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基于在线估计的多旋翼无人机抗扰动方法研究
Alternative TitleResearch on Anti-Disturbance Methods for Multi-Rotor Unmanned Aerial Vehicles Based on Online Estimation
江紫亚1,2
Department机器人学研究室
Thesis Advisor韩建达
ClassificationV249.1
Keyword多旋翼无人机 抗扰动控制 在线估计 模型参考自适应 自适应ukf 加速度增强控制
Call NumberV249.1/J44/2017
Pages103页
Degree Discipline模式识别与智能系统
Degree Name博士
2017-05-27
Degree Grantor中国科学院沈阳自动化研究所
Place of Conferral沈阳
Abstract由于具有垂直起降、定点悬停、超低空飞行等特点,多旋翼无人机在测绘侦察、灾难救援、农林植保、智慧物流等领域扮演着重要角色。然而,由于多旋翼无人机体积小、重量轻,气流扰动会对其运动产生较为明显的影响。此外,任务载荷的变化也会导致无人机质量和转动惯量发生较大程度的改变。多旋翼无人机本身是一个非线性、强耦合的欠驱动系统,加上这些参数扰动和气流扰动的不确定性,无疑给控制系统的设计带来了极大挑战。论文围绕这两大类扰动展开研究,旨在提高多旋翼无人机的抗扰动性能。论文的主要内容如下: 论文的第1章,对多旋翼无人机的研究背景及现状进行了论述,阐明了现有研究存在的不足,从而引出本论文的研究意义和研究内容。 论文的第2章,对多旋翼无人机的非线性模型进行了介绍,包括模型的性质和常用的简化,为后续估计和控制方法的验证提供仿真对象。 论文的第3章,在不考虑噪声的情况下,首先对多旋翼无人机非线性模型的参数辨识进行研究,提出了一种基于模型参考自适应的参数辨识方法,能够解决以非线性形式存在的参数的辨识问题,且对参数的变化能够快速跟踪。然而,由于所提方法中参数的更新率可能导致估计值发散,且方法并未对控制器设计进行讨论,接下来又提出了一种基于线性滤波降阶的自适应控制算法,通过仿真验证了该方法对姿态和高度的跟踪性能,以及持续激励条件下的参数辨识效果。 论文的第4章,首先比较了UKF方法与自适应方法在噪声存在情况下的辨识效果。为解决UKF方法需要噪声先验知识、数值稳定性较差的问题,论文提出了一种基于UD分解的自适应UKF方法,其思想在于实现理论协方差矩阵与实际协方差矩阵的匹配,再通过对原UKF算法中的协方差矩阵进行UD分解,能够提高滤波算法的估计性能和数值稳定性。同时,该方法为后续抗扰动控制中加速度信息的估计提供算法支持。 论文的第5章,主要对气流扰动下的多旋翼无人机稳定控制问题进行了研究,通过探讨加速度信息与扰动的关系、加速度估计方法,以及前置滤波的扰动抑制机理,提出了一种基于加速度估计的抗扰动控制方法,并通过仿真和第6章的实验进行了验证。 最后,在结论与展望部分,对论文所进行的研究进行了总结,并对后续可能的研究方向作了简要陈述。
Other AbstractDue to its advantages such as vertical take-off and landing (VTOL), precise hovering, minimum altitude flying, multi-rotor unmanned aerial vehicle (UAV) has played an important role in areas including survey and reconnaissance, disaster rescue, agriculture and forestry protection, intellectual logistics. However, as a result of small size and light weight, airflow disturbance will have a visible impact on multi-rotor UAV’s movement. In addition, changes in mission load can lead to a significant change in the mass and moment of inertia of the UAV. The uncertainty of these parameters perturbations and airflow disturbances will undoubtedly present a great challenge to the design of the control system since the multi-rotor UAV itself is a nonlinear, strongly coupled under-actuated system. This paper aims to improve the anti-disturbance performance of multi-rotor UAV. The main contents of the paper are as follows: In Chapter 1, the research background and current situation of multi-rotor UAV are discussed, and the existing problems of the existing research are elucidated, which leads to the research significance and main content of this thesis. In Chapter 2, the nonlinear model of multi-rotor UAV is introduced, including the characteristics of the model and the simplification of the model. It provides simulation objects for the subsequent estimation and verification of the control methods. In Chapter 3, the parameter identification for nonlinear model of multi-rotor UAV is studied without considering the noise. A model reference adaptive identification (MRAI) method is proposed, which can solve the identification problem of parameters existed in nonlinear format, and can quickly track the changes in parameters. However, since the update law of the parameters in the proposed method may lead to the divergence of the estimated value, and the method does not take the controller design into consideration, an adaptive control algorithm based on linear filtering is proposed. The tracking performance of the method for attitude and height, and the parameter identification convergence under persistent excitation (PE) conditions are demonstrated by simulations. In Chapter 4, we first compare the performance of parameter identification of UKF and MRAI method in the presence of noise. In order to solve the drawbacks that the UKF method needs the prior knowledge of noise and the numerical stability is poor, this paper proposes an adaptive UKF method based on UD decomposition. The idea is to match the theoretical covariance matrix with the actual covariance matrix, then the UD decomposition of the covariance matrices in original UKF is utilized to improve the numerical stability of the filtering algorithm, which results in a better estimation performance. At the same time, this method provides the algorithm support for the estimation of the acceleration information in the subsequent anti-disturbance control. In Chapter 5, the stability control of multi-rotor UAV under airflow disturbance is studied. By discussing the relationship between acceleration information and perturbation, the method of acceleration estimation and the perturbation suppression mechanism of pre-filter, an anti-disturbance control strategy based on online estimation of the (linear and angular) accelerations is proposed, whose effectiveness was verified through simulations and experiments conducted in Chapter 6. Finally, in the conclusion and prospect part, the research of the paper is summarized, and the possible research directions are briefly described.
Language中文
Contribution Rank1
Document Type学位论文
Identifierhttp://ir.sia.cn/handle/173321/20560
Collection机器人学研究室
Affiliation1.中国科学院沈阳自动化研究所
2.中国科学院大学
Recommended Citation
GB/T 7714
江紫亚. 基于在线估计的多旋翼无人机抗扰动方法研究[D]. 沈阳. 中国科学院沈阳自动化研究所,2017.
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