Heuristic and deep reinforcement learning-based PID control of trajectory tracking in a ball-and-plate system
The manual tuning of controller parameters, for example, tuning proportional integral derivative (PID) gains often relies on tedious human engineering. To curb the aforementioned problem, we propose an artificial intelligence-based deep reinforcement learning (RL) PID controller (three variants) com...
Main Authors: | Emmanuel Okafor, Daniel Udekwe, Yusuf Ibrahim, Muhammed Bashir Mu'azu, Ekene Gabriel Okafor |
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Format: | Article |
Language: | English |
Published: |
Taylor & Francis Group
2021-04-01
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Series: | Journal of Information and Telecommunication |
Subjects: | |
Online Access: | http://dx.doi.org/10.1080/24751839.2020.1833137 |
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