柴油机共轨压力自适应神经模糊PID控制研究  

Adaptive neural fuzzy PID control of common-rail pressure for diesel engine

作　　者：徐龙 陈国金[1] 朱凌俊[1] 陈昌[1] 

机构地区：[1]杭州电子科技大学机械工程学院,浙江杭州310018

出　　处：《机电工程》2018年第2期213-218,共6页Journal of Mechanical & Electrical Engineering

基　　金：国家自然科学基金资助项目(51405117;51675148;51541507);浙江省重点研发计划资助项目(2015C04002);校内创新实践基地建设项目(JDR201709)

摘　　要：针对高压共轨柴油机共轨压力的精确控制问题,对共轨压力的控制方法进行了归纳研究,提出了一种基于T-S型自适应神经模糊推理系统(ANFIS)与PID控制器相结合的共轨压力控制算法。在Matlab/Simulink环境中,利用已完成的自适应神经模糊PID控制器搭建轨压的控制算法仿真模型,与常规PID控制进行了初步的仿真比较;通过实验监测到共轨压力的波动曲线,对两种控制方法在起动和加速两种过渡工况下的控制效果进行了分析比较。研究结果表明:自适应神经模糊PID控制的稳态、动态特性以及抗干扰性都明显优于常规PID控制;在起动和加速两种过渡工况下,自适应神经模糊PID控制的共轨压力波动幅度均较小,符合实际应用中对共轨压力稳定性的要求。Aiming at the precise control of the common-rail pressure of the high pressure common-rail diesel engine,the control method of the common-rail pressure was summarized,and a common-rail pressure control algorithm based on the adaptive neuro-fuzzy inference system（ ANFIS） and PID controller was proposed. Firstly,in the Matlab/Simulink environment,the simulation model of the control algorithm of rail pressure was established by using the adaptive neural fuzzy PID controller,and the simulation was compared with the conventional PID control. Secondly,the fluctuation curve of the common-rail pressure was monitored by experiment,the control effect of the two control methods under the two kinds of transition conditions of starting and accelerating was observed. The results indicate that the steady state,dynamic characteristics and the adaptive neural fuzzy PID control are obviously better than those of conventional PID control. At the same time,under the two transition conditions of starting and accelerating,the fluctuation range of common-rail pressure is small,meeting the requirement of common-rail pressure stability in practical application.

关 键 词：高压共轨 共轨压力 自适应神经模糊推理系统 PID控制 稳定性 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置] TK421.44[自动化与计算机技术—控制科学与工程]