基于自适应网络和强化学习的离散时间强大的事件触发式执行器容错控制
1Department of Robotic and Advanced Manufacturing, CINVESTAV-IPN., Mexico.
概括
本研究介绍了一种针对面临非线性不确定性和执行器故障的离散时间系统的新型耐故障控制系统. 适应控制器确保了强大的性能和减少数据传输,经过实验验证.
科学领域:
- 控制系统工程 控制系统工程
- 非线性系统分析 非线性系统分析
- 故障诊断和耐受性问题
背景情况:
- 离散时间系统易受非线性不确定性和执行器故障的影响,影响性能.
- 现有的耐故障控制方法可能无法充分解决复杂的故障类型或优化数据传输.
研究的目的:
- 为具有非线性不确定性和执行器故障的离散时间系统开发适应性耐故障控制方案.
- 通过事件触发机制来增强系统的稳定性并最大限度地减少数据传输.
- 通过理论分析和实验结果验证拟议的控制器的有效性.
主要方法:
- 基于非线性电子电路的自适应控制器的设计,用于管理执行器故障 (偏移偏移,灵敏度变化,死区).
- 实施事件触发的滑动表面机制,以提高稳定性和减少数据交换.
- 利用适应性网络 (MiFRENs) 进行训练,并通过强化学习进行适应性控制.
- 理论分析以保证信号的界限性和跟踪错误的趋同.
主要成果:
- 拟议的自适应控制器有效地处理各种执行器故障和非线性不确定性.
- 事件触发机制显著减少数据传输,同时保持系统性能.
- 实验验证证证实了控制器的稳定性,数据负载减少,与现有方法相比,性能优越.
结论:
- 开发的耐故障控制方案为具有复杂不确定性和故障的离散时间系统提供了强大的和高效的解决方案.
- 适应性网络和事件触发控制的集成为先进的控制系统设计提供了一个有希望的方向.
- 这些发现显示出实际可用性和与传统方法相比的显著优势.
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