六度自由度四旋翼稳定使用自适应波诺博帕雷托多目标FLC与处理器在循环验证验证
Aissa Benhammou1, Mohamed Amine Hartani2,3, Fatma A Hashim4,5
1Smart Grids & Renewable Energies Laboratory SGRE-L, Tahri Mohamed University, Bechar, Algeria. Benhammou.aissa@univ-bechar.dz.
Scientific reports
|November 17, 2025
概括
本研究提出了一种新的四旋翼模糊逻辑控制策略,使用独特的进化算法进行了优化. 这种方法显著提高了无人驾驶飞行器的飞行控制精度和响应能力.
科学领域:
- 机器人和控制系统 机器人和控制系统
- 在工程领域的人工智能.
- 航空航天工程 航空航天工程
背景情况:
- 四旋翼控制系统面临着非线性动态和外部干扰的挑战.
- 现有的控制策略往往难以有效地平衡跟踪精度和控制努力.
- 同时优化多个控制器参数对于强大的四旋翼飞机性能至关重要.
研究的目的:
- 为四旋翼飞机开发一个全面和模块化的模糊逻辑控制策略.
- 引入一种新的多目标优化技术来调整控制器收益.
- 为了提高四旋翼飞机在跟踪准确性,控制力度和稳健性方面的性能.
主要方法:
- 实现了六个解的模糊逻辑控制器,用于单个自由度 (滚动,俯冲,偏移,高度,x,y).
- 使用一种新的多目标自适应Bonobo优化器来调整18个控制器收益.
- 应用帕雷托前线原理,同时优化跟踪精度和控制力度.
- 通过模拟和实时实现在dSPACE处理器在循环平台上的验证.
主要成果:
- 在横向运动中,根平均平方误差 (高达51%) 和平均绝对误差 (高达76%) 显著减少.
- 与基线配置相比,保持了高度稳定性和改善了响应时间.
- 证明了对非线性动态,干扰和模型不确定性的强度.
- 在侵略性轨迹条件下成功实时验证.
结论:
- 拟议的模糊逻辑控制策略,通过自适应Bonobo优化器进行优化,为四旋翼控制提供了卓越的性能.
- 这种方法有效地平衡了跟踪精度和控制力度,提高了整体系统的稳定性.
- 嵌入式部署的概念框架代表了现实世界无人驾驶飞行器应用的实际进步.
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