吉林大学学报(工学版) ›› 2020, Vol. 50 ›› Issue (1): 77-83.doi: 10.13229/j.cnki.jdxbgxb20190114

• 车辆工程·机械工程 • 上一篇    下一篇

熔融沉积成型技术3D打印机加热系统的模糊自适应PID控制

曲兴田(),王学旭,孙慧超(),张昆,闫龙威,王宏一   

  1. 吉林大学 机械与航空航天工程学院,长春 130022
  • 收稿日期:2019-02-16 出版日期:2020-01-01 发布日期:2020-02-06
  • 通讯作者: 孙慧超 E-mail:quxt@jlu.edu.cn;sunhc@jlu.edu.cn
  • 作者简介:曲兴田(1962-),男,教授,博士生导师.研究方向:先进制造技术.E-mail:quxt@jlu.edu.cn
  • 基金资助:
    吉林省教育厅“十三五”科学技术项目(JJKH20180082KJ)

Fuzzy self⁃adaptive PID control for fused deposition modeling 3D printer heating system

Xing-tian QU(),Xue-xu WANG,Hui-chao SUN(),Kun ZHANG,Long-wei YAN,Hong-yi WANG   

  1. College of Mechanical and Aerospace Engineering, Jilin University, Changchun 130022, China
  • Received:2019-02-16 Online:2020-01-01 Published:2020-02-06
  • Contact: Hui-chao SUN E-mail:quxt@jlu.edu.cn;sunhc@jlu.edu.cn

摘要:

在熔融沉积成型技术(FDM)3D打印过程中,需要对打印喷头和打印平台加热床进行加热,直到打印材料所需的温度才能开始打印,由于加热系统存在的时间滞后性和稳定性差的缺点,使加热过程既耗时又浪费能源。针对以上问题,采用模糊自适应PID控制方法控制打印喷头和打印平台加热床加热过程,并建立了控制系统Matlab/Simulink仿真模型。仿真结果表明,模糊自适应PID控制方法对FDM 3D打印机加热系统的控制效果优于传统PID控制方法,具有超调量小、响应速度快、控制效果更稳定的优势。

关键词: 自动控制技术, 3D打印, 模糊PID, 温度控制, 仿真模型

Abstract:

In the process of FDM 3D printing, it is necessary to heat the printing nozzle and the heating bed of the printing platform until the required temperature of the printing material is reached. The heating process is time-consuming and energy-wasting due to the time lag and poor stability of the heating system. In order to solve the above problems, the paper adopts the fuzzy self-adaptive PID control method to control the heating process of the printing nozzle and the heating bed of the printing platform, and establishes the Matlab/Simulink simulation model of the control system. The simulation results show that the control effect of the fuzzy self-adaptive PID control method on the heating system of FDM 3D printer is better than that of the traditional PID control method. It has the advantages of small overshoot, fast response and more stable control effect.

Key words: automatic control technology, 3D printing, fuzzy PID, temperature control, simulation model

中图分类号: 

  • TP18

图1

FDM 3D打印过程原理"

图2

模糊自适应PID控制系统结构原理图"

表1

变量模糊论域明细"

变量名称 模糊论域
e [-3,3]
ec [-3,3]
? K P [-0.3,0.3]
? K I [-0.06,0.06]
? K D [-3,3]

图3

输入变量e隶属度函数"

图4

输入变量ec隶属度函数"

图5

输出变量 ? K P 隶属度函数"

图6

输出变量 ? K I 隶属度函数"

图7

输出变量 ? K D 隶属度函数"

表2

变量ΔK P 模糊规则"

ec
NB NM NS ZO PS PM PB
e NB PB PB PM PM PS ZO ZO
NM PB PB PM PS PS ZO NS
NS PM PM PM PS ZO NS NS
ZO PM PM PS ZO NS NM NM
PS PS PS ZO NS NS NM NM
PM PS ZO NS NM NM NM NB
PB ZO ZO NM NM NM NB NB

表3

变量ΔK I 模糊规则"

ec
NB NM NS ZO PS PM PB
e NB NB NB NM NM NS ZO ZO
NM NB NB NM NS NS ZO ZO
NS NB NM NS NS ZO PS PS
ZO NM NM NS ZO PS PM PM
PS NM NS ZO PS PS PM PB
PM ZO ZO PS PS PM PB PB
PB ZO ZO PS PM PM PB PB

