An Enhanced Real-time Iterative Compensation Method for Fast Tool Servos with Resonance Suppression

• Published in: IEEE transactions on industrial electronics (1982) Vol. 71; no. 6; pp. 1 - 10
• Main Authors: Meng, Yixuan, Chen, ZaoZao, Huang, Wei-Wei, Zhang, XinQuan, Hu, Chuxiong, Zhu, LiMin
• Format: Journal Article
• Language: English
• Published: New York IEEE 01-06-2024; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Closed loop systems; Closed loops; Compensation; Control systems design; Disturbance observers; Fast tool servos (FTSs); Feedback control; Hysteresis; Iterative methods; Mathematical models; Prediction models; Predictive models; Real time; real-time iterative compensation; Real-time systems; Resonance; resonance suppression; Stability analysis; Tracking errors; Trajectory
• ISSN: 0278-0046; 1557-9948
• DOI: 10.1109/TIE.2023.3294632

Excellent tracking accuracy and remarkable disturbance rejection capability are quite important for fast tool servo (FTS) operations in ultraprecision manufacturing. For these purposes, this article proposes an enhanced real-time iterative compensation (ERIC) method with resonance suppression for the FTS system. The dual-loop controller is first designed and optimized to damp the high-frequency resonance and increase the control bandwidth of the FTS system. Then, a disturbance observer is employed to eliminate the impact of various unmodeled disturbances including the nonlinear hysteretic disturbance. Finally, a linear error prediction model is constructed based on only the past and current states of the closed-loop system during the real-time tracking. The predicted tracking error is utilized for online iterative compensation via reference input modification. It is also analyzed and verified that the stability and tracking error convergence of the ERIC can be guaranteed with an appropriate compensation gain in theory. Various experiments are performed on an FTS prototype, and the results demonstrate the exceptional benefits of the proposed ERIC method. The root-mean-squared errors are all less than 0.1% for experiments with trajectory variations or large external disturbances. Also, the ERIC is applicable for the tracking of real-time generated trajectories, which is crucial for FTS operations.