Hydraulic system modeling through memory-based learning

Krishna, Murali; Bares, John

doi:10.1109/iros.1998.724848

Cited by 9 publications

(9 citation statements)

References 7 publications

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“…[1], [2], [15]) but often cannot be processed with requisite speed when they must run much faster than real-time. Several factors contribute to the difficulty of modeling this system.…”

Section: Actuator Modelsmentioning

confidence: 99%

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State of the Art in Automation of Earthmoving

Singh

1997

J. Aerosp. Eng.

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“…[1], [2], [15]) but often cannot be processed with requisite speed when they must run much faster than real-time. Several factors contribute to the difficulty of modeling this system.…”

Section: Actuator Modelsmentioning

confidence: 99%

“…While motion between any two points in space can be optimized in an offline fashion [15], it is important to be able to plan motion of an earthmover in free space online and preferably in an adaptive fashion that compensates for changing characteristics of the actuators over long periods of time.…”

Section: Free-space Motion Controlmentioning

confidence: 99%

State of the Art in Automation of Earthmoving

Singh

1997

J. Aerosp. Eng.

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“…For excavator manipulators, the drive forces or torques are produced by hydraulic systems including pumps, valves, and cylinders [18,25,49]. Therefore, modeling and simulation of hydraulic systems comprise an important component for the design and analysis of an excavator manipulator system.…”

Section: Hydraulic System Modelingmentioning

confidence: 99%

A Review on Mechanical and Hydraulic System Modeling of Excavator Manipulator System

Yoon

2016

Journal of Construction Engineering

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A recent trend in the development of off-highway construction equipment, such as excavators, is to use a system model for model-based system design in a virtual environment. Also, control system design for advanced excavation systems, such as automatic excavators and hybrid excavators, requires system models in order to design and simulate the control systems. Therefore, modeling of an excavator is an important first step toward the development of advanced excavators. This paper reviews results of recent studies on the modeling of mechanical and hydraulic subsystems for the simulation, design, and control development of excavator systems. Kinematic and dynamic modeling efforts are reviewed first. Then, various approaches in the hydraulic system modeling are presented.

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“…Many institutes and universities, including DLR (Germany) and Georgia Tech (USA), are presenting the automation methods for repetitive work using electrohydraulic and autonomous excavation [3,4].…”

Section: Introductionmentioning

confidence: 99%

Autonomous Traction Control for the Intelligent Excavator System

Im¹,

Choi²,

Lee³

2011

28th International Symposium on Automation and Robotics in Construction (ISARC 2011)

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ABSTRACT:With the recent development of information technology (IT), automation is being introduced in the construction sites as well as in plants. This study was conducted to address autonomous driving in the outside environment as part of the construction automation task in the advanced fusion construction research project of the Ministry of Land, Transport, and Maritime Affairs. The DGPS and IMU sensor were used to acquire the position and posture information of the excavator in the outside environment, and the information was used to create and follow diverse movement trajectories and to ensure smooth autonomous excavation. For autonomous driving, a vehicle-type control device, which was named remote control station (RCS), and an excavator attribute-sensing module, which was mounted on the excavator, were developed. The excavator attribute-sensing module was mounted on the electrohydraulic excavator, which allowed the wireless communication of the excavator state between the excavator and the mobile control station and autonomous driving. The path-tracking and posture control algorithm for the excavator that had no additional steering system for the outside environment, which was proposed in this study, significantly differs from that of the conventional and general mobile platform in the inside/outside environment. The precision and reliability of the proposed autonomous control algorithm was verified via diverse tests in the actual environment.

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Hydraulic system modeling through memory-based learning

Cited by 9 publications

References 7 publications

State of the Art in Automation of Earthmoving

State of the Art in Automation of Earthmoving

A Review on Mechanical and Hydraulic System Modeling of Excavator Manipulator System

Autonomous Traction Control for the Intelligent Excavator System

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