混合哈里斯·霍克斯优化与战略粒子群集优化,以稳定和干扰拒绝在绑定的无人机系统中
Alialhadi Khaleel Ismael1, Sefer Kurnaz1, Noorulden Basil2
1Department of Computer Engineering, Altinbas University, Istanbul, Türkiye.
Scientific reports
|November 13, 2025
概括
一种新的混合优化方法增强了绑定的无人机态度控制. 与传统方法相比,先进的分数顺序比例导数导数整数 (FOPDD-I) 控制器显示出优越的稳定性和干扰排斥.
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
- 优化算法 优化算法
背景情况:
- 连接无人机 (UAV) 需要先进的姿态控制,以保持稳定性和性能.
- 像PID和ADRC这样的传统控制器在动态和不确定的环境中存在局限性.
- 优化控制器参数对于实现所需的性能指标至关重要.
研究的目的:
- 提出一种新的混合优化方法,用于为绑定的无人机设计先进的姿态控制器.
- 开发一个使用混合算法优化的分数顺序比例导数导数整数 (FOPDD-I) 控制器.
- 评估拟议控制器的性能与传统和先进的控制策略相比.
主要方法:
- 开发一个分数顺序比例导数导数整数 (FOPDD-I) 控制器.
- 使用混合哈里斯·霍克斯优化-战略-粒子群优化 (HHHOESPSO) 算法优化FOPDD-I控制器.
- 通过MATLAB模拟对比传统的PID,级PID,经典的ADRC和先进的ADRC控制器进行比较分析.
主要成果:
- 经过HHHOESPSO优化的FOPDD-I控制器表现出卓越的稳定性,对干扰的反应更快,并增强了干扰排斥能力.
- 显著的参数调整包括Kp增加了56.5%,Ki增加了65.2%,Kd减少了98.4%.
- 分数顺序参数在非线性动态环境中调整为12.5%和14.7%的适应性改进.
- 拟议的控制器在稳定性和响应性方面表现优于传统的PID,Cascade PID和ADRC方法.
结论:
- 分数顺序控制和混合优化策略的组合为绑定的无人机态度控制提供了强大的解决方案.
- 拟议的FOPDD-I控制器在动态和不确定的条件下在稳定性,响应性和干扰拒绝方面提供了显著的优势.
- 该方法为绑定的无人机应用程序中先进的态度控制建立了新的基准.
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