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题名: 面向旋翼飞行机器人估计与控制方法及实验研究
其他题名: Experimental Research on Estimation and Control for Fly-robot with Rotor Wings
作者: 宋大雷
导师: 刘光军 ; 韩建达
分类号: V249.32
关键词: 旋翼飞行机器人 ; 主动模型控制 ; 模型预测控制 ; 自适应集员估计 ; 飞行实验研究
索取号: V249.32/S86/2011
学位专业: 模式识别与智能系统
学位类别: 博士
答辩日期: 2011-11-30
授予单位: 中国科学院沈阳自动化研究所
学位授予地点: 中国科学院沈阳自动化研究所
作者部门: 机器人学研究室
中文摘要: 旋翼飞行机器人拓展了无人飞行器潜在的应用价值,具有垂直起降,定点悬停,低空低速飞行等能力。与传统大型直升机相比,旋翼飞行机器人具有更强的机动能力和响应能力。但是,从80年代末旋翼飞行机器人概念提出直至今日的近30年的研究中,虽然提出大量的控制与估计方法,并且已经解决了悬停与低速飞行模态下系统镇定与跟踪问题,但是旋翼飞行机器人潜在的机动能力并没有完全被开发,与系统本身潜在的机动能力相距甚远,因此,目前自主型旋翼飞行机器人飞行能力无法满足其在民事与军事方面的应用需求。迫切地需要进行估计与控制方法实验研究,以获得一套完整而且可工程应用的旋翼飞行机器人系统全包线飞行控制方法。 本论文在上述工程应用的背景下,以中国科学院沈阳自动化研究所机器人学国家重点实验室的旋翼飞行机器人平台为研究对象,以制约旋翼飞行机器人控制策略实施的复杂且滞后系统动力学为主要的待解决问题,在理论上结合自适应集员估计方法(ASMF),创造性地引入主动模型控制思想,并对于现有系统辨识和预测控制方法面向旋翼飞行机器人系统应用中存在的问题进行改进,最终提出了基于主动增量模型的预测控制策略和悬停动力学参考模型的频域辨识方法,并对所提出的理论,完成了稳定性分析与实际飞行实验验证。在此基础上总结出了面向旋翼飞行机器人大机动飞行控制的工程化实施步骤。本文的主要研究工作如下: (1)旋翼飞行机器人悬停动力学辨识方法 首先进行旋翼飞行机器人的动力学模型结构的分析,从刚体运动学角度获得其非线性描述,在悬停模态附近进行泰勒展开,获得其线性表达形式,并通过旋翼动力学分析,展开系统驱动力与力矩得到线性动力学方程的参数化表达;其次,在传统单入单出频域参数辨识方法基础上,化简参数方程结构,通过优化函数的改进,使其可应用于多入多出线性系统,并给出初始参数估计的方法和收敛性判定准则;最后,结合传统频域辨识方法的收敛性定理,给出了改进后频域辨识流程的收敛性证明。 (2)基于相对增量模型的预测控制方法 对传统预测控制方法进行改进,引入增量模型预测,未来控制量规划以及关注状态转化手段,解决特定飞行模态下的模型漂移和工作点转换造成的预测器有偏问题,在线状态参考值规划问题以及计算量达的问题,使得旋翼飞行机器人系统控制的滞后环节的到有效的补偿。 (3)基于ASMF的模型差估计与修正策略 面向旋翼飞行机器人在全飞行包线中应用所存在的模型失配问题,提出模型差的数学表达,并且基于ASMF提出了模型差,即模型失配程度,在线估计及其控制修正策略,以保证基于特定飞行模态下的参考模型所设计的控制器在多种飞行模态转变的实际应用中的鲁棒性和跟踪性能。 (4)旋翼飞行机器人实验研究 针对上述研究结果,分别对模型辨识和主动模型控制进行控制性能改进前后的对比实验,并验证方法研究中涉及的假设条件的真实性,如过程噪声非正态性、驱动滞后环节存在性等,通过飞行实验证明本文提出的方法可以针对实际旋翼飞行机器人系统进行大机动飞行控制,且比传统飞行控制策略的控制性能有所提升。 本文的工作丰富了旋翼飞行机器人自主控制研究的内容,对搭建高控制性能的旋翼飞行机器人系统进行了有益的尝试,有助于推动机器人自主行为研究和相关技术的发展。
英文摘要: Fly-robot with rotor wings expands the potential application range of UAVs, it has the capability of vertical take-off and landing, spot hovering, low speed and altitude cruise and etc. Comparing with traditional large helicopters, fly-robot with rotor wings provides greater agilities and reactivity. But from the propose of the fly-robot with rotor wings concept in late 1980s, despite the release of numerous control and estimation methodologies and the resolving of the hovering and low speed tracking and stabilization problem, the potential agilities have never been fully explored, the system still has huge potential agilities to release, therefore, the flying capacity of a autonomous fly-robot with rotor wings cannot meet with its various civil and military needs. In order to complete applicable flight control algorithm for Fly-robot with rotor wings in full envelope, the research of control and estimation methodologies has become an urgent need. With this background, the paper is based on the fly-robot platform, built by Shenyang Institue of Automation, Chineses Academy of Scineces, the problem of the time-delay in system dynamics was solved, the theory was combined with adaptive set-membership filter (ASMF), the logics in active controlling method were creatively introduced in, and defects in modern system identification and predictive control were improved for fly-robot with rotor wings, after all active incremental model based predictive control and frequency identification for hovering dynamics were