Aided Inertial Estimation of Wing Shape

Abstract

Advanced large-wing-span aircraft result in more structural flexibility and the potential for instability or poor handling qualities. These shortcomings call for stability augmentation systems that entail active structural control. Consequently, the in-flight estimation of wing shape is beneficial for the control of very flexible aircraft. This paper proposes a new methodology for estimating flexible structural states based on extended Kalman filtering by exploiting ideas employed in aided inertial navigation systems. High-bandwidth-rate gyro angular velocities at different wing stations are integrated to provide a short-term standalone inertial shape estimation solution, and additional low-bandwidth aiding sensors are then employed to bound diverging estimation errors. The proposed filter implementation does not require a flight dynamics model of the aircraft, facilitates the often tedious Kalman filtering tuning process, and allows for accurate estimation under large and nonlinear wing deflections. To illustrate the approach, the technique is verified by means of simulations using sighting devices as aiding sensors, and an observability study is conducted. In contrast to previous work in the literature based on stereo vision, a sensor configuration that provides fully observable state estimation is found using only one camera and multiple rate gyros for Kalman filtering update and prediction phases, respectively.