小型ターボジェットエンジンの推力推定のための非線形モデル同定とオブザーバ設計
Nonlinear Model Identification and Observer Design for Thrust Estimation of Small-scale Turbojet Engines
小型ターボジェットの回転数計測のみから推力を推定するため、グレーボックス法で非線形状態空間モデルを同定し、拡張カルマンフィルタを設計・検証した論文。
著者: Affaf Junaid Ahamad Momin, Gabriele Nava, Giuseppe LErario, Hosameldin Awadalla Omer Mohamed, Fabio Bergonti, Punith Reddy Vanteddu, Francesco Braghin, Daniele Pucci
分類: cs.RO, cs.SY, eess.SY
原文アブストラクト
Jet-powered vertical takeoff and landing (VTOL) drones require precise thrust estimation to ensure adequate stability margins and robust maneuvering. Small-scale turbojets have become good candidates for powering heavy aerial drones. However, due to limited instrumentation available in these turbojets, estimating the precise thrust using classical techniques is not straightforward. In this paper, we present a methodology to accurately estimate the online thrust for the small-scale turbojets used on the iRonCub - an aerial humanoid robot. We use a grey-box method to capture the turbojet system dynamics with a nonlinear state-space model based on the data acquired from a custom engine test bench. This model is then used to design an extended Kalman filter that estimates the turbojet thrust only from the angular speed measurements. We exploited the parameter estimation algorithm to ensure that the EKF gives smooth and accurate estimates even at engine failures. The designed EKF was validated on the test bench where the mean absolute error in estimated thrust was found to be within 2% of rated peak thrust.
