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Control Design for UAV Quadrotors via Embedded Model Control

机译:通过嵌入式模型控制对UAV时级调节器的控制设计

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摘要

In this paper, a control system for unmanned aerial vehicles (UAVs) is designed, tested in simulation by means of a high-fidelity simulator, and then applied to a real quadrotor UAV. A novel approach is proposed for the control design, based on the combination of two methodologies: feedback linearization (FL) and embedded model control (EMC). FL allows us to properly transform the UAV dynamics into a form suitable for EMC; EMC is then used to control the transformed system. A key feature of EMC is that it encompasses a so-called extended state observer (ESO), which not only recovers the system state but also gives a real-time estimate of all the disturbances/uncertainties affecting the system. This estimate is used by the FL-EMC control law to reject the aforementioned disturbances/uncertainties, including those collected via the FL, allowing a robustness and performance enhancement. This approach allows us to combine FL and EMC strengths. Most notably, the entire process is made systematic and application oriented. To set-up a reliable UAV attitude observer, an effective attitude sensors fusion is proposed and also benchmarked with an enhanced complementary filter. Finally, to enhance the closed-loop performance, a complete tuning procedure, encompassing frequency requirements, is outlined, based on suitably defined stability and performance metrics.
机译:在本文中,设计了一种无人驾驶飞行器(无人机)的控制系统,通过高保真模拟器进行了模拟测试,然后应用于真正的四轮车UAV。基于两种方法的组合,提出了一种用于控制设计的新方法:反馈线性化(FL)和嵌入式模型控制(EMC)。 FL允许我们将UAV Dynamics正常转换为适合EMC的形式;然后使用EMC来控制转换系统。 EMC的一个关键特征是它包括所谓的扩展状态观察者(ESO),其不仅恢复系统状态,还提供了影响系统的所有干扰/不确定性的实时估计。 FL-EMC控制法使用该估计,以拒绝上述扰动/不确定性,包括通过FL收集的扰动/不确定性,允许稳健性和性能增强。这种方法使我们能够结合FL和EMC优势。最值得注意的是,整个过程是系统的和应用面向的。为了设置可靠的无人机态度观察者,提出了一种有效的态度传感器融合,并通过增强型互补滤波器进行基准测试。最后,为了提高闭环性能,基于适当定义的稳定性和性能指标,概述了完整的调谐过程,包括频率要求。

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