Experimental Investigation of Helicopter Weight and Mass Center Estimation

Abstract

Real-time estimates of weight and mass center location for helicopters are desirable for flight control and condition-based maintenance purposes. While methods to estimate mass parameters of helicopters have been developed, they often assume near-perfect knowledge of helicopter dynamics and have been validated only through simulated measurement data. The work described here aims to experimentally validate a method for weight and mass center estimation using an ALIGN T-REX 600e R/C helicopter. The estimation algorithm utilizes an extended Kalman filter (EKF) which estimates the helicopter states along with the weight and mass center location in real-time. Nonlinear system identification is performed using maximum likelihood estimation to create an accurate dynamic model for use in the EKF. Results show that given a reasonably accurate dynamic model, weight, stationline mass center location, and buttline mass center location can be reliably estimated in non-descending flight conditions. Weight estimation is shown to be robust to sudden weight changes during flight, whereas stationline and buttline mass center estimates are marginally robust to sudden shifts in the mass center location. Waterline mass center proved to be unobservable for the axial flight maneuvers conducted. Detailed flight test studies characterize estimation error in weight and three-dimensional mass center position using the EKF formulation.