飞机舵机电液负载模拟器多余力抑制方法研究

发布时间：2018-07-06 14:09

本文选题：飞机舵机电液负载模拟器 + 多余力抑制　；参考：《中国民航大学》2016年硕士论文

【摘要】：飞机舵机电液负载模拟器是在实验室条件下模拟舵机在飞机飞行过程中所受到的气动载荷,具有良好的可控性、无破坏性等优点。该模拟器是被动式力伺服控制系统,其中舵机的主动运动会使系统产生多余力。由于多余力的存在严重影响系统的控制性能,因此如何最大程度地抑制乃至消除多余力干扰,已成为我国民航飞机飞行控制领域亟待解决的研究课题。在目前国内外电液负载模拟器研究现状的基础上,首先分析了飞机舵机电液负载模拟器的结构组成及其工作原理,根据负载模拟器的技术指标,确定了系统主要元件的型号。其次,建立了电液伺服阀、液压缸、力传感器和缓冲弹簧的数学模型,从而构建了系统整体数学模型,并定性地研究了多余力的产生机理。再次,提出了结合液压缸速度信号前馈、常规PID反馈的复合控制器结构,解决了系统在低频、大加载梯度下的多余力抑制问题,但在高频、小加载梯度下的多余力抑制效果较差。为此,提出了结合液压缸速度信号前馈、基于RBF神经网络在线辨识的单神经元PID反馈的复合控制器结构。最后,从控制系统的观点来看,RBF神经网络的辨识效果较差,因此有必要对具有高聚类质量的最近邻聚类算法进行研究,使其应用于RBF神经网络之中。又由于最近邻聚类算法的聚类中心及聚类半径不易获得,进而降低聚类效果,因此需要对该算法进行改进,为此采用蚁群聚类算法对RBF神经网络进行优化。通过计算机仿真实验进一步验证结论的可行性和有效性。
[Abstract]:The aircraft rudder electrohydraulic load simulator is a simulation of the aerodynamic load of the steering gear in the flight process under the laboratory conditions, which has the advantages of good controllability, no destructive and so on. The simulator is a passive force servo control system, in which the active sports of the steering gear make the system produce multiple Yu Li. As the existence of redundant force seriously affects the control performance of the system, how to suppress or eliminate the multiple Yu Li interference to the greatest extent has become an urgent research topic in the field of flight control of civil aviation aircraft in China. Based on the research status of electro-hydraulic load simulator at home and abroad, the structure composition and working principle of the aircraft rudder electrohydraulic load simulator are analyzed. According to the technical index of the load simulator, the model of the main components of the system is determined. Secondly, the mathematical models of electro-hydraulic servo valve, hydraulic cylinder, force sensor and buffer spring are established, and the overall mathematical model of the system is constructed, and the mechanism of producing multiple Yu Li is studied qualitatively. Thirdly, the structure of compound controller combined with feed forward of hydraulic cylinder speed signal and conventional pid feedback is proposed, which solves the problem of redundant force suppression under low frequency and large loading gradient, but at high frequency. The suppression effect of superfluous force under small loading gradient is poor. In this paper, a single neuron pid feedback controller structure based on RBF neural network is proposed, which combines the feed forward of hydraulic cylinder velocity signal and on-line identification of RBF neural network. Finally, from the point of view of the control system, the identification effect of RBF neural network is poor, so it is necessary to study the nearest neighbor clustering algorithm with high clustering quality, so that it can be applied to RBF neural network. Because the clustering center and radius of nearest neighbor clustering algorithm are not easy to get, and then reduce the clustering effect, it is necessary to improve the algorithm. Therefore, the ant colony clustering algorithm is used to optimize the RBF neural network. The feasibility and effectiveness of the conclusions are further verified by computer simulation experiments.
【学位授予单位】：中国民航大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：V249.1

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