模糊神经网络控制EHSS速度

S.A. Mohseni, M. Aliyari, M. Teshnehlab
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引用次数: 12

摘要

本文提出了一种模糊神经网络(FNN)用于存在流量非线性和内耗的电液伺服系统的速度控制。该系统包含几个主要的非线性,限制了简单控制器获得满意性能的能力。这些非线性包括:阀门死区、阀门流量饱和和气缸密封摩擦。由于液压动力学的高度非线性,传统线性控制器(如PD)所能达到的性能通常受到限制。结果表明,本文所采用的模糊神经控制器可以成功地稳定系统的任意工作点。将误差反向传播(EBP)方法应用于FNN,并指出其优点。该方法可进一步推广到液压驱动机械手的控制中。通过对系统的非线性数学模型进行计算机仿真,验证了所得结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
EHSS Velocity Control by Fuzzy Neural Networks
In this paper a fuzzy neural network (FNN) is presented for velocity control of an electro hydraulic servo system (EHSS) in presence of flow nonlinearties and internal friction. The system contains several major nonlinearties that limit the ability of simple controllers in achieving satisfactory performance. These nonlinearties include: valve dead zones, valve flow saturation, and cylinder seal friction. The performances achievable by classical linear controllers, e.g. PD, are usually limited due to highly nonlinear behavior of the hydraulic dynamics. It is shown that the fuzzy neural controller, which is employed in this paper, can be successfully used to stabilize any chosen operating point of the system. The EBP (error back propagation) method is employed in FNN and the advantaged are mentioned. The approach can be further extended to the control of hydraulically driven manipulators. All derived results are validated by computer simulation of a nonlinear mathematical model of the system.
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