Clearance Nonlinear Control Method of Electro-Hydraulic Servo System Based on Hopfield Neural Network

Machines Pub Date : 2024-05-11 DOI:10.3390/machines12050329
Tao Wang, Jinchun Song
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Abstract

The electro-hydraulic servo system has advantages such as high pressure, large flow, and high power, etc., which can also realize stepless regulation, so it is widely used in many engineering machineries. A linear model is sometimes only a simple approximation of an idealized model, but in an actual system, there may be nonlinear and transient variation characteristics in the systems. Coupling is reflected in the fact that the components or functional structures implemented by each system used for the design of hydraulic systems are not completely or independently related to each other, but affect each other. The nonlinear clearance between the actuator and the load reduces the control accuracy of the system and increases the impact, thus losing stable working conditions. In the paper, based on the nonlinear clearance problem of the electro-hydraulic servo system, a mathematical transfer model with clearance is established, and on this basis, a clearance compensation method based on the Hopfield neural network is proposed. In this way, clearance compensation can be realized by adjusting the parameters of neural network nodes, through simple and convenient operation. Finally, by setting different clearance values, the results of the step response and sine response curve before and after clearance compensation of the hydraulic system are compared, and the effectiveness of Hopfield neural network compensation clearance control is verified based on the comparison simulation results.
基于 Hopfield 神经网络的电液伺服系统清零非线性控制方法
电液伺服系统具有压力高、流量大、功率大等优点,还可以实现无级调节,因此被广泛应用于许多工程机械中。线性模型有时只是理想化模型的简单近似,但在实际系统中,系统可能存在非线性和瞬态变化特性。耦合性体现在用于液压系统设计的每个系统所实现的组件或功能结构之间并非完全或独立相关,而是相互影响。执行器与负载之间的非线性间隙会降低系统的控制精度,增加冲击力,从而失去稳定的工作条件。本文基于电液伺服系统的非线性间隙问题,建立了带间隙的数学传递模型,并在此基础上提出了基于 Hopfield 神经网络的间隙补偿方法。这样,通过调整神经网络节点的参数,就可以实现间隙补偿,操作简单方便。最后,通过设置不同的间隙值,比较了液压系统间隙补偿前后的阶跃响应和正弦响应曲线结果,并根据比较仿真结果验证了 Hopfield 神经网络补偿间隙控制的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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