基于WRBF神经网络的万向四旋翼的适应分数顺序非单元终端滑动模式控制
PloS one
|December 26, 2025
概括
本研究介绍了使用统一的分数顺序非单元终端滑动模式控制器 (FONTSMC) 和自适应波形半径基函数 (WRBF) 网络的倾斜旋转机四旋转机的强有力的控制策略. 这种新的方法提高了无人驾驶飞行器 (UAV) 操作的轨迹跟踪精度和干扰下的稳定性.
科学领域:
- 机器人和控制系统 机器人和控制系统
- 航空航天工程 航空航天工程
- 人工智能的人工智能
背景情况:
- 倾斜旋转机四旋转机在轨迹跟踪方面面临挑战,原因是不确定性和干扰.
- 现有的控制策略往往缺乏稳定性和精确处理复杂的动态.
研究的目的:
- 开发一种新的,强大的六度自由度 (6-DOF) 轨迹跟踪控制策略,用于倾斜转子四旋翼机.
- 在非结构化的不确定性和外部干扰下提高控制性能.
主要方法:
- 一个分数顺序非单元终端滑动模式控制器 (FONTSMC) 与一个自适应波形辐射基函数 (WRBF) 神经网络的共同设计.
- 整合了墨西哥帽波段激活功能,以提高近似度和噪声稳定性.
- 实现一个并行控制结构与摩尔-罗斯伪反向的执行器分配.
主要成果:
- 该WRBF网络准确地估计和补偿不确定性,确保快速的有限时间融合,没有奇点.
- 墨西哥帽子波段比高斯的RBF网络提高了学习速度和噪声稳定性.
- 与传统方法相比,模拟证实了优越的跟踪精度,融合速度和更顺的响应.
结论:
- 拟议的统一FONTSMC和WRBF框架为6DOF轨迹跟踪在倾斜转子四旋翼机提供了强大的和高效的解决方案.
- 控制器在处理不确定性和干扰方面具有显著的优势,这对于复杂的无人机应用至关重要.
- 该研究验证了用于先进机器人飞行控制的集成控制架构的有效性.
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