对未知非线性系统的安全最佳FTC的自适应式批评设计,具有不对称的受约束输入输入
Dehua Zhang1, Yuchen Wang1, Lei Meng1
1School of Artificial Intelligence, Henan University, Zhengzhou, 450046, China.
ISA transactions
|September 21, 2024
概括
本研究引入了一种新型安全最佳的故障耐受性控制 (FTC) 方法,用于未知具有执行器故障的非线性系统. 该方法通过使用控制障碍函数和零和游戏框架来确保系统安全和最佳性能.
科学领域:
- 控制工程 控制工程 控制工程
- 非线性系统动态 非线性系统动态
- 机器人技术 机器人技术 机器人技术
背景情况:
- 容错控制 (FTC) 对于提高复杂动态系统的可靠性至关重要.
- 在未知的非线性系统中解决执行器故障和不对称输入约束存在重大挑战.
研究的目的:
- 为未知的非线性系统开发新的安全最佳FTC方法,以执行器故障和不对称的输入约束.
- 为了保证系统在安全范围内运行,同时优化性能.
主要方法:
- 将控制屏障功能 (CBF) 纳入成本函数,以惩罚不安全的行为.
- 制定安全最佳的FTC问题作为差异性的零和游戏 (ZSG).
- 使用基于神经网络的标识符来重建系统动态,并使用自适应的批评方案来处理不对称的约束.
主要成果:
- 拟议的方法确保闭环系统中的所有信号均最终约束 (UUB).
- 通过在单环机器人臂系统上进行模拟验证的有效性,执行器故障.
- 该算法成功地满足了FTC在具有不对称输入约束的故障系统中的安全最佳要求.
结论:
- 开发的安全最佳FTC方法有效地管理未知的非线性系统中的执行器故障和不对称输入约束.
- 该方法为在故障条件下保持系统安全和性能提供了强大的解决方案.
- 这项研究有助于通过先进的控制策略提高复杂动态系统的可靠性.
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