Comparison of linear and nonlinear aerodynamic parameter estimation approaches for an unmanned aerial vehicle using unscented Kalman filter

Aerodynamic parameter estimation provides an effective way for aerospace system modeling using measured data from flight tests, especially for the purpose of developing elaborate simulation environments and designing control systems of unmanned aerial vehicle （UAV） with short design cycles and reduced cost. However, parameter identification of airplane dynamics by nonlinear mod- els is complicated because of the noisy and biased sensor measurements. Using linear models for system identification is an alternative way if the fidelity can be guaranteed, as control design procedures are better established in linear systems. This paper considers the application and comparison of linear as well as nonlinear aerodynamic parameter estimation approaches of an UAV using unscented Kalman filter （UKF）. It also highlights the degree of deterioration of the linear model in the UKF identification process. The results show that both the linear and nonlinear methodologies can accurately estimate the control system design. Furthermore, considering loss of accuracy to be negligible, the linear model can be employed for control design of the UAV as presented here.

一对纳米卫星编队飞行控制的分析

本文针对两颗纳米卫星受到控制和状态约束、且存在有界扰动和测量误差的情况下，分析并提出了它们的稳定和机动控制的可行方法。本主题是当前的一个热门研究领域(参见文献1—6)，这些文章利用了多种配置和算法。目前实现约束控制的方法不多。本文采用改进后的时间最优鲁棒控制方法，可降低能量消耗。文献7介绍的受约束的时间最优控制问题的解要求计算鲁棒可控性集合Xi(Xi是在存在扰动的情况下，可以在i步时间内将状态控制到目标集合B^t的状态集合)。在大部分实际应用中，这些集合太复杂。在本文中，我们利用一种有效的新方法[广义钻石(Diamond)方法]计算可控性集合的内部近似值，以回避该问题的复杂性。然后用这些内部近似值为这个约束系统提供有效的非线形控制，其性能损失很小。