• Proceedings of the Korean Society of Precision Engineering Conference
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• 1992.04a
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• pp.385-389
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• 1992

The position control of the electro-hydraulic servo indexing system in a flexible forging machine was investigated. The role of an Electro-hydraulic servoindexing system is to rotate a workpiect fast and accurately to a desired position. Since the inertia of a workpiece changes during each forging step, an adapt control scheme could be adopted to the position control of the workpiece. A generalized predictive control method which depends on predicting the plant output over several steps ahead based on the assumption about future control actions is proposed. The perormance of the proposed GPC algorithm is investigated experimentally and compared with that of PID control. Experimental results show that the proposed GPC algorithm is satisfactory for the position control of the workpiece of an electrohydraulic indexing system.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.1
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• pp.95-100
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• 2021

This paper introduces model-based meta reinforcement learning as a control for the manipulator of an underwater construction robot. Model-based meta reinforcement learning updates the model fast using recent experience in a real application and transfers the model to model predictive control which computes control inputs of the manipulator to reach the target position. The simulation environment for model-based meta reinforcement learning is established using MuJoCo and Gazebo. The real environment of manipulator control for underwater construction robot is set to deal with model uncertainties.