该方法确保了控制准确度,尽管通信不完美.
科学领域:
- 控制工程 控制工程 控制工程
- 网络化系统 网络化系统
- 信号处理 信号处理
背景情况:
- 网络系统经常遭受数据丢失和色的道,降低控制性能.
- 代学习控制 (ILC) 对于重复的任务是有效的,但对沟通问题敏感.
研究的目的:
- 开发一个强大的预测代学习控制 (PILC) 方法,用于有数据丢失和色通道的网络系统.
- 为了减轻通道损害对控制精度的不利影响.
主要方法:
- 一种一般平均 (GA) 技术集成到预测模型和控制器中.
- 在成功传输数据后,控制输入被选择性地更新.
- 在随机框架中使用复合能量函数方法来分析收.
主要成果:
- 拟议的基于GA的PILC方法有效地消除了数据丢失和色通道的不利影响.
- 理论上已经证明了平均追踪误差的收.
- 该方法的有效性通过模拟来证明.
结论:
- 基于GA的PILC提供了一个强大的解决方案,用于控制具有不可靠通信通道的网络系统.
- 这种方法提高了控制系统的可靠性和在具有挑战性的环境中的性能.
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