{"title":"Design and Control of a Macro–Micromanipulator Using Macrofiber Composite","authors":"Chen Wang;Yiling Yang;Yuguo Cui;Gaohua Wu;Yanding Wei","doi":"10.1109/TIE.2024.3525114","DOIUrl":null,"url":null,"abstract":"This article presents the structural design, dynamics modeling, and precision control of a new macro–micromanipulator driven by macrofiber composite (MFC). In particular, the stick–slip platform has a high single-step rotation angle, and its fallback inhibition with a single-actuator configuration is proposed. Also, wide-range trajectory tracking with continuous stick–slip motion is realized. First, the macro–micromanipulator is devised using a stick–slip platform and a micromanipulator. Then, a system dynamics model is developed to describe multifactor coupling and macro–microinteractions. A quick-reaching and filtered discrete sliding mode (QFDSM) control is proposed, in which a new convergence law and a low-pass filter are designed to approach fast, smooth control voltage, and avoid chattering. Thus, a macromotion composite control with QFDSM is developed. Experiments show that the stick–slip platform has a high single-step output of 8.02 mrad, a vertical load of 120 N, and a maximum speed of 730 mrad/s. The fallback rate is reduced from 56.1% to 12.2% with the inhibition beam and further decreased to 4.5% by combining macro–microcomposite control. Meanwhile, microscopic vibration suppression and precision wide-range trajectory tracking are realized. Experiments verified the performance of the macro–micromanipulator.","PeriodicalId":13402,"journal":{"name":"IEEE Transactions on Industrial Electronics","volume":"72 8","pages":"8365-8375"},"PeriodicalIF":7.2000,"publicationDate":"2025-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Industrial Electronics","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10841843/","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
This article presents the structural design, dynamics modeling, and precision control of a new macro–micromanipulator driven by macrofiber composite (MFC). In particular, the stick–slip platform has a high single-step rotation angle, and its fallback inhibition with a single-actuator configuration is proposed. Also, wide-range trajectory tracking with continuous stick–slip motion is realized. First, the macro–micromanipulator is devised using a stick–slip platform and a micromanipulator. Then, a system dynamics model is developed to describe multifactor coupling and macro–microinteractions. A quick-reaching and filtered discrete sliding mode (QFDSM) control is proposed, in which a new convergence law and a low-pass filter are designed to approach fast, smooth control voltage, and avoid chattering. Thus, a macromotion composite control with QFDSM is developed. Experiments show that the stick–slip platform has a high single-step output of 8.02 mrad, a vertical load of 120 N, and a maximum speed of 730 mrad/s. The fallback rate is reduced from 56.1% to 12.2% with the inhibition beam and further decreased to 4.5% by combining macro–microcomposite control. Meanwhile, microscopic vibration suppression and precision wide-range trajectory tracking are realized. Experiments verified the performance of the macro–micromanipulator.
期刊介绍:
Journal Name: IEEE Transactions on Industrial Electronics
Publication Frequency: Monthly
Scope:
The scope of IEEE Transactions on Industrial Electronics encompasses the following areas:
Applications of electronics, controls, and communications in industrial and manufacturing systems and processes.
Power electronics and drive control techniques.
System control and signal processing.
Fault detection and diagnosis.
Power systems.
Instrumentation, measurement, and testing.
Modeling and simulation.
Motion control.
Robotics.
Sensors and actuators.
Implementation of neural networks, fuzzy logic, and artificial intelligence in industrial systems.
Factory automation.
Communication and computer networks.