Closed-loop identification of multi-axis active magnetic bearing systems based on decentralized and decoupling control. (April 2023)

• Record Type: Journal Article
• Authors: Yeh, T.-J.; Huang, Chien-Chih; Toh, Chow-Shing
• Is Part Of: Mechatronics. Volume 90(2023)
• Publication Date: 2023-04
• Subjects: Multi-axis magnetic bearing systems -- Closed-loop identification -- Recursive estimation -- Positive-real condition; Computer integrated manufacturing systems -- Periodicals; Flexible manufacturing systems -- Periodicals; Mechatronics -- Periodicals; Productique -- Périodiques; Fabrication, Systèmes flexibles de -- Périodiques; Mécatronique -- Périodiques; Computer integrated manufacturing systems; Flexible manufacturing systems; Mechatronics; Periodicals; 629.89
• DOI: 10.1016/j.mechatronics.2022.102933
• Languages: English
• ISSNs: 0957-4158

Abstract

Abstract: In response to the open-loop instability of magnetic bearing systems, this paper develops a closed-loop identification method to obtain an accurate plant model for controller design. The identification method is based on a decentralized and decoupling control architecture, which allows the decoupling of the multi-input-multi-output (MIMO) system into two single-input-single-output (SISO) systems for simplifying the identification process. The identification uses a pseudo-random binary sequence as the excitation signal. A parameterized model is obtained through a parameter estimation algorithm based on the output error model. To ensure that the model prediction error can converge during the computation process, a filter is incorporated into the estimation algorithm. The filter can be synthesized systematically by solving a set of linear matrix inequalities. The performance of the proposed closed-loop identification method is firstly verified by simulations. Then it is implemented on a five-axis magnetic bearing platform and the parameterized model obtained from the identification is compared to the experimental frequency response.