Contouring accuracy improvement using a tangential contouring controller with a fuzzy logic-based feedrate regulator

被引:4
作者
Ming-Yang Cheng
Ke-Han Su
机构
[1] National Cheng Kung University,Department of Electrical Engineering
来源
The International Journal of Advanced Manufacturing Technology | 2009年 / 41卷
关键词
Tangential contouring controller (TCC); Fuzzy logic; Contour error; Feedrate regulator;
D O I
暂无
中图分类号
学科分类号
摘要
In contour-following tasks, contour error reduction is an issue of much concern. Generally speaking, contour error is caused by the mismatched dynamics between each axis. To reduce the contour error, many previous studies have focused on developing proper controllers and/or more accurate contour error estimation algorithms. An alternative method for reducing contour errors is to exploit the idea of desired feedrate adjustment. This paper proposes using the approximate contour error information to develop a fuzzy logic-based feedrate regulator, which adjusts the value of the desired feedrate. Moreover, to further reduce contour error, an integrated motion control scheme is also developed. This scheme consists of a position loop controller with velocity command feedforward, a tangential contouring controller (TCC), a real-time contour error estimator, and the proposed fuzzy logic-based feedrate regulator. Several experiments on free-form contour-following tasks are conducted to evaluate the performance of the proposed approach. The experimental results clearly demonstrate the effectiveness of the proposed approach.
引用
收藏
页码:75 / 85
页数:10
相关论文
共 50 条
[21]   Fuzzy Logic-Based Target Classification Using Kinematic Data [J].
Fernandes, Mateus de Araujo ;
Oliveira, Hallysson ;
Kienitz, Karl Heinz .
CYBERNETICS AND SYSTEMS, 2011, 42 (06) :430-446
[22]   Fuzzy logic-based performance improvement on MAC layer in wireless local area networks [J].
Kocak, Cemal ;
Karakurt, Haci Bayram .
NEURAL COMPUTING & APPLICATIONS, 2019, 31 (10) :6113-6128
[23]   Fuzzy logic-based performance improvement on MAC layer in wireless local area networks [J].
Cemal Kocak ;
Hacı Bayram Karakurt .
Neural Computing and Applications, 2019, 31 :6113-6128
[24]   Fuzzy Logic-Based Flood Detection System Using Lora Technology [J].
Khuen, Choo Kam ;
Zourmand, Alireza .
2020 16TH IEEE INTERNATIONAL COLLOQUIUM ON SIGNAL PROCESSING & ITS APPLICATIONS (CSPA 2020), 2020, :40-45
[25]   DYNAMIC BEHAVIOR IMPROVEMENT OF INDUCTION HEATING CONVERTERS USING FUZZY LOGIC CONTROLLER [J].
Kumar, Anand ;
Raman, Rahul ;
Sadhu, Pradip Kumar .
REVUE ROUMAINE DES SCIENCES TECHNIQUES-SERIE ELECTROTECHNIQUE ET ENERGETIQUE, 2019, 64 (02) :163-168
[26]   Fuel economy improvement for fuel cell hybrid electric vehicles using fuzzy logic-based power distribution control [J].
Ahn, H.-S. ;
Lee, N. S. ;
Moon, C. W. ;
Jeong, G.-M. .
INTERNATIONAL JOURNAL OF AUTOMOTIVE TECHNOLOGY, 2007, 8 (05) :651-658
[27]   A new fuzzy logic-based controller design method for DC and AC impressed-voltage drives [J].
Cupertino, F ;
Lattanzi, A ;
Salvatore, L .
IEEE TRANSACTIONS ON POWER ELECTRONICS, 2000, 15 (06) :974-982
[28]   Design of Fuzzy Logic-Based Dynamic Droop Controller of Wind Turbine System for Primary Frequency Support [J].
Bubshait, Abdullah ;
Simoes, Marcelo Godoy .
2018 IEEE INDUSTRY APPLICATIONS SOCIETY ANNUAL MEETING (IAS), 2018,
[29]   Fuzzy logic-based incident detection system using loop detectors data [J].
Rossi, Riccardo ;
Gastaldi, Massimiliano ;
Gecchele, Gregorio ;
Barbaro, Valeria .
18TH EURO WORKING GROUP ON TRANSPORTATION, EWGT 2015, 2015, 10 :266-275
[30]   A Fuzzy Logic-Based Stock Market Trading Algorithm Using Bollinger Bands [J].
Lauguico, Sandy ;
Concepcion, Ronnie, II ;
Alejandrino, Jonnel ;
Macasaet, Dailyne ;
Tobias, Rogelio Ruzcko ;
Bandala, Argel ;
Dadios, Elmer .
2019 IEEE 11TH INTERNATIONAL CONFERENCE ON HUMANOID, NANOTECHNOLOGY, INFORMATION TECHNOLOGY, COMMUNICATION AND CONTROL, ENVIRONMENT, AND MANAGEMENT (HNICEM), 2019,