並行学習によるクアッドロータの慣性パラメータ推定と制御
Concurrent Learning-Based Inertial Parameter Estimation and Control of Quadrotors
重心が幾何中心と一致しないクアッドロータに対し、積分並行学習を用いて質量・重心オフセット・慣性行列をオンライン推定しながら軌道追従する幾何学制御器を提案した論文。
著者: Sandesh Thapa, He Bai
分類: eess.SY, cs.RO
原文アブストラクト
In this letter, we consider trajectory tracking control and inertial parameter estimation of a quadrotor UAV whose center of mass (CoM) does not coincide with its geometric center. Onboard payloads like an IMU, a camera, or a battery are not necessarily placed at its geometric center. Moreover, during the flight these sensors might move because of external disturbances and cause a CoM offset. Thus, these events and equipment introduce an offset and cause the inertia matrix to be non-diagonal. We develop an integral concurrent learning (ICL)-based geometric controller that estimates the mass, the CoM offset, and the full inertia matrix online, without an accelerometer or numerical derivatives, and tracks a given trajectory corrected by the offset estimated online. We prove that the estimated parameters converge to their true values under a finite excitation condition. We validate the effectiveness of the proposed algorithm using a simulation example.