Deep RL Based Notch Filter Design Method for Complex Industrial Servo Systems

• Published in: International journal of control, automation, and systems Vol. 18; no. 12; pp. 2983 - 2992
• Main Authors: Oh, Tae-Ho, Han, Ji-Seok, Kim, Young-Seok, Yang, Dae-Young, Lee, Sang-Hoon, Cho, Dong-Il “Dan”
• Format: Journal Article
• Language: English
• Published: Bucheon / Seoul Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers 01.12.2020; Springer Nature B.V; 제어·로봇·시스템학회
• Subjects: Algorithms; Control; Control Theory and Applications; Design techniques; Engineering; Filter design (mathematics); Mechatronics; Motion control; Notch filters; Parameters; Robotics; Stability; System effectiveness; Tuning; Vibration mode; 제어계측공학; highly complex servo system; Deep reinforcement learning; resonance suppression; multiple notch filters
• DOI: 10.1007/s12555-020-0153-y
• ISSN: 1598-6446

This paper proposes a deep reinforcement learning (deep RL) method for simultaneously designing several notch filters in complex industrial servo systems. Notch filters are highly effective for suppressing resonances in motion control systems and are widely utilized in industry. However, severe limitations exist in complex servo systems because there are many vibration modes that are difficult to identify. In such cases, several notch filters must be used, but the task of tuning these filters involves lengthy empirical procedures by well-experienced engineers. To automate this tuning process, this paper proposes a novel design method that can design several notch filters simultaneously for the first time. In this method, a deep deterministic policy gradient (DDPG) algorithm with a vector stability margin as the reward function is utilized to find filter parameters in the frequency domain. The proposed method simultaneously finds a set of many parameters for several notch filters that are optimal with respect to stability. Using a real industrial servo system that has multiple resonances, it is demonstrated that the proposed method effectively finds the optimal parameters for several notch filters and successfully suppresses multiple resonances to provide desired performances.