Vibration suppression of ball-screw drive system based on flexible dynamics model. (January 2023)

• Record Type: Journal Article
• Authors: Li, Lin; Zhang, Qiangwei; Zhang, Tie; Zou, Yanbiao
• Is Part Of: Engineering applications of artificial intelligence. Volume 117:Part A(2023)
• Publication Date: 2023-01
• Subjects: Flexible dynamics -- Parameter identification -- Particle swarm optimization -- Vibration suppression -- Input shaping; Engineering -- Data processing -- Periodicals; Artificial intelligence -- Periodicals; Expert systems (Computer science) -- Periodicals; Ingénierie -- Informatique -- Périodiques; Intelligence artificielle -- Périodiques; Systèmes experts (Informatique) -- Périodiques; Artificial intelligence; Engineering -- Data processing; Expert systems (Computer science); Periodicals; 620.00285
• DOI: 10.1016/j.engappai.2022.105506
• Languages: English
• ISSNs: 0952-1976

Abstract

Abstract: Aiming at the problem of residual vibration of the ball-screw drive system when it stops in high-speed motion, a vibration suppression method based on the flexible dynamics model is proposed. A simplified flexible dynamics model of the ball-screw system is developed using the Lagrange method and rewritten as a parametric identification equation containing only the motor's rotation angle. A Particle Swarm Optimization algorithm based on Recursive Least Square finite search space (RLS-PSO) is proposed for dynamic parameter identification and the results are used to design a coupled ZVD shaper to suppress residual vibration in the ball-screw drive system. The experimental results of model identification show that RLS-PSO is more accurate than WLS, PSO and GA, and the convergence speed is much higher compared to PSO and GA. The simplified dynamics model can reflect the dynamic characteristics of the system accurately. The results of the vibration experiments demonstrate the effectiveness of the input shaper designed using the identification results in suppressing residual vibration of the ball-screw drive system.