Comparison of Reinforcement Learning and Model Predictive Control for Automated Generation of Optimal Control for Dynamic Systems within a Design Space Exploration Framework
This work provides a study of methods for the automated derivation of control strategies for over-actuated systems. For this purpose, Reinforcement Learning (RL) and Model Predictive Control (MPC) approximating the solution of the Optimal Control Problem (OCP) are compared using the example of an ov...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Society of Automotive Engineers of Japan, Inc.
2024-01-01
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| Series: | International Journal of Automotive Engineering |
| Online Access: | https://www.jstage.jst.go.jp/article/jsaeijae/15/1/15_20244099/_article/-char/ja |