Title
Predictive Control of a Robot Manipulator with Deep Reinforcement Learning
Date Issued
23 April 2021
Access level
metadata only access
Resource Type
conference proceedings
Publisher(s)
Institute of Electrical and Electronics Engineers Inc.
Abstract
This paper tackles the problem of trajectory following of a two-link rigid robot manipulator. The proposed controller bases its operation on the idea behind preview control in which the control law is divided in two parts: a feedback component that depends only on the present state of the system, and a predictive component that only uses future values of the reference trajectory. In this sense, the designed controller uses for training and control both present and future states of the system. Simulation results when following a test trajectory are presented to validate the proposed method and to show that the proposed controller exhibits better performance with respect to a neurocontroller that does not use a predictive component neither for training nor control.
Start page
127
End page
130
Language
English
OCDE Knowledge area
Sistemas de automatización, Sistemas de control
Scopus EID
2-s2.0-85114465885
ISBN
9781665449861
Source
2021 7th International Conference on Control, Automation and Robotics, ICCAR 2021
Resource of which it is part
2021 7th International Conference on Control, Automation and Robotics, ICCAR 2021
Sources of information: Directorio de Producción Científica Scopus