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Model-Free Control Approach for Fixed-Wing UAVs with Uncertain Parameters Analysis

机译:不确定参数分析的固定翼无人机的无模型控制方法

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This paper presents first results of an innovative Model-Free Control (MFC) architecture applied to fixed-wing UAVs. MFC is an algorithm dedicated to systems with poor modeling knowledge. Indeed, the costs to derive a reliable and representative aerodynamic model for UAVs motivated the use of such a controller. By exploiting a purely numerical model, this algorithm provides an intuitive method to tune the control loop without any information about the controlled system. We propose to extend the MFC architecture to the case of fixed-wing UAVs and study the MFC properties in terms of uncertain parameters. As a first result, our designed MFC architecture provides a continuous controller able to stabilize the entire flight envelope of two different fixed-wing UAVs. These results show promising adaptive perspectives and demonstrate that MFC presents robust properties for both uncertain parameters and disturbance rejection.
机译:本文介绍了应用于固定翼无人机的创新无模型控制(MFC)架构的初步结果。 MFC是专用于建模知识较差的系统的算法。确实,为无人机获得可靠且具有代表性的空气动力学模型的成本促使这种控制器的使用。通过利用纯数值模型,该算法提供了一种直观的方法来调节控制回路,而无需任何有关受控系统的信息。我们建议将MFC体系结构扩展到固定翼无人机的情况,并根据不确定参数研究MFC属性。首先,我们设计的MFC架构提供了一个连续的控制器,该控制器能够稳定两个不同的固定翼无人机的整个飞行范围。这些结果显示了有前途的适应性观点,并证明了MFC对不确定的参数和干扰抑制均具有鲁棒的性能。

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