TY - GEN
T1 - Mass Characteristics Identification and Intelligent Automatic Balancing Technology of Three-Axis Air-Bearing Testbed
AU - Xu, Xu
AU - Jierui, Zhang
AU - Jie, Qin
AU - Zening, Li
AU - Guangcheng, Ma
AU - Hongwei, Xia
N1 - Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
PY - 2022
Y1 - 2022
N2 - Mass characteristic identification and balancing of the centre of mass are the core key technologies of the full physical trial based on the three-axis air-bearing testbed. According to the above point of view, this paper proposes a mass characteristics identification method and an intelligent automatic balancing technology of a large three-axis air-bearing testbed. First, we establish the identification model of the three-axis air-bearing testbed based on the Euler angle. Next, an online identification algorithm of mass characteristics of the three-axis air-bearing testbed is investigated based on the asymptotic least squares method. Utilizing the mass characteristics obtained by the online identification algorithm, an intelligent automatic balancing algorithm for the three-axis air-bearing testbed is proposed. Finally, a physical trial is carried out to illustrate the benefits and effectiveness of the online identification algorithm and the intelligent automatic balancing algorithm. The physical trial results show that the intelligent automatic balancing algorithm proposed in this paper can be applied to most three-axis air-bearing testbed systems and the accuracy of the identification algorithm is better than 3.8%, which has high stability and application value.
AB - Mass characteristic identification and balancing of the centre of mass are the core key technologies of the full physical trial based on the three-axis air-bearing testbed. According to the above point of view, this paper proposes a mass characteristics identification method and an intelligent automatic balancing technology of a large three-axis air-bearing testbed. First, we establish the identification model of the three-axis air-bearing testbed based on the Euler angle. Next, an online identification algorithm of mass characteristics of the three-axis air-bearing testbed is investigated based on the asymptotic least squares method. Utilizing the mass characteristics obtained by the online identification algorithm, an intelligent automatic balancing algorithm for the three-axis air-bearing testbed is proposed. Finally, a physical trial is carried out to illustrate the benefits and effectiveness of the online identification algorithm and the intelligent automatic balancing algorithm. The physical trial results show that the intelligent automatic balancing algorithm proposed in this paper can be applied to most three-axis air-bearing testbed systems and the accuracy of the identification algorithm is better than 3.8%, which has high stability and application value.
KW - Asymptotic least squares
KW - Intelligent automatic balancing algorithm
KW - Mass characteristics
KW - Online identification algorithm
KW - Physical trial
KW - Three-axis air-bearing testbed
UR - https://www.scopus.com/pages/publications/85146707354
U2 - 10.1007/978-981-19-9195-0_23
DO - 10.1007/978-981-19-9195-0_23
M3 - 会议稿件
AN - SCOPUS:85146707354
SN - 9789811991943
T3 - Communications in Computer and Information Science
SP - 273
EP - 287
BT - Methods and Applications for Modeling and Simulation of Complex Systems - 21st Asia Simulation Conference, AsiaSim 2022, Proceedings
A2 - Fan, Wenhui
A2 - Zhang, Lin
A2 - Li, Ni
A2 - Song, Xiao
PB - Springer Science and Business Media Deutschland GmbH
T2 - 21st Asia Simulation Conference, AsiaSim 2022
Y2 - 9 December 2022 through 11 December 2022
ER -