This study proposes a method for designing an adaptive PID controller based on deep reinforcement learning, which can automatically adjust PID parameters in complex and changing control environments to achieve better control performance. We validate the effectiveness of this method in different applications through simulations and experiments, demonstrating its wide potential in automation control.
Design of Adaptive PID Controller Based on Deep Reinforcement Learning
2023-10-11
2847476 byte
Conference paper
Electronic Resource
English
Deep reinforcement learning based path tracking controller for autonomous vehicle
SAGE Publications | 2021
|Adaptive PID Controller based on Reinforcement Learning for Wind Turbine Control
BASE | 2008
|Adaptive traffic light control method based on deep reinforcement learning
European Patent Office | 2023
|