Research on stability of hydraulic system based on nonlinear PID control

IF 2.4 Q2 ENGINEERING, MECHANICAL
Tong Liu
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引用次数: 1

Abstract

Abstract In order to avoid the interference of the excavator hydraulic control system by external factors, the output stability of the hydraulic control system has to be improved. The method introduces a nonlinear Proportional integral differentiation (PID) controller with deviation correction parameters through the simulation verification of the control effect and the creation of excavator hydraulic drive diagram. PID, whose full English name is proportional integral derivative, is a mathematical and physical term. The controller is modeled in Matlab/Simulink. Finally, the whole hydraulic system is co-simulated by the interface of AMESim and Matlab. The simulation results show that the system model realizes the co-simulation through the interface combination of the two software, which is more accurate than the traditional PID control, and the pressure and flow fluctuation are smaller, which can suppress the interference of external load mutation, and improve the stability of the hydraulic drive output of the excavator. The validity of the experiment is verified.
基于非线性PID控制的液压系统稳定性研究
摘要为了避免挖掘机液压控制系统受到外界因素的干扰,必须提高液压控制系统的输出稳定性。该方法通过对控制效果的仿真验证和挖掘机液压驱动图的创建,引入了带有偏差校正参数的非线性比例积分微分(PID)控制器。PID的英文全称是比例积分导数,是一个数学和物理术语。在Matlab/Simulink中对控制器进行了建模。最后,利用AMESim和Matlab软件对整个液压系统进行了联合仿真。仿真结果表明,该系统模型通过两种软件的接口组合实现了联合仿真,比传统的PID控制更加精确,且压力和流量波动较小,可以抑制外部负载突变的干扰,提高挖掘机液压驱动输出的稳定性。验证了实验的有效性。
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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来源期刊
CiteScore
6.20
自引率
3.60%
发文量
49
审稿时长
44 weeks
期刊介绍: The Journal of Nonlinear Engineering aims to be a platform for sharing original research results in theoretical, experimental, practical, and applied nonlinear phenomena within engineering. It serves as a forum to exchange ideas and applications of nonlinear problems across various engineering disciplines. Articles are considered for publication if they explore nonlinearities in engineering systems, offering realistic mathematical modeling, utilizing nonlinearity for new designs, stabilizing systems, understanding system behavior through nonlinearity, optimizing systems based on nonlinear interactions, and developing algorithms to harness and leverage nonlinear elements.
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