Moore Joseph, Cory Rick, Tedrake Russ
MIT 32-380, Cambridge, MA 02139, USA.
Bioinspir Biomim. 2014 Jun;9(2):025013. doi: 10.1088/1748-3182/9/2/025013. Epub 2014 May 22.
Birds routinely execute post-stall maneuvers with a speed and precision far beyond the capabilities of our best aircraft control systems. One remarkable example is a bird exploiting post-stall pressure drag in order to rapidly decelerate to land on a perch. Stall is typically associated with a loss of control authority, and it is tempting to attribute this agility of birds to the intricate morphology of the wings and tail, to their precision sensing apparatus, or their ability to perform thrust vectoring. Here we ask whether an extremely simple fixed-wing glider (no propeller) with only a single actuator in the tail is capable of landing precisely on a perch from a large range of initial conditions. To answer this question, we focus on the design of the flight control system; building upon previous work which used linear feedback control design based on quadratic regulators (LQR), we develop nonlinear feedback control based on nonlinear model-predictive control and 'LQR-Trees'. Through simulation using a flat-plate model of the glider, we find that both nonlinear methods are capable of achieving an accurate bird-like perching maneuver from a large range of initial conditions; the 'LQR-Trees' algorithm is particularly useful due to its low computational burden at runtime and its inherent performance guarantees. With this in mind, we then implement the 'LQR-Trees' algorithm on real hardware and demonstrate a 95 percent perching success rate over 147 flights for a wide range of initial speeds. These results suggest that, at least in the absence of significant disturbances like wind gusts, complex wing morphology and sensing are not strictly required to achieve accurate and robust perching even in the post-stall flow regime.
鸟类能够常规地执行失速后的机动动作,其速度和精度远远超出了我们最好的飞机控制系统的能力。一个显著的例子是,一只鸟利用失速后的压力阻力迅速减速,以便降落在栖木上。失速通常与控制权限的丧失相关联,人们很容易将鸟类的这种敏捷性归因于其翅膀和尾巴复杂的形态、精确的传感装置或它们执行推力矢量控制的能力。在这里,我们要问的是,一个极其简单的固定翼滑翔机(无螺旋桨),其尾部只有一个致动器,是否能够在大范围的初始条件下精确地降落在栖木上。为了回答这个问题,我们专注于飞行控制系统的设计;在之前基于二次调节器(LQR)的线性反馈控制设计的工作基础上,我们开发了基于非线性模型预测控制和“LQR树”的非线性反馈控制。通过使用滑翔机的平板模型进行模拟,我们发现这两种非线性方法都能够在大范围的初始条件下实现类似鸟类的精确栖息机动动作;“LQR树”算法特别有用,因为它在运行时的计算负担低,并且具有固有的性能保证。考虑到这一点,我们随后在实际硬件上实现了“LQR树”算法,并在147次飞行中针对各种初始速度展示了95%的栖息成功率。这些结果表明,至少在没有像阵风这样的重大干扰的情况下,即使在失速后气流状态下,要实现精确而稳健的栖息,并不严格需要复杂的机翼形态和传感。