对于具有半马科维亚跳转参数的多代理系统,基于ADP的容错控制
IEEE transactions on cybernetics
|July 11, 2024
概括
这项研究集成了适应性动态编程 (ADP) 和适应性故障耐受性控制 (FTC) 对于具有执行器故障的半马科维亚多剂系统. 这种方法确保了系统的稳定性和共识,即使存在环境变化和故障.
科学领域:
- 控制系统工程 控制系统工程
- 人工智能的人工智能
- 随机过程 随机过程
背景情况:
- 多代理系统 (MAS) 由于环境变化和组件故障,在达成共识方面面临挑战.
- 半马科夫过程为模拟具有时间变化的参数和复杂状态过渡的系统提供了灵活的框架.
- 执行器偏差故障会降低系统性能,并阻碍在MAS中达成共识.
研究的目的:
- 为半马科维斯跳跃多代理系统开发一个集成的自适应动态编程 (ADP) 和自适应容错控制 (FTC) 战略.
- 解决在执行器偏差故障和环境不确定性存在时的共识控制问题.
- 通过数据驱动方法克服对精确系统动态知识的需求.
主要方法:
- 将自适应动态编程 (ADP) 与演员关键神经网络结构集成,以在线学习系统动态.
- 实施数据驱动的自适应性故障耐受性控制 (FTC) 方案,用于实时补偿执行器偏差故障.
- 使用半马科夫过程来建模系统的环境参数变化和随机行为.
主要成果:
- 控制系统信号的统一边界性,以确保稳定性.
- 达成共识,追随者代理人的状态成功跟踪领导者的状态.
- 通过模拟结果验证了拟议的控制战略的有效性.
结论:
- 集成的ADP和FTC方法有效地解决了具有执行器偏差故障的半马科维斯跳跃多代理系统的共识控制问题.
- 联邦贸易委员会计划的数据驱动性允许在没有事先系统识别的情况下进行在线故障补偿.
- 该研究证实了在复杂,不确定的环境中提出的方法的稳定性和有效性.
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