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基于分数阶滑模的四旋翼无人机抗风扰控制OA

Fractional-order Sliding-model-based Anti-wind Disturbance Control for Quadrotor UAVs

中文摘要英文摘要

针对四旋翼无人机在轨迹跟踪过程中遇到的风场扰动问题,本文构建风场数学模型并整合于无人机动力学模型中,设计了一种双闭环分数阶滑模控制(Fractional Order Sliding Mode Control,FOSMC)算法.该算法通过在滑模面和趋近律中引入分数阶微分算子,有效提升了系统的控制灵活性和鲁棒性.同时,配套应用非线性扰动观测器进行风扰动自适应补偿,并借助智能优化算法实现控制参数自动整定.仿真结果表明,与传统滑模控制(Sliding Mode Control,SMC)和PID算法相比,本文所提出的算法在风扰动环境下具有更优异的鲁棒性和跟踪性能,验证了所提算法在复杂风场环境中的优越性.

In this study,a dual-closed-loop fractional-order sliding mode control(FOSMC)algorithm is designed to address the wind field disturbances during UAV trajectory tracking.A mathematical model of the wind field is established and integrated it into the UAV dynamics model to characterize external perturbations.The proposed FOSMC introduces fractional-order differential operators into both the sliding mode surface and convergence law,thereby enhancing the control flexibility and robustness of the system.At the same time,the supporting application of nonlinear disturbance observer is used for wind disturbance adaptive compensation,and the control parameters are automatically tuned with the help of intelligent optimization algorithm.The simulation results show that,under wind disturbance conditions,the proposed algorithm exhibit superior robustness and tracking performance compared to conventional sliding mode control(SMC)and PID algorithms,confirming its effectiveness in the complex wind field environment.

王海龙;梁杰;宴聪

广东工业大学 机电工程学院,广东 广州 510006广东工业大学 机电工程学院,广东 广州 510006广东工业大学 机电工程学院,广东 广州 510006

信息技术与安全科学

四旋翼风场扰动轨迹跟踪分数阶滑模控制粒子群优化算法

quadrotorwind field disturbancetrajectory trackingfractional order sliding mode controlparticle swarm optimization algorithm

《广东工业大学学报》 2026 (1)

79-86,8

国家重点研发计划项目(2023YFC3106904)广东工业大学2024年度实验教学与管理改革研究专项项目(20240722)

10.12052/gdutxb.250101

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