基于模型校正的生物机器人鱼的后续控制
Yu Wang1, Jian Wang2, Huijie Dong3
1The School of Intelligence Science and Technology, The Institute of Artificial Intelligence, University of Science and Technology Beijing, Beijing 100083, China.
Biomimetics (Basel, Switzerland)
|August 27, 2025
概括
这项研究使用模糊逻辑和动态模型校正引入了对生物机器人鱼的容错控制. 这种方法使得机器人鱼能够在关节故障的情况下保持跟踪控制,从而提高水下操作能力.
科学领域:
- 机器人技术
- 控制系统
- 海洋工程
背景情况:
- 生物机器人鱼由于复杂的动态和关节故障而面临故障耐受性控制的挑战.
- 关节故障会破坏推进,影响航行和任务执行的速度和曲率.
研究的目的:
- 为多关节生物机器人鱼开发一个耐故障的后续控制框架.
- 通过模糊控制和动态模型校正来解决联合故障引起的控制问题.
主要方法:
- 离线故障分析以推导关节故障的影响因子函数.
- 适应期曲折过和改进的视线导航以适应运动.
- 双循环模糊控制策略用于协调速度和曲率控制.
主要成果:
- 拟议的框架有效地实现了对生物机器人鱼的容错性后续控制.
- 通过数值模拟证明了对多种关节故障的强度.
- 影响因子函数准确地描述了对鱼的故障影响.
结论:
- 开发的耐故障控制策略为复杂的水下环境中的生物机器人鱼提供了可行的解决方案.
- 模糊控制方法与动态模型校正相结合, 提高机器人鱼对故障的弹性.
- 这项研究有助于可靠的自主水下操作.
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