高级MIMO非线性多代理系统的神经适应性固定时间故障耐受性封闭控制,以类似的严格反形式
Hui Lv1, Dandan Liu1, Kai Sun1
1School of Information and Automation, Qilu University of Technology (Shandong Academy of Sciences), Jinan 250353, PR China.
概括
本研究介绍了一种神经适应的固定时间制控制方法,用于多代理系统,确保快速可靠的性能,尽管存在干扰和故障. 这种方法保证在一定的时间内制,独立于初始条件.
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
- 机器人技术 机器人技术 机器人技术
背景情况:
- 多代理系统 (MAS) 在干扰和故障下实现协调控制方面面临挑战.
- 固定时间控制提供了比传统方法更快的融合,但需要对复杂系统进行精心设计.
研究的目的:
- 为高阶MIMO非线性多代理系统开发一个固定时间封闭控制协议.
- 为了解决控制设计中的外部干扰和执行器故障.
- 为了确保在可预测的,固定的时间内实现封闭性能.
主要方法:
- 在后退框架内采用神经适应控制策略.
- 该协议是为非定向和定向通信拓设计的.
- 耐故障标准是为了处理执行器故障而推导的.
主要成果:
- 提出了一种新的神经适应固定时间制控制协议.
- 控制方法保证在固定的时间内控制,独立于初始状态.
- 在控制设计中避免了奇点问题.
结论:
- 开发的神经适应性固定时间封闭控制方法对高阶MIMO非线性多代理系统有效.
- 这种方法提供了保证的封闭性能和故障耐受性.
- 该方法的有效性通过数值模拟和实际的多操作器应用得到证实.
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