Design of Adaptive PID Controller Based on Deep Reinforcement Learning

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.