Reinforcement Learning Compensation based PD Control for Inverted Pendulum

Guillermo Puriel-Gil, Wen Yu, Humberto Sossa

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11 Citas (Scopus)

Resumen

In this paper, we present a Control Algorithm based on Reinforcement Learning for an inverted pendulum. By implementing the Q-Learning techniques in the PD control scheme, the pendulum is enabled to improve its online performance and adapt to changes in the parameters of the pendulum model. In a first step, Q-Learning is used so that the control can balance the pendulum towards its inverted vertical position; In a second step, we combine hybrid techniques of Q-Learning and PD control. With this combination, we can bring the pendulum to its inverted vertical position, regardless of the applied disturbance. Finally, the results of the simulation show the effectiveness of the proposed controller.

Idioma originalInglés
Título de la publicación alojada2018 15th International Conference on Electrical Engineering, Computing Science and Automatic Control, CCE 2018
EditorialInstitute of Electrical and Electronics Engineers Inc.
ISBN (versión digital)9781538670323
DOI
EstadoPublicada - 13 nov. 2018
Publicado de forma externa
Evento15th International Conference on Electrical Engineering, Computing Science and Automatic Control, CCE 2018 - Mexico City, México
Duración: 5 sep. 20187 sep. 2018

Serie de la publicación

Nombre2018 15th International Conference on Electrical Engineering, Computing Science and Automatic Control, CCE 2018

Conferencia

Conferencia15th International Conference on Electrical Engineering, Computing Science and Automatic Control, CCE 2018
País/TerritorioMéxico
CiudadMexico City
Período5/09/187/09/18

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