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https://rinacional.tecnm.mx/jspui/handle/TecNM/4481| Título : | REINFORCEMENT LEARNING MODULE FOR PERSONALIZED ASSISTED PEDALING IN HUMAN-ELECTRIC HYBRID VEHICLES (PEDELEC) |
| Autor : | GARCIA REYES, CARLOS RICARDO TONATIUH |
| Fecha de publicación : | 2021-09-10 |
| Editorial : | Tecnológico Nacional de México |
| metadata.dc.publisher.tecnm: | Instituto Tecnológico de Chihuahua II |
| Descripción : | This document contains the complete research for a Reinforcement (RL) Learning Artificial Intelligence (IA) for the automatic control of a PEDE LEC power assistance module. The RL IA will use trial and error methods to determine the best available assistance for the PEDELEC rider using as reference the Torque produced at the crankshaft and the rider’s heartbeat at one second intervals. This data w ill be transformed into an RL Environment where an agent will learn from no previous experience how to increase or decrease the assistance level to maintain the rider’s heartbeat at a comfortable level. The implementation of the RL will use the principles of TD(0) control and SARSA Prediction to achieve the goal. |
| metadata.dc.type: | info:eu-repo/semantics/masterThesis |
| Aparece en las colecciones: | TESIS MAESTRIA EN SISTEMAS COMPUTACIONALES |
Ficheros en este ítem:
| Fichero | Descripción | Tamaño | Formato | |
|---|---|---|---|---|
| REINFORCEMENT LEARNING MODULE FOR PERSONALIZED ASSISTED PEDALING IN HUMAN-ELECTRIC HYBRID VEHICLES (PEDELEC).pdf | TEXTO COMPLETO | 3.94 MB | Adobe PDF | Visualizar/Abrir |
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