.  Abstract

Energy-Aware Speed Regulation in Electrical Drives: A Load-Agnostic Motor Control Approach Via Reinforcement Learning

The paper introduces a novel design of a reinforcement learning agent. Compared to application-tuned classical control methods, the agent demonstrated advanced capability to save energy, showcasing its potential for future applications.

Authors: Klotz Steven, Buksch Thorsten, Infineon Technologies AG, Goswami Dip, Eindhoven University of Technology, Mueller-Gritschneder Daniel, TU Munich

Abstract

Machine Learning based Diagnostic Approach to Condition Monitoring of Railway Platform Screen Door Systems

by Şükrü Görgülü 1,

İsa Koç 2, Necim Kırımça 3, Ömer Mermer 4, Mehmet Karaköse 5, and Mehmet Tankut Özgen 6
(1,6 Dept. of Electrical and Electronics Engineering, Eskişehir Technical University, Türkiye; 2 Dept. of Electrical and Electronics Engineering, Eskişehir Osmangazi University, Türkiye; 5 Dept. of Computer Engineering, Elazığ Fırat University, Türkiye; 1,2,3,4 Albayrak Makine Elektronik San. Tic. A.Ş. Eskişehir, Türkiye)

March, 14th, 2023, 2PM – 6 PM

Class 8.1

An Introduction to TinyML: Bringing Deep Learning to Ultra-low-power Micro-Controllers

by Prof. Dr. Daniel Müller-Gritschneder, TU Munich