Model-free Active Disturbance Rejection Control of Two-dimensional Linear Motor Based on Multi-parameter Genetic Optimization

被引：1

作者：

Chang, Debiao ^{[1
]}

Cao, Rongmin ^{[1
]}

Hou, Zhongsheng ^{[2
]}

Jia, Jihui ^{[1
]}

Li, Yifan ^{[1
]}

机构：

[1] Beijing Informat Sci & Technol Univ, Sch Automat, Beijing 100192, Peoples R China

[2] Qingdao Univ, Coll Automat, Qingdao 266071, Peoples R China

来源：

2023 IEEE 12TH DATA DRIVEN CONTROL AND LEARNING SYSTEMS CONFERENCE, DDCLS | 2023年

基金：

中国国家自然科学基金; 北京市自然科学基金;

关键词：

Model-Free Adaptive Control; Active Disturbance Rejection Control; Genetic Algorithm; Parameter Tuning; Disturbance Compensation;

D O I：

10.1109/DDCLS58216.2023.10166983

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The position tracking accuracy of a two-dimensional linear motor is the most important accuracy index in the servo motion process of a two-dimensional linear motor, and it is of great significance to the servo motion process of two-dimensional linear motor modeling and control. Aiming at the problem that the complex dynamic characteristics of the two-dimensional linear motor are difficult to carry out conventional mechanism modeling and other disturbances such as friction impedance during its movement a compensation scheme founded on the combination of tight format dynamic linearization model-free adaptive control and active disturbance rejection control technology is proposed, according to the data-driven control idea. The scheme provides an idea for solving the problem of friction disturbance of two-dimensional linear motors. After establishing the mathematical model of a two-dimensional linear motor, the scheme uses Matlab to simulate the algorithm. Then, owing to the influence of many adjustable parameters on the performance of the controller, and the problems of time-consuming and unsatisfactory optimization of many parameters, the controller parameters are optimized based on a genetic algorithm to improve the efficiency of parameter tuning.

引用

页码：220 / 225

页数：6

共 15 条

[1]

Chen Qi, 2014, Electronics Optics & Control, V21, P20, DOI 10.3969/j.issn.1671-637X.2014.10.005

[2]

Chen XY, 2020, PROCEEDINGS OF 2020 IEEE 4TH INFORMATION TECHNOLOGY, NETWORKING, ELECTRONIC AND AUTOMATION CONTROL CONFERENCE (ITNEC 2020), P1273, DOI [10.1109/ITNEC48623.2020.9084730, 10.1109/itnec48623.2020.9084730]

[3] Active Disturbance Rejection Control for Nonaffined Globally Lipschitz Nonlinear Discrete-Time Systems [J].

Chi, Ronghu ;

Hui, Yu ;

Huang, Biao ;

Hou, Zhongsheng .

IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2021, 66 (12) :5955-5967

[4]

[冯增喜 Feng Zengxi], 2021, [控制工程, Control Engineering of China], V28, P766

[5]

[冯增喜 Feng Zengxi], 2016, [控制工程, Control Engineering of China], V23, P405

[6]

Fu L., 2022, COMPUTER SIMULATION, V39, P109

[7] Friction compensation in control valves: Nonlinear control and usual approaches [J].

Hidalgo, Matheus Cammarosano ;

Garcia, Claudio .

CONTROL ENGINEERING PRACTICE, 2017, 58 :42-53

[8]

Hou Z., 2014, Model Free Adaptive Control, Theory and Applications

[9]

Lin Weitian, 2020, DESIGN SYNCHRONOUS C

[10]

Liu Ao, 2021, RES FRICTION CHARACT

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