An Online Auto-Tuning Method for PID Controllers Based on Back Propagation Neural Network

The performance of the servo system is typically compromised by factors including internal characteristic changes, variations in load, and external disturbances. As a result, pre-set control parameters could fail to attain the intended optimal performance. To address this issue, this paper proposes an auto-tuning method for PID controller parameters utilizing Back Propagation Neural Network (BPNN) to enable on-line parameter adjustments in servo control systems. The experimental findings validate the efficacy of the proposed method, underscoring significant enhancements in both the robustness and overall performance of the servo controller system.