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Qualitative analysis of guidance and control methods for wind gradients exploitation with small fixed wing UAS

机译:小型固定翼UAS的风梯度导引与控制方法的定性分析。

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摘要

In this paper, different Guidance and Control (GC) methods for trajectory tracking are analyzed. This effort considers the ongoing research effort regarding wind features characterization and trajectory generation. The investigation of GC methods is contextualized for long duration missions of small Unmanned Aerial Systems (UAS). These are often hampered by the platform characteristics with cost and weight stringent restrictions. Therefore, innovative ways of increasing flight duration are necessary to fulfill the safety and reliability requirements for such missions fulfilling the cost and weight constraints. Atmospheric Energy Harvesting has been studied as an alternative for flight duration enhancement. The guidance and control strategies have been focused in the dynamic soaring case, in which the trajectories require precise tracking for energy gain. This gain depends on the tracking ability of the autopilot which motivates this analysis. As a conclusion to this analysis, two methodologies are chosen as candidates for GC, one based on pure differential geometry techniques to formulate simple error equations, and the other that uses adaptive control strategies based on vector field theory to formulate error equations and a Lyapunov function ensuring asymptotic stability with complex curve shapes and wind disturbances.
机译:在本文中,分析了用于轨迹跟踪的不同制导和控制(GC)方法。这项工作考虑了正在进行的有关风特征表征和轨迹生成的研究工作。对于小型无人机系统(UAS)的长时任务,GC方法的研究是情境化的。这些通常受到平台特性的限制,并受到成本和重量的严格限制。因此,需要增加飞行持续时间的创新方法来满足此类任务的安全性和可靠性要求,从而满足成本和重量限制。大气能量收集已被研究作为增加飞行时间的替代方法。制导和控制策略已集中在动态飞升的情况下,在这种情况下,轨迹需要精确跟踪以获取能量。该增益取决于自动驾驶仪的跟踪能力,从而激发了这一分析。作为此分析的结论,选择了两种方法作为GC的候选方法,一种方法是基于纯微分几何技术来制定简单的误差方程,另一种方法是使用基于矢量场理论的自适应控制策略来制定误差方程和Lyapunov函数通过复杂的曲线形状和风扰来确保渐近稳定性。

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