四旋翼直升无人机
本文为美国麻省理工学院（作者：Zachary Thompson Dydek）的博士学位论文，共139页。
自适应控制被认为是未来高性能、关键安全系统（如高超声速飞行器）的关键技术之一。由于自适应飞行控制系统能够根据在线测量数据调整控制参数，从而提供了改进的性能和应对不确定性的增强鲁棒特性。自适应控制理论领域中的广泛研究使得稳定自适应系统的设计、分析和综合成为可能。当前我们的研究正在进入一个阶段，在这个阶段中，自适应飞行控制系统已经达到应用于硬件飞行平台的必要成熟度。
无人机系统（UAS）为自适应控制器从理论到实践的过渡提供了独特的契机。本文研究的小型无人机（UAV）在仿真与高风险系统应用之间提供了一个低成本、低风险的跳板，其中安全性是最关键的问题。与有人飞行器相比，无人机本身具有一些好处，其中包括极限续航性、机动性、重量轻和更小的尺寸。此外，监视、探索、搜索跟踪以及重物运送等最好由多个UAV组成的UAS来完成。本文讨论了自适应飞行控制系统在UAS应用中所面临的一些挑战。
为了克服无人机系统的性能限制，开发了新的自适应控制体系架构，其中最重要的贡献是降低了由于通信和有限机载处理能力导致的较大时延。还开发了计算理论上合理的时间延迟极限的分析工具，这些工具反过来实现对闭环系统时滞裕度的估计，这是智能飞行控制系统验证和验证方法的基本部分。这些方法使用一系列仿真研究进行了数值验证，然后将这些控制器和分析方法应用于无人机，实践证明了改进的性能和对时延增加的鲁棒性。
本文还介绍了一种新的多架UAS协调自适应控制方法。在模拟和实际飞行试验中，发现局部和全局两种不同级别的自适应算法可减少单个无人机的跟踪误差、降低无人机之间的距离估计误差，并减少与其它无人机或障碍物碰撞的可能性。
Adaptive control is considered to be one of the key enablingtechnologies for future high-performance, safety-critical systems such asair-breathing hypersonic vehicles. Adaptive flight control systems offerimproved performance and increased robustness to uncertainties by virtue oftheir ability to adjust control parameters as a function of onlinemeasurements. Extensive research in the field of adaptive control theory has enabledthe design, analysis, and synthesis of stable adaptive systems. We are now enteringthe stage in which adaptive flight control systems have reached the requisite levelof maturity for application to hardware flight platforms. Unmanned aerialsystems (UAS) provide a unique opportunity for the transition of adaptivecontrollers from theory to practice. The small, unmanned aerial vehicles (UAVs)examined in this thesis offer a low-cost, low-risk stepping stone between simulationand application to higher-risk systems in which safety is a critical concern. Unmannedaircraft also offer several benefits over their manned counterparts including extremepersistence, maneuverability, lower weight and smaller size. Furthermore, severalmissions such as surveillance, exploration, search-and-track, and lifting of heavyloads are best accomplished by a UAS consisting of multiple UAVs. This thesisaddresses some of the challenges involved with the application of adaptive flightcontrol systems to UAS. Novel adaptive control architectures are developed toovercome performance limitations of UAS, the most significant of which is alarge time delay due to communication and limited onboard processing.Analytical tools that allow the calculation of a theoretically justified timedelay limit are also developed. These tools in turn lead to an estimate of thetime-delay margin of the closed-loop system which is an essential part of thevalidation and verification methodology for intelligent flight control systems.These approaches are validated numerically using a series of simulationstudies. These controllers and analytical methods are then applied to the UAV,demonstrating improved performance and increased robustness to time delays.Also introduced in this thesis is a novel adaptive methodology for coordinatedadaptive control of a multi-vehicle UAS. Including two distinct classes ofadaptive algorithms at both the local and global levels was found to result,both in simulation and in actual flight tests, in decreased tracking error forindividual vehicles, decreased errors in intervehicle distances, and reducedlikelihood of collisions with other vehicles or obstacles in the environment.
1 引言
2 项目背景
3 参数不确定性的无人机自适应控制
4 通用系统的参数不确定与时延分析
5 具有参数不确定性的无人机组合/复合自适应控制
6 多无人机组队的自适应参数控制
7 总结与未来研究展望
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