定期事件触发模型预测控制网络非线性不确定系统与干扰
IEEE transactions on cybernetics
|October 11, 2024
概括
本研究介绍了网络非线性系统的周期性事件触发模型预测控制 (PETMPC). 它通过仅在必要时触发控制更新来减少计算和数据传输,确保系统稳定性.
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:
- 网络非线性不确定系统面临的挑战是随时间变化的干扰.
- 传统模型预测控制 (MPC) 可能是计算密集型和通信繁重的.
- 事件触发控制策略旨在优化控制系统中的资源使用.
研究的目的:
- 为网络非线性不确定系统开发周期事件触发模型预测控制 (PETMPC).
- 与传统的MPC相比,减少计算负载和信号传输频率.
- 确保闭环系统的全局局限稳定性.
主要方法:
- 一个通用比例整体观察器 (GPIO) 旨在从采样数据中估计系统状态和干扰.
- 干扰预测是使用前向欧勒法生成的.
- 计算和存储一个最佳的控制序列,在事件间隔执行,减少计算和传输.
主要成果:
- 拟议的PETMPC方法有效地减少了控制序列计算和信号传输的数量.
- 稳定性分析证实,闭环混合控制系统在PETMPC法下是全球局限稳定的.
- 数字模拟证明了PETMPC方法的可行性和卓越性能.
结论:
- 对于联网的非线性不确定系统,PETMPC方法提供了一个有效的控制策略.
- 事件触发机制显著优化了资源利用,而不影响系统稳定性.
- 该方法为具有通信和计算限制的应用程序提供了传统MPC的可行替代方案.
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