基于观察者的事件触发的递归最佳跟踪控制,用于一类严格反非线性系统.
1School of Information Engineering, Xuzhou University of Technology, Lishui Road 2, Xuzhou, China.
ISA transactions
|November 22, 2023
概括
本研究介绍了一种事件触发的最佳跟踪控制算法,用于具有未知动态和输入和的非线性系统. 这种创新方法提高了系统可靠性,并通过使用基于神经网络的状态观察器和混合触发控制器来减少数据传输.
科学领域:
- 控制系统工程 控制系统工程
- 非线性动力学是一种非线性动力学.
- 人工智能的人工智能
背景情况:
- 具有未知动态的严格反非线性系统带来了重大的控制挑战.
- 输入和和减少传感器配置的需要需要先进的控制策略.
- 现有的观察员-控制器框架往往缺乏直接合,影响性能.
研究的目的:
- 为输入和非线性系统提出一个创新的事件触发的最佳跟踪控制算法.
- 开发基于神经网络的自适应状态观察器,用于状态重建,减少传感器要求.
- 设计一个混合触发控制器,尽量减少成本功能,同时减少数据传输.
主要方法:
- 基于神经网络 (NN) 的自适应状态观察器被开发用于状态估计.
- 一个混合触发的前控制器将跟踪问题转化为监管问题.
- 设计了一个由事件触发的最佳控制器,加上使用多个错误的以同步为导向的触发规则.
- 利亚普诺夫理论被用来保证收性质.
主要成果:
- 拟议的控制方案有效地将预定义的成本函数最小化.
- 通过事件触发机制实现了数据传输的显著减少.
- 控制策略确保精确的状态估计和跟踪控制,即使输入和.
- 结合的观察者控制器设计显示了比单独的框架更好的性能.
结论:
- 开发的事件触发最佳跟踪控制算法对具有未知动态和输入和度的非线性系统有效.
- 基于神经网络的观察员和混合触发控制器的集成提高了系统的可靠性和效率.
- 拟议的方法为控制设计提供了一种新的方法,确保精确的状态估计和跟踪控制,减少数据交换.
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