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Design of robust backstepping controller for unmanned aerial vehicle using analytical redundancy and extended state observer

机译:基于分析冗余和扩展状态观测器的无人机稳健反推控制器设计

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In current flight control system (FCS) practice for unmanned aerial vehicles(UAVs), flight safety becomes more and more important in extreme weather or in the face of sensor and control effector failures. Flight safety is guaranteed traditionally by specifying functionally redundant control hardware. Compared with extra burden increased by hardware redundancy on UAV, design of analytical redundancy becomes attractive in recent years. This paper proposes a new hybrid design scheme of analytical redundance FCS, which is composed of analytical redundance, core flight control algorithm and uncertainties compensator. Analytical redundancy for attitude angle rates adopts reduced order nonlinear state observer method. The core backstepping flight controller realizes linearization and decoupling of the highly nonlinear and tightly coupled UAV model. For cancelling out uncertainties such as unmodeled dynamics and external disturbances, an extended state observer(ESO) compensator is designed to enhance the robustness of FCS. Pseudoinverse method is applied to establish the mapping between moments and multiple control surfaces. Numerical simulation shows that UAV equipped with the hybrid control scheme has good maneuverability, strong self-learning ability of compensating the unmodeled dynamics and enough robust stability against constraints of actuators.
机译:在当前用于无人机(UAV)的飞行控制系统(FCS)实践中,在极端天气或面对传感器和控制执行器故障的情况下,飞行安全变得越来越重要。传统上,通过指定功能上冗余的控制硬件可确保飞行安全。与无人机上的硬件冗余所增加的额外负担相比,分析冗余的设计近年来变得有吸引力。提出了一种新的解析冗余FCS混合设计方案,该方案由解析冗余,核心飞行控制算法和不确定性补偿器组成。姿态角速率的分析冗余采用降阶非线性状态观测器方法。核心反推飞行控制器实现了高度非线性和紧密耦合的无人机模型的线性化和去耦。为了消除不确定性,例如未建模的动力学和外部干扰,设计了扩展状态观察器(ESO)补偿器以增强FCS的鲁棒性。伪逆方法用于建立力矩与多个控制面之间的映射。数值模拟表明,装备有混合控制方案的无人机具有良好的机动性,较强的自学习能力,可以补偿未建模的动力学特性,并具有足够的鲁棒稳定性,可以抵抗执行器的约束。

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