Yong Zhou;Ruqi Ding;Min Cheng;Liqiu Liao;Zheng Chen;Bin Yao
{"title":"Precision Motion Control of Independent Metering Hydraulic Swing System With Large Inertia Loads: A Case Study on a Rotary Drilling Rig","authors":"Yong Zhou;Ruqi Ding;Min Cheng;Liqiu Liao;Zheng Chen;Bin Yao","doi":"10.1109/TIE.2025.3549091","DOIUrl":null,"url":null,"abstract":"Electro-hydraulic systems are widely used in heavy machines to drive large inertia loads because of their high power-to-weight ratio and substantial force/torque outputs. Achieving both control accuracy and energy efficiency is critical for such systems to ensure construction quality and minimize costs. However, it is challenging to improve motion control accuracy of large inertia systems because of the extremely low system damping, nonlinearities, and uncertainties. Additionally, the high pressures and large flow rates required to actuate these loads further complicate the optimization of energy efficiency. In this article, the hydraulic swing system of a 105-ton rotary drilling rig is used as a case study to explore control strategies that address these issues. An independent metering system (IMS) is employed to enhance energy efficiency. Meanwhile, an adaptive robust controller (ARC) with working mode selection is developed to improve control accuracy. A damping optimization principle is proposed to adjust the system damping through feedback gains, enhancing both motion accuracy and system stability. Experimental results from two cases demonstrate that the proposed strategy achieves a position accuracy of 0.1<inline-formula><tex-math>${}^{\\circ}$</tex-math></inline-formula> and over 10% energy savings, meeting both accuracy and efficiency objectives.","PeriodicalId":13402,"journal":{"name":"IEEE Transactions on Industrial Electronics","volume":"72 10","pages":"10390-10400"},"PeriodicalIF":7.2000,"publicationDate":"2025-03-21","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/10934809/","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
Electro-hydraulic systems are widely used in heavy machines to drive large inertia loads because of their high power-to-weight ratio and substantial force/torque outputs. Achieving both control accuracy and energy efficiency is critical for such systems to ensure construction quality and minimize costs. However, it is challenging to improve motion control accuracy of large inertia systems because of the extremely low system damping, nonlinearities, and uncertainties. Additionally, the high pressures and large flow rates required to actuate these loads further complicate the optimization of energy efficiency. In this article, the hydraulic swing system of a 105-ton rotary drilling rig is used as a case study to explore control strategies that address these issues. An independent metering system (IMS) is employed to enhance energy efficiency. Meanwhile, an adaptive robust controller (ARC) with working mode selection is developed to improve control accuracy. A damping optimization principle is proposed to adjust the system damping through feedback gains, enhancing both motion accuracy and system stability. Experimental results from two cases demonstrate that the proposed strategy achieves a position accuracy of 0.1${}^{\circ}$ and over 10% energy savings, meeting both accuracy and efficiency objectives.
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.