Precise control of a four degree-of-freedom permanent magnet biased active magnetic bearing system in a magnetically suspended direct-driven spindle using neural network inverse scheme. (1st May 2017)

• Record Type: Journal Article
• Authors: Sun, Xiaodong; Su, Bokai; Chen, Long; Yang, Zebin; Xu, Xing; Shi, Zhou
• Is Part Of: Mechanical systems and signal processing. Volume 88(2017)
• Page Start: 36
• Page End: 48
• Publication Date: 2017-05-01
• Subjects: Magnetic bearing -- Neural network inverse -- Decoupling control -- Internal model control -- Magnetically suspended direct-driven spindle; Structural dynamics -- Periodicals; Vibration -- Periodicals; Constructions -- Dynamique -- Périodiques; Vibration -- Périodiques; Structural dynamics; Vibration; Periodicals; 621
• DOI: 10.1016/j.ymssp.2016.11.022
• Languages: English
• ISSNs: 0888-3270

Abstract

Abstract: The capacity of improving the control accuracy and dynamic performance of a four degree-of-freedom (DOF) permanent magnet biased active magnetic bearing (PMBAMB) system is critical to developing and maintaining a high precision application in a magnetically suspended direct-driven spindle system. The 4-DOF PMBAMB system, however, is a multivariable, strong coupled and nonlinear system with unavoidable and unmeasured external disturbances, in addition to having parameter variations. The satisfactory control performance cannot be obtained by using traditional strategies. Therefore, it is important to present a novel control scheme to construct a robust controller with good closed-loop capability. This paper proposes a new decoupling control scheme for a 4-DOF PMBAMB in a direct-driven spindle system based on the neural network inverse (NNI) and 2- degree-of-freedom (DOF) internal model control method. By combining the inversion of the 4-DOF PMBAMB system with its original system, a new pseudolinear system can be developed. In addition, by introducing the 2-DOF internal model controller into the pseudolinear system to design extra closed-loop controllers, we can effectively eliminate the influence of the unmodeled dynamics to the decoupling control accuracy, as well as adjust the properties of tracking and disturbance rejection independently. The experimental results demonstrate the effectiveness of the proposed control scheme. Highlights: A four degree-of-freedom permanent magnet biased active magnetic bearing (4-DOF PMBAMB) is nonlinear and coupled. Radial position control is of vital challenge and importance for a 4-DOF PMBAMB system. A decoupling control strategy based on neural network inverse (NNI) is presented. The 2-DOF internal model control theory is used to design extra closed-loop controllers. Good decoupling and robustness performances in different conditions are achieved.