基于HOD的无模型四旋翼RBF滑模控制
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中国民航大学

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TP273

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Model Free RBF Sliding Mode Control based on HOD Designed for Quadrotor
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CAUC

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    摘要:

    在无模型控制算法中, 关键的问题在于如何对系统的未知模型和扰动进行准确估计. 为了探索解决这一问题, 本文提出了一种基于高阶微分器(HOD)的无模型RBF神经网络滑模控制器(HODRBFSMC), 首先引入HOD估计系统模型的各阶状态变量, 并将系统模型的未知项和外界干扰统一归为总扰动, 通过RBF 神经网络对总扰动进行估计, 并根据Lyapunov定理证明了所设计控制器的闭环稳定性.为验证控制器的有效性, 所设计的控制器被应用于四旋翼飞行器的轨迹控制, 解决其模型参数复杂并且飞行过程中易受外界干扰的问题. 仿真实验表明, 本文所提出的方法能够有效估计并补偿总扰动, 其轨迹跟踪能力和抗干扰性能相比于PID和高阶微分反馈控制(HODFC)具有一定优越性, 能够很好满足四旋翼飞行器控制的需求

    Abstract:

    In model free control, the key is how to accurately estimate the unknown model and disturbance of the system. In order to explore and solve this problem, this paper proposes a model-free RBF neural network sliding mode controller(HODRMFSMC) based on high-order-differentiator (HOD). Firstly, HOD is introduced to estimate the state variables of each order of the system model. The unknown items of the system model and external disturbances are unified as total disturbances,and the total disturbances are estimated by RBF neural network. According to the Lyapunov theorem, the closed-loop stability of the designed controller is proved. In order to verify the effectiveness of the controller, the designed controller is applied to the trajectory control of the quadrotor to solve the problem of complex model parameters and susceptibility to external interference during flight. The Simulation experiments show that the method proposed in this paper can effectively estimate and compensate the total disturbances, and its trajectory tracking ability and anti-disturbance performance are superior to PID and HODFC, and can well meet the needs of quadrotor control.

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  • 收稿日期:2021-09-24
  • 最后修改日期:2022-01-04
  • 录用日期:2022-01-04
  • 在线发布日期: 2022-02-01
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