单旋翼无人直升机的旋翼系统建模与容错控制研究

Unmanned helicopter, which can takeoff and land vertically, is a special kind of aircraft and is widely used in both military and civilian fields. Single rotary wing configuration is one the most common used and widely applied configurations among all the unmanned helicopters. However, it is still an open problem to accurately model the unmanned helicopter since the complicity of the induced flow of the rotor. This project will overcome the shortages of existing dynamic inflow model and build a new one based on a finite state method to calculate the inflow both accurately and rapidly. Then the new inflow model will be used to calculate the wake with co-state approach, and the interaction of wake and tail rotor will also be studied. In full consideration of the dynamics of various parts of the helicopter, a new more precise model will be established. Moreover, some common failures of the unmanned helicopter will be modeled and considered in the context of fault tolerance strategy, and adaptive sliding mode control method will be used to construct a robust controller. The research will improve the accuracy of the model of the unmanned helicopter and the reliability of the whole system, as well as enrich the dynamic analyze approaches and control theory for unmanned helicopter.

无人直升机是一种可垂直起降的飞行器，在军用和民用领域都具有重要的应用价值。单旋翼无人直升机是其中最为常见，应用最为广泛的一种无人直升机。但由于旋翼诱导流场得复杂性，其准确建模一直是困扰学术界的难题。本项目将针对现有动态入流模型的缺点，构建新的基于有限状态方法的入流模型，使其兼具准确性和计算的快速性。并基于新的动态入流模型，采用co-state方法计算旋翼尾流，研究尾流与尾桨的相互作用。在充分考虑无人直升机各部分动态的前提下，建立新的准确的无人直升机模型。针对无人直升机常见故障，建模并采用自适应滑模控制的方法，设计容错控制器。本项目的研究成果将提高无人直升机建模准确性及系统的安全性与可靠性，丰富旋翼系统的动态分析方法以及无人机的控制理论。

单旋翼无人直升机是无人机系统中大量采用的结构，在军用和民用领域都具有重要的应用价值。但由于旋翼诱导流场得复杂性，其快速准确建模一直是困扰学术界的难题。本研究针对现有动态入流模型的缺点，构建新的基于有限状态方法的入流模型，使其兼具准确性和计算的快速性，并结合co-state方法重构了计算旋翼系统下方的模型的计算方法。考虑到无人直升机的动态特性及工作环境等，结合本单位研究特长，以及无人旋翼系统研究中遇到的问题及其多模态的特点，深入研究了切换系统的相关的理论，并解决了二维系统的控制与滤波，切换系统的有限时间控制，可达集估计，随机Markov时滞系统的控制和滤波等问题，取得了一系列成果。.. 在本项目支持下，项目组在基金执行期间共发表SCI检索论文16篇（其中包含本领域顶级期刊Automatica论文1篇，IEEE transactions on Automatic Control论文2篇），参加本领域国内/国际重要会议4次，并宣读相关研究成果。申请人入选哈尔滨工业大学基础研究杰出人才，并获得黑龙江省自然科学一等奖，获得自然科学基金面上项目支持（2019.01-2022.12）。