使用混合LQR和超扭转滑动模式的超扭动耐扰四旋翼控制方法
Serkan Budak1, Cemil Sungur2, Akif Durdu3
1Electrical and Electronics Engineering, Konya Technical University, Konya, Turkey. sbudak@ktun.edu.tr.
Scientific reports
|February 18, 2026
概括
一个新的混合控制系统结合了线性四边形调节器 (LQR) 和超扭曲滑动模式控制 (STSMC),为四旋翼无人机 (UAV) 提供了卓越的姿态稳定. 这种强大的LQR-STSMC方法在具有挑战性的飞行条件下提高了故障耐受性和精度.
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
- 控制理论 控制理论
背景情况:
- 低调的四旋翼无人机 (UAV) 由于其复杂的动态和对外部干扰的敏感性,在姿态稳定方面存在重大挑战.
- 现有的控制策略,如线性二次调节器 (LQR) 和模型预测控制 (MPC),通常在不确定性和系统故障下与稳定性和性能退化作斗争.
研究的目的:
- 开发和验证一个强大的级联式混合控制架构,用于低功率四旋翼无人机的态度稳定.
- 为了提高四旋翼控制系统在不确定和安全关键环境中的故障耐受性和精度.
主要方法:
- 提出了一种混合控制架构,集成线性方位调节器 (LQR) 进行内环稳定和超扭曲滑动模式控制 (STSMC) 进行外环参考修改.
- 超扭曲滑动模式控制 (STSMC) 参数使用大爆炸-大崩 (BB-BC) 算法进行了全球优化,以最大限度地提高稳定性.
- 拟议的LQR-STSMC策略在各种干扰场景下,在Quanser 3-DOF Hover系统模型上与经典的LQR和模型预测控制 (MPC) 相比进行了评估.
主要成果:
- 拟议的LQR-STSMC控制器与LQR和MPC相比表现出更高的性能,实现了明显较低的错误指标 (ISE,IAE,ITAE).
- 混合控制方案表现出增强的故障耐受性,有效地管理风,不同推力系数,有效载荷释放和电机故障等干扰.
- 虚拟3D空间分析证实了旋转器尖端的位置稳定性,验证了控制策略的有效性.
结论:
- 级联的LQR-STSMC混合控制架构提供了一个高度可靠和坚固的解决方案,用于在未经调节的四旋翼无人机中稳定姿势.
- 这种方法提供了卓越的容错性,更快的稳定性和精确的跟踪能力,使其适用于安全关键的飞行操作.
- 优化的混合控制策略在处理模型不确定性和系统故障方面明显优于传统的LQR和MPC.
关键词:
大爆炸大崩优化大爆炸大崩.外部干扰 外部干扰有故障耐受性的控制器.混合动力控制控制器线性二次调节器 线性二次调节器模型预测控制模型预测控制参数不确定性 参数不确定性实用载荷的变化变化超扭转的滑动模式控制器更多相关视频
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