表4

变量ΔK D 模糊规则"

ec
NB NM NS ZO PS PM PB
NB PS NS NB NB NB NM PS
e NM PS NS NB NM NM NS ZO
NS ZO NS NM NM NS NS ZO
ZO ZO NS NS NS NS NS ZO
PS ZO ZO ZO ZO ZO ZO ZO
PM PB PS PS PS PS PS PB
PB PB PM PM PM PS PS PB

图8

? K P 输出曲面图"

图9

? K I 输出曲面图"

图10

? K D 输出曲面图"

图11

加热系统模型"

图12

模糊自适应PID模型系统仿真图"

图13

温度控制过程仿真曲线"

图14

温度控制过程误差曲线"

1 Berman B .3-D printing: the new industrial revolution[J]. Business Horizons, 2012, 55(2): 155-162.
2 申玄伟 . 熔融沉积成型3D打印中翘曲变形的仿真分析与状态识别方法研究[D]. 杭州:浙江大学机械工程学院, 2018.
Shen Xuan-wei . Research on simulation analysis and condition recognition technique of warp deformation in FDM 3D printing[D]. Hangzhou:School of Mechanical Engineering, Zhejiang University,2018.
3 Xu Y , Zheng Y , Du Y , et al . Adaptive condition predictive-fuzzy PID optimal control of start-up process for pumped storage unit at low head area[J]. Energy Conversion and Management, 2018, 177: 592-604.
4 Guo X , Wang J , Liao F , et al . Neuroadaptive quantized PID sliding‐mode control for heterogeneous vehicular platoon with unknown actuator deadzone[J]. International Journal of Robust and Nonlinear Control, 2019, 29(1): 188-208.
5 Gaidhane P J , Nigam M J , Kumar A , et al . Design of interval type-2 fuzzy precompensated PID controller applied to two-DOF robotic manipulator with variable payload[J]. ISA Transactions, 2019, 89: 169-185.
6 刘晓峰 . 覆带起重机起升系统双马达同步控制技术研究[D]. 长春:吉林大学机械科学与工程学院, 2012.
Liu Xiao-feng . Research on synchronous control technology of dual-motor in crawler crane lifting system[D]. Changchun: College of Mechanical Science and Engineering, Jilin University, 2012.
7 李静, 余春贤 . 基于模糊与PID的车辆底盘集成控制系统[J]. 吉林大学学报:工学版, 2013, 43(增刊1): 509-513.
Li Jing , Yu Chun-xian . Vehicle chassis integrated control system based on fuzzy and PID[J]. Journal of Jilin University (Engineering and Technology Edition), 2013, 43(Sup.1): 509-513.
8 曹婧华, 孔繁森, 冉彦中, 等 . 基于模糊自适应PID控制的空压机背压控制器设计[J]. 吉林大学学报:工学版, 2018, 48(3): 781-786.
Cao Jing-hua , Kong Fan-sen , Ran Yan-zhong ,et al . Back pressure controller design of air compressor based on fuzzy self-adaptive PID control[J]. Journal of Jilin University (Engineering and Technology Edition), 2018, 48(3): 781-786.
9 Chehadeh M S , Boiko I . Design of rules for in-flight non-parametric tuning of PID controllers for unmanned aerial vehicles[J]. Journal of the Franklin Institute, 2019, 356(1): 474-491.
10 Wang J , Yang G . Data-driven approach to accommodating multiple simultaneous sensor faults in variable-gain PID systems[J]. IEEE Transactions on Industrial Electronics, 2019, 66(4): 3117-3126.
11 Sahoo B P , Panda S . Improved grey wolf optimization technique for fuzzy aided PID controller design for power system frequency control[J]. Sustainable Energy, Grids and Networks, 2018, 16: 278-299.
12 Bakhtiari-Shahri M , Moeenfard H . Optimal design of a stable fuzzy controller for beyond pull-in stabilization of electrostatically actuated circular micro-plates[J]. Journal of Vibration and Acoustics, 2018, 141(1): No.011019.
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