Fuzzy-PID-Based Improvement Controller for CNC Feed Servo System

被引：0
作者：
Nguyen Huu Cuong [1 ]
Trung Trong Nguyen [2 ]
Tran Viet Thang [2 ]
机构：
[1] Can Tho Univ, Can Tho, Vietnam
[2] Vietnam Res Inst Elect Informat & Automat, Hanoi, Vietnam
来源：
INTELLIGENT HUMAN COMPUTER INTERACTION, IHCI 2020, PT II | 2021年 / 12616卷
关键词：
Fuzzy PID controller; Fuzzy logic controller; CNC machine tool; Feed servo system;
D O I：
10.1007/978-3-030-68452-5_4
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The feed servo system is one of the most important mechatronics parts in CNC machine tools. However, it is very difficult to model its control system accurately because of time-varying parameters in continuous-time nonlinear system and load disturbances. This paper introduces the control methods on feed servo system aimed to promote higher precision for CNC milling machine. The main objective of our research is focus on the improvement of Fuzzy PID (FPID) controller applied to feed servo system of CNC milling machine. The performances between the developed FPID controller and conventional PID controller have been compared and evaluated on MATLAB/SIMULINK simulation. The simulation results of AC servo system with the FPID controller show that this control method not only has more robustness but also has a better adaptation capability. Furthermore, the proposed control method has been tested in the TI developed board with one horsepower Yaskawa AC servo motor. The experimental results demonstrate that the accuracy of the motion precision of CNC milling machine's axis using the proposed control system with one horsepower AC motor can achieve about 8-10 mu m.
引用
收藏
页码：38 / 46
页数：9
相关论文
共 50 条
[31]   Research of Secondary Constant Pressure Water Supply system based on Fuzzy-PID Controller [J].
Wu, Jie ;
Lu, Minggang .
2017 IEEE 3RD INFORMATION TECHNOLOGY AND MECHATRONICS ENGINEERING CONFERENCE (ITOEC), 2017, :462-465
[32]   An Optimal Fuzzy PID Controller Design Based on Conventional PID Control and Nonlinear Factors [J].
Chao, Chun-Tang ;
Sutarna, Nana ;
Chiou, Juing-Shian ;
Wang, Chi-Jo .
APPLIED SCIENCES-BASEL, 2019, 9 (06)
[33]   Fault prediction of the CNC machine tool servo system based on the BRB [J].
Zhang, Bangcheng ;
Yin, Xiaojing ;
Wang, Yilong ;
Zhang, Bing ;
Zhou, Zhijie .
PROCEEDINGS OF 2014 PROGNOSTICS AND SYSTEM HEALTH MANAGEMENT CONFERENCE (PHM-2014 HUNAN), 2014, :145-148
[34]   Comparison of PID and FUZZY Controller in the Cascade Tank System in Matlab/Simulink [J].
Bayir, R. ;
Ertunc, H. M. ;
Demir, H. .
INTELLIGENT TECHNOLOGIES IN LOGISTICS AND MECHATRONICS SYSTEMS, ITELMS 2013, 2013, :50-54
[35]   Fuzzy PID Controller Design and Implement in Ball-Beam System [J].
Wu Yuanyuan ;
Liu Yongxin .
2015 34TH CHINESE CONTROL CONFERENCE (CCC), 2015, :3613-3616
[36]   Design of Improved Fuzzy PID Controller Based on the Temperature Control System of Large Inertia and Time Delay [J].
Wang, Longkui ;
Li, HongXin ;
Wang, Yaru .
PRACTICAL APPLICATIONS OF INTELLIGENT SYSTEMS, ISKE 2013, 2014, 279 :775-783
[37]   Auto-tuning Method of Fuzzy PID Controller Parameter Based on Self-learning System [J].
Yang, Zhangli ;
Li, Lei ;
Liu, Buqing .
2014 11TH INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS AND KNOWLEDGE DISCOVERY (FSKD), 2014, :222-226
[38]   RESEARCH ON FUZZY SELF-REGULATING PID CONTROLLER FOR SRM SPEED SYSTEM BASED ON PSO ALGORITHM [J].
Sun, Hui-Qin ;
Du, Yun ;
Zhu, Wei-Lu ;
Wang, Su-Zhi .
PROCEEDINGS OF 2013 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS (ICMLC), VOLS 1-4, 2013, :1363-1367
[39]   Research of Network Pressure-superposed Water Supply System Based on Fuzzy-PID Controller [J].
Li Hongfeng ;
Chen Zhenfei ;
Chen Wei .
2009 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND BIOMIMETICS (ROBIO 2009), VOLS 1-4, 2009, :1194-+
[40]   Optimal fuzzy PID controller design of an active magnetic bearing system based on adaptive genetic algorithms [J].
Chen, Hung-Cheng .
PROCEEDINGS OF 2008 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-7, 2008, :2054-2060
12345