The Hardware-In-Loop simulation research on trajectory control and modeling parameter estimation of working device of hydraulic excavator

He, Jiping; Zhao, Xin; Zhang, Daqing; He, Qingbo

doi:10.1109/icma.2010.5588594

Cited by 2 publications

(1 citation statement)

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“…The time-optimal trajectories were planned. Cerebellar Model Articulation Controller (CMAC) + PID algorithm was adopted by Central South University to help excavator to be more accurate [10]. The trajectory control accuracy of bucket teeth can be accurate to 15 cm.…”

Section: Introductionmentioning

confidence: 99%

Research on Trajectory Planning and Autodig of Hydraulic Excavator

Zhang

Wang

Liu

et al. 2017

Mathematical Problems in Engineering

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As the advances in computer control technology keep emerging, robotic hydraulic excavator becomes imperative. It can improve excavation accuracy and greatly reduce the operator's labor intensity. The 12-ton backhoe bucket excavator has been utilized in this research work where this type of excavator is commonly used in engineering work. The kinematics model of operation device (boom, arm, bucket, and swing) in excavator is established in both Denavit-Hartenberg coordinates for easy programming and geometric space for avoiding blind spot. The control approach is based on trajectory tracing method with displacements and velocities feedbacks. The trajectory planning and autodig program is written by Visual C++. By setting the bucket teeth's trajectory, the program can automatically plan the velocity and acceleration of each hydraulic cylinder and motor. The results are displayed through a 3D entity simulation environment which can present real-time movements of excavator kinematics. Object-Oriented Graphics Rendering Engine and skeletal animation are used to give accurate parametric control and feedback. The simulation result shows that a stable linear autodig can be achieved. The errors between trajectory planning command and simulation model are analyzed.

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Section: Introductionmentioning

confidence: 99%