concluded, the stability analysis and flying test of all the proposed theories were completed. Based on these theories, the procedures of applications to fly-robot were proposed. The following sections were included in this paper: (1) The identification method for the hovering dynamics of the fly-robot First the dynamic structure of the fly-robot with rotor wings was analyzed, then non-linear description of the object was obtained, Taylor transformation was performed near the hovering region to get its linear representation, after that it was analyzed using rotor craft dynamics, the system driving force and torque equations were expended to get linear equations for the dynamics. Based on the traditional SISO spectrum parameter recognition method, the equations were simplified. The system was optimizing to MIMO linear system, the initial parameter estimation method and convergence criterion were also listed. At last, with the convergence criterions in the traditional spectrum recognition method the convergence for the optimized spectrum recognition process was tested. (2) The predictive control method based on relative incremental model The traditional predictive control method was improved; the incremental model prediction, aftertime control scheme and state shift oriented instrument were introduced to rectify the predictor error, solve the online reference value planning problem and release the computational extensiveness that were caused by model and working point shift in specific flying mode. The time-delay part for the control system of the fly-robot with rotor wings was compensated effectively.  (3) ASMF baesd estimation and correction strategy for model difference The mathematical interpretation for the model difference, the rectifying strategy for online estimation and the model unmatching problem in the application of fly-robot with rotor wings were listed. This is to ensure in real applications the robustness and tractability of the flight control system which was based on the reference model in specific flying mode when shifting between various flight modes. (4) Experimental research on fly-robot with rotor wings For the results above, a contrast experiment was performed between the original and optimized system to compare their model recognition and active model control abilities. The validities of the hypothesis such as the non-positive noise in the process and the existence of the driving lag were also tested in this experiment. By carrying out these tests, the strategies in this paper was proved that it could be used in the control system for a more agile fly-robot with rotor wings and it was more efficient than the traditional control strategy. This paper enriched the research in an auto pilot system for the fly-robot with rotor wings. It was also very helpful for building a more controllable system for the Fly-robot. It pushed the technology forward and was good for researches in robotics.
语种: 中文
产权排序: 1
内容类型: 学位论文
URI标识: http://ir.sia.cn/handle/173321/9400
Appears in Collections:机器人学研究室_学位论文

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Recommended Citation:
宋大雷.面向旋翼飞行机器人估计与控制方法及实验研究.[博士学位论文].中国科学院沈阳自动化研究所.2011
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