Purpose

The paper aims at developing a novel algorithm to estimate high-order derivatives of rotorcraft angular rates to break the contradiction between bandwidth and filtering performance because high-order derivatives of angular rates are crucial to rotorcraft control. Traditional causal estimation algorithms such as digital differential filtering or various tracking differentiators cannot balance phase-lead angle loss and high-frequency attenuation performance of the estimated differentials under the circumstance of strong vibration from the rotor system and the rather low update rate of angular rates.

Design/methodology/approach

The algorithm, capable of estimating angular rate derivatives to maximal second order, fuses multiple attitude signal sources through a first-proposed randomized angular motion maneuvering model independent of platform dynamics with observations generated by cascaded tracking differentiators.

Findings

The maneuvering flight test on 5-kg-level helicopter and the ferry flight test on 230-kg-level helicopter prove such algorithm is feasible to generate higher signal to noise ratio derivative estimation of angular rates than traditional differentiators in regular flight states with enough bandwidth for flight control.

Research limitations/implications

The decrease of update rate of input attitude signals will weaken the bandwidth performance of the algorithm and higher sampling rate setting is recommended.

Practical implications

Rotorcraft flight control researchers and engineers would benefit from the estimation method when implementing flight control laws requiring angular rate derivatives.

Originality/value

A purely kinematic randomized angular motion model for flight vehicle is first established, combining rigid-body Euler kinematics. Such fusion algorithm with observations generated by cascaded tracking differentiators to estimate angular rate derivatives is first proposed, realized and flight tested.

中文翻译：

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旋翼机角速率的高阶导数融合估计

目的

本文旨在开发一种新颖的算法来估计旋翼飞机角速率的高阶导数，以打破带宽和滤波性能之间的矛盾，因为角速率的高阶导数对于旋翼飞机的控制至关重要。传统的因果估计算法，例如数字差分滤波或各种跟踪微分器，在转子系统强烈振动且角速率的更新率相当低的情况下，无法平衡相位前角损失和估计差分的高频衰减性能。

设计/方法/方法

该算法能够将角速率导数估计为最大二阶，并通过与平台动力学无关的第一个提议的随机角运动操纵模型融合多个姿态信号源，并通过级联跟踪微分器生成观测值。

发现

在具有足够带宽的常规飞行状态下，与传统的微分器相比，该算法在5公斤级直升机的机动飞行试验和230公斤级直升机的渡轮飞行试验中证明了这种算法可产生比传统微分器更高的角速率信噪比导数估计。用于飞行控制。

研究局限/意义

输入姿态信号更新速率的降低会削弱算法的带宽性能，建议使用更高的采样率设置。

实际影响

当执行要求角速度导数的飞行控制法则时，旋翼飞机的飞行控制研究人员和工程师将受益于估计方法。

创意/价值

结合刚体欧拉运动学，首先建立了飞行器的纯运动学随机角运动模型。首先提出，实现并测试了这种融合算法，该算法具有由级联跟踪微分器生成的观测值以估计角速率导数。