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Adaptive command filtered backstepping tracking controller design for quadrotor unmanned aerial vehicle

机译:四旋翼无人机的自适应指令滤波反步跟踪控制器设计

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摘要

This paper discusses the design of an adaptive command-filtered backstepping flight control law with uncertain parameters for a quadrotor unmanned aerial vehicle (UAV). The control law is tasked with tracking reference trajectories with a constrained velocity, attitude, and attitude rate. Thruster misalignment is included in the formulation of the quadrotor dynamics. Online parameter update laws are used to compensate for the uncertain parameters, namely mass, inertia, actuator gain, and thruster misalignment. Command filters are used to implement the vehicle's actuator and state constraints. Stability of the control law with parameter update laws during periods of saturation is guaranteed by using a modified tracking error in the Lyapunov function, in which the effect of the saturation is smoothed into the other internal control steps. The controller and its performance are evaluated using a non-linear, six-degree-of-freedom dynamic model of a quadrotor UAV in simulations. The results show that the proposed control law enhances the tracking performance by controlling internal states even with parameter uncertainties and thruster misalignment errors.
机译:本文讨论了具有不确定参数的四旋翼无人机(UAV)的自适应命令滤波反推飞行控制律的设计。控制律的任务是跟踪速度,姿态和姿态速率受限的参考轨迹。推力器未对准包括在四旋翼动力学公式中。在线参数更新定律用于补偿不确定参数,即质量,惯性,执行器增益和推进器未对准。命令过滤器用于实现车辆的执行器和状态约束。通过在Lyapunov函数中使用修正的跟踪误差,可以保证饱和期间的控制定律和参数更新定律的稳定性,其中将饱和的影响平滑到其他内部控制步骤中。在仿真中,使用四旋翼无人机的非线性六自由度动态模型评估了控制器及其性能。结果表明,所提出的控制律即使存在参数不确定性和推进器失准误差,也可以通过控制内部状态来提高跟踪性能。